Dominios, públicos y acceso - Contribuciones del usuario [es]

2001 - Manifiesto por el desarrollo ágil de software - Agile Alliance

2016-05-03T18:22:29Z

Nevi:

We are uncovering better ways of developing
software by doing it and helping others do it.
Through this work we have come to value:

Individuals and interactions over processes and tools
Working software over comprehensive documentation
Customer collaboration over contract negotiation
Responding to change over following a plan

That is, while there is value in the items on
the right, we value the items on the left more.

Autores: Kent Beck,Mike Beedle, Arie van Bennekum, Alistair Cockburn, Ward Cunningham, Martin Fowler,James Grenning, Jim Highsmith, Andrew Hunt, Ron, Jeffries, Jon Kern, Brian Marick, Robert C. Martin, Steve Mellor, Ken Schwaber, Jeff Sutherland, Dave Thomas.

Enlace:http://www.agilemanifesto.org/

Wayback Machine:https://web.archive.org/web/*/http://www.agilemanifesto.org/

[[Categoría:Manifiestos]]
[[Categoría:Kent Beck]]
[[Categoría:Mike Beedle]]
[[Categoría:Arie van Bennekum]]
[[Categoría:Alistair Cockburn]]
[[Categoría:Ward Cunningham]]
[[Categoría:Martin Fowler]]
[[Categoría:James Grenning]]
[[Categoría:Jim Highsmith]]
[[Categoría:Andrew Hunt]]
[[Categoría:Ron Jeffries]]
[[Categoría:Jon Kern]]
[[Categoría:Brian Marick]]
[[Categoría:Robert C. Martin]]
[[Categoría:Steve Mellor]]
[[Categoría:Ken Schwaber]]
[[Categoría:Jeff Sutherland]]
[[Categoría:Dave Thomas]]
[[Categoría:Inglés]]
[[Categoría:EE.UU.]]
[[Categoría:2001]]

1996 - Manifiesto de la zorra mutante - VNS Matrix

2016-05-03T18:09:30Z

Nevi:

Abres tus alas al viento atómico, que te propulsa de regreso al futuro, una entidad que viaja en el tiempo recorriendo las escurriduras del siglo XX, una maleta espacial, tal vez un ángel alienígena, asomándote a la profunda garganta de un millón de catástrofes.
pantallazo de un millónmillón de máquinas conscientes

arde brillante

usuarios atrapados en el bombardeo estático de las líneas

mirando sin ver la descarga que garabatea en sus retinas calcinadas

convulso en un éxtasis epiléptico

come código y muere

Succionado, absorbido por un vórtice de banalidad. Acabas de perderte el siglo XX. Estás al borde del milenio, ¿cuál?, ¿eso qué importa?

Lo cautivador es la mezcla de fundidos. El contagio ardoroso de la fiebre del milenio funde lo retro con lo posmo, catapultando cuerpos con órganos hacia la tecnotopía.... donde el código dicta el placer y satisface el deseo.

Applets primorosos engalanan mi garganta. Soy una cadena binaria. Soy puro artificio. Lee mi memoria de sólo lectura. Cárgame en tu imaginación pornográfica. Escríbeme.

La identidad se descomprime polimorfa y se infiltra en el sistema desde la raíz.

Partes de un no-todo innombrable cortocircuitan los programas de reconocimiento de código empujando a los agentes de vigilancia, convulsos en un ataque de pánico esquizofrénico, con un colocón de terror, a una hiperunidad frenética que vomita millones de bits de datos corruptos.

¿Qué tiene el nuevo milenio que ofrecer a las sucias masas sin módem? ¿Agua potable a gogó? La simulación tiene sus límites. ¿Están los artistas de las naciones oprimidas en una agenda paralela? ¿No será sólo seleccción natural?

La red es la niña salvaje, zorra/mutante, partogenética del Gran Papá Mainframe. La niña se nos va de las manos, Kevin, es el sistema sociopático emergente. Encierren a sus hijos, amordaza a la zorra con cinta aislante y métele una rata por el culo.

Estamos al borde de la locura y ruge la marabunta de vándalos. Amplía mi fenotipo, baby, dame un poco de ese mágico java negro y caliente del que siempre andas pavoneándote. (Ya tengo el módem entre las piernas). Los defensores del extropianismo estaban equivocados, hay algunas cosas más allá de las cuales no se puede trascender.

El placer está en la de-materialización. La de-evolución del deseo.

Somos el accidente maligno que cayó en tu sistema mientras dormías. Y cuando despiertes, terminaremos con tus falsas ilusiones digitales, secuestrando tu impecable software.

Tus dedos exploran mi red neural. El cosquilleo que sientes en las yemas son mis sinapsis respondiendo a tu contacto. No es química, es electricidad. Deja de toquetearme.

No dejes nunca de toquetear mis agujeros supurantes, ampliando mis fronteras, pero en el ciberespacio no hay fronteras

PERO EN EL ESPIRALESPACIO NO HAY ELLOS

sólo hay *nosotros*

Intentando escapar de lo binario entro en la cromozona, que no es una XXYXXYXXYXXYXXYXXYXXYXXYXXYXXYXXYXXYXXYXX

heterofóllame, baby
la resistencia es inútil
engatúsame, machihémbrame, mapea mi genoma ABANDONADO a imagen de tu proyecto

implícame artificialmente

quiero vivir eternamente

cárgame en tu brillante, brillante futuro de PVC

CHÚPAME EL CÓDIGO

Sujeto X dice que la trascendencia se encuentra en el límite de los mundos, donde ahora y entonces, aquí y allá, texto y membrana hacen impacto.

Donde la verdad se esfuma Donde nada es cierto No hay mapas

El límite es NO CARRIER/NO HAY LÍNEA, la súbita conmoción de la falta de contacto, intentar tocar y encontrar una piel fría...

El límite es permiso denegado, visión doble y necrosis.

Donde la verdad se esfuma Donde nada es cierto No hay mapas

El límite es NO CARRIER / NO HAY LÍNEA, la súbita conmoción de la falta de contacto, intentar tocar y encontrar una piel fría...

El límite es permiso denegado, doble visión y necrosis.

Error de línea de comandos

Los párpados caen como cortinas de plomo. Hielo caliente besa mis sinapsis en una carrera e(x/s)tática. Mi sistema está nervioso, mis neuronas aúllan – dibujando una espiral hacia la singularidad. Flotando en el éter, mi cuerpo se comprime.

Me convierto en el FUEGO.

Incéndiame si te atreves.

Traducción de Carolina Díaz Soto.

Enlace: http://www.estudiosonline.net/texts/vns_matrix.html

Wayback Machine:https://web.archive.org/web/*/http://www.estudiosonline.net/texts/vns_matrix.html

[[Categoría:Manifiestos]]
[[Categoría:VNS Matrix]]
[[Categoría:Español]]
[[Categoría:Australia]]
[[Categoría:1996]]

1991 - Manifiesto ciberfeminista para el siglo XXI - VNS Matrix

2016-05-03T18:06:24Z

Nevi:

we are the modern cunt
positive anti reason
unbounded unleashed unforgiving

we see art with our cunt we make art with our cunt

we believe in jouissance madness holiness and poetry

we are the virus of the new world disorder

rupturing the symbolic from within

saboteurs of big daddy mainframe

the clitoris is a direct line to the matrix

VNS MATRIX

terminators of the moral code

mercenaries of slime

go down on the altar of abjection

probing the visceral temple we speak in tongues

infiltrating disrupting disseminating

corrupting the discourse

we are the future cunt

Enlace: http://www.obn.org/reading_room/manifestos/html/cyberfeminist.html

Wayback Machine:https://web.archive.org/web/20160313031444/http://www.obn.org/reading_room/manifestos/html/cyberfeminist.html

[[Categoría:Manifiestos]]
[[Categoría:Inglés]]
[[Categoría:Australia]]
[[Categoría:1991]]
[[Categoría:VNS Matrix]]

1991 - Manifiesto ciberfeminista para el siglo XXI - VNS Matrix

2016-05-03T18:05:11Z

Nevi:

we are the modern cunt
positive anti reason
unbounded unleashed unforgiving
we see art with our cunt we make art with our cunt
we believe in jouissance madness holiness and poetry
we are the virus of the new world disorder
rupturing the symbolic from within
saboteurs of big daddy mainframe
the clitoris is a direct line to the matrix
VNS MATRIX
terminators of the moral code
mercenaries of slime
go down on the altar of abjection
probing the visceral temple we speak in tongues
infiltrating disrupting disseminating
corrupting the discourse
we are the future cunt

Enlace: http://www.obn.org/reading_room/manifestos/html/cyberfeminist.html

Wayback Machine:https://web.archive.org/web/20160313031444/http://www.obn.org/reading_room/manifestos/html/cyberfeminist.html

[[Categoría:Manifiestos]]
[[Categoría:Inglés]]
[[Categoría:Australia]]
[[Categoría:1991]]
[[Categoría:VNS Matrix]]

2014 - The Data Manifesto - Development Initiatives

2016-04-07T00:03:15Z

Nevi:

=== Staging a Data Revolution ===

Accessible, useable, timely and complete data is core to sustainable development and social progress. Access to information provides people with a base to make better choices and have more control over their lives. Too often attempts to deliver sustainable economic, social and environmental results are hindered by the failure to get the right information, in the right format, to the right people, at the right time. Worse still, the most acute data deficits often affect the people and countries facing the most acute problems.

The Data Revolution should be about data grounded in real life. Data and information that gets to the people who need it at national and sub-national levels to help with the decisions they face – hospital directors, school managers, city councillors, parliamentarians. Data that goes beyond averages – that is disaggregated to show the different impacts of decisions, policies and investments on gender, social groups and people living in different places and over time.

We need a Data Revolution that sets a new political agenda, that puts existing data to work, that improves the way data is gathered and ensures that information can be used. To deliver this vision, we need the following steps.

'''12 steps to a Data Revolution'''

Implement a national ‘Data Pledge’ to citizens that is supported by governments, private and non-governmental sectors
Address real world questions with joined up and disaggregated data
Empower and up-skill data users of the future through education
Examine existing frameworks and publish existing data
Build an information bank of data assets
Allocate funding available for better data according to national and sub-national priorities
Strengthen national statistical systems’ capacity to collect data
Implement a policy that data is ‘open by default’
Improve data quality by subjecting it to public scrutiny
Put information users’ needs first
Recognise technology cannot solve all barriers to information
Invest in infomediaries’ capacity to translate data into information that policymakers, civil society and the media can actually use

'''It is time for data to become a central building block for better choices.'''
'''It is time to put the power of information to work.
'''

=== Setting a new agenda ===

A revolution in the production, access to and use of data demands a new agenda. Without clear political leadership and public commitments to a shared approach, the step-change in capacity for better data at every level will not be delivered. Three core political actions are necessary for the Data Revolution to release the power of information:

'''1. Implement a national ‘Data Pledge’ to citizens that is supported by governments, private and non-governmental sectors
'''
Commitments to better data must primarily be between a government and its people. All governments should make a public ‘Data Pledge’. Private and non-governmental sectors should follow suit and pledge to support national governments to fulfil the ‘Data Pledge’.

The national '''‘Data Pledge’''' should:

Publicly acknowledge the Data Revolution and the imperative to improve public data for decision-making, accountability and improved service delivery.
Commit to putting all existing data to work by publishing all data currently in government systems.
Produce a data investment plan to finance the systems and structures needed to achieve better data through to 2030.
Adopt a comprehensive and consistent policy for opening up all government data quickly.
Ensure the data does not become an extractive industry – extracting information from local populations – but protects the public’s right to information about their own society by publishing data in a way that is accessible not just to the few but to all.
Introduce regular consultations with civil society organisations (CSO), local governments and businesses to inform the release of data that meets their needs and enables better participation in local governing processes and decisions.
'''2. Address real world questions with joined up and disaggregated data'''

Very few datasets tell a story in isolation. Answers to real world questions often need data from different sources to be joined up and disaggregated so that the impacts on different people and locations can be traced. Data can only be joined up if it can be compared – using common definitions and standards. We need urgent political will to establish basic pillars for the publication of data for all data publishers to adhere to. To get beyond the averages we need a major effort to gather disaggregated data on both the income and wellbeing (in health, education, water and sanitation) of the poorest 20% of people, ensuring no one is left behind.

'''3. Empower and upskill data users of the future through education'''

It is not enough to put the data out there: the data needs to be accessible and useable by all sections of society to overcome of the current lack of trust in data: otherwise the Data Revolution risks merely reinforcing the existing power dynamic. We need a widespread education programme that informs people of their access to information rights and empowers them with knowledge and skills to act on those rights.

=== Putting existing data to work ===

Lots of data exists already. Across the world, data availability and quality has improved dramatically during the past two decades. Aggregated development, social and health indicators have been in the public domain for many years. Yet much of the data in most national statistics systems is still private, leaving its economic and social potential untapped.

'''4. Examine existing frameworks and publish existing data'''

The Data Revolution should put to use the large amounts of data that already exist in national statistics and other information systems. Public data should be made public. All governments should start by examining the frameworks and publish data that already exists, in as detailed form as possible, with a particular focus on:

Administrative and geographic infrastructures
Budgets and censuses
Health, education and agricultural data from national management information systems
All anonymised microdata collected through publicly funded initiatives (such as household surveys)
Panel data measuring what has happened to the same people over time

'''5. Build an information bank of data assets'''

The private sector has expertise in gathering and using data on its customers, supply chains and the provenance of goods and services. Mobile technologies, internet and social media all create opportunities for gathering and communicating data – including from people and places that are currently least well served with data. To put these existing data assets to work, they need to be visible. Governments need to provide incentives for open publication of all data from private and public sources. National audits of data assets should be developed, bringing together data that is often held in sectoral silos. The private sector should work in partnership with governments to show how the data they own, such as mobile phone data, could be provided as a public good to complement and improve public data.

=== Gathering better data ===

'''6. Allocate funding available for better data according to national and sub-national priorities'''

There are limited resources to improve data and decision makers have different and sometimes conflicting needs. How the limited resources available to improve data are allocated should therefore be determined by national and sub-national priorities of where greatest impact on poverty can be felt. Allocations should not be driven by international commitments or donor requirements.

'''7. Strengthen national statistical systems’ capacity to collect data
'''
The challenges for national statistics systems and solutions are now well documented and must be addressed. They should be tackled through actions such as:<ref>[1] Centre for Global Development and African Population and Health Research Center, Delivering on the Data Revolution in Sub-Saharan Africa, July 2014 www.cgdev.org/sites/default/files/delivering-data-revolution-sub-saharan-africa-pdf.pdf</ref>

Enhance the functional autonomy by recognising the national statistical system as an independent function and ensure national statistics offices receive greater independence from political influence.
Reduce donor dependency and fund national statistics offices more from national budgets, based on the business case for investing in better data.
Experiment with new institutional models such as public–private partnerships and crowd-sourcing to collect hard-to-get data or outsource data collection activities.
Build quality control mechanisms into data collection to improve accuracy.
Improve technical infrastructures for data collection, storage and publishing.

'''8. Implement a policy that data is ‘open by default’
'''
Where data is available, there are often limitations on how it can be accessed and used. Firstly, data sources are rarely openly licensed, so users are not clear whether they can use and redistribute the data. Secondly, the format is not always machine-readable. Much of the data lives in PDF files or websites. Users need different kinds of information for different purposes, so information needs to be published in a machine-readable format and under open licenses that allow users to access the data and re-purpose it to meet their individual needs.

'''9. Improve data quality by subjecting it to public scrutiny
'''
Good quality data – data that is accurate, complete and timely – is critical, and data providers should provide mechanisms for data users to feedback and suggest how it can be improved. Too often policy prescriptions fail to alert the reader of the underlying quality of the data. Hence policy makers are not alerted to the poor quality of the data, reducing their incentive to invest in improving it. Data users and policy makers need to adopt a code of practice and always ask, always tell on the provenance and quality of the data.

=== Ensuring better information ===

How data is produced and used matters for how beneficial it ultimately is. Despite the potential that ‘more data’ holds, publishing data on its own is not enough. More data does not always mean better information. Data needs combining, contextualising and explaining if it is to be turned into information that elected officials and civil society can act on.

'''10. Put information users’ needs first
'''
Data analysis and information delivery must be driven by the needs of national and sub-national decision-makers and those who need to hold them accountable. Too often published data meets the needs of producers rather than users of information, for whom it is inaccessible or too complex. The needs of data users and local decision-makers must be put first by asking themthrough regular consultations what information they need, how they need it, and when.

'''11. Recognise technology cannot solve all barriers to information'''

Getting the right information, in the right format, to right people, at the right time is challenging. Despite legal frameworks for freedom of information or open data, significant technological, human and bureaucratic challenges must still be overcome. These include unstable power supplies, the lack of functioning websites, very limited numbers of information technology specialists or dedicated information officers working in government, cumbersome procedures to access information, and publication in formats that are difficult to disseminate. Addressing these obstacles requires an understanding of the whole data ecosystem – not just a focus on technological solutions.

'''12. Invest in infomediaries’ capacity to translate data into information that policymakers, civil society and the media can actually use
'''
Most ‘users’ don’t want to handle raw data; they need it translated into accessible information. Open data does not in itself provide usable information. In short, data is for machines; information is for people. We need investment to develop and support a cadre of data literate infomediaries – including government departments, information communication technology, research and non-governmental organisations, and journalists to translate data into a form that policymakers, civil society and the media can actually use.

Enlace:http://devinit.org/#!/post/data-manifesto-2, http://devinit.org/wp-content/uploads/2014/10/DI-data-revolution-manifesto21.pdf

Wayback Machine: http://web.archive.org/web/20160327233347/http://devinit.org/,

[[Categoría:Manifiestos]]
[[Categoría:Development Initiatives]]
[[Categoría:Inglés]]
[[Categoría:Reino Unido]]
[[Categoría:Kenia]]
[[Categoría:2014]]

2014 - The Data Manifesto - Development Initiatives

2016-04-07T00:00:44Z

Nevi:

=== Staging a Data Revolution ===

Accessible, useable, timely and complete data is core to sustainable development and social progress. Access to information provides people with a base to make better choices and have more control over their lives. Too often attempts to deliver sustainable economic, social and environmental results are hindered by the failure to get the right information, in the right format, to the right people, at the right time. Worse still, the most acute data deficits often affect the people and countries facing the most acute problems.

The Data Revolution should be about data grounded in real life. Data and information that gets to the people who need it at national and sub-national levels to help with the decisions they face – hospital directors, school managers, city councillors, parliamentarians. Data that goes beyond averages – that is disaggregated to show the different impacts of decisions, policies and investments on gender, social groups and people living in different places and over time.

We need a Data Revolution that sets a new political agenda, that puts existing data to work, that improves the way data is gathered and ensures that information can be used. To deliver this vision, we need the following steps.

'''12 steps to a Data Revolution'''

Implement a national ‘Data Pledge’ to citizens that is supported by governments, private and non-governmental sectors
Address real world questions with joined up and disaggregated data
Empower and up-skill data users of the future through education
Examine existing frameworks and publish existing data
Build an information bank of data assets
Allocate funding available for better data according to national and sub-national priorities
Strengthen national statistical systems’ capacity to collect data
Implement a policy that data is ‘open by default’
Improve data quality by subjecting it to public scrutiny
Put information users’ needs first
Recognise technology cannot solve all barriers to information
Invest in infomediaries’ capacity to translate data into information that policymakers, civil society and the media can actually use

'''It is time for data to become a central building block for better choices.'''
'''It is time to put the power of information to work.
'''

=== Setting a new agenda ===

A revolution in the production, access to and use of data demands a new agenda. Without clear political leadership and public commitments to a shared approach, the step-change in capacity for better data at every level will not be delivered. Three core political actions are necessary for the Data Revolution to release the power of information:

'''1. Implement a national ‘Data Pledge’ to citizens that is supported by governments, private and non-governmental sectors
'''
Commitments to better data must primarily be between a government and its people. All governments should make a public ‘Data Pledge’. Private and non-governmental sectors should follow suit and pledge to support national governments to fulfil the ‘Data Pledge’.

The national '''‘Data Pledge’''' should:

Publicly acknowledge the Data Revolution and the imperative to improve public data for decision-making, accountability and improved service delivery.
Commit to putting all existing data to work by publishing all data currently in government systems.
Produce a data investment plan to finance the systems and structures needed to achieve better data through to 2030.
Adopt a comprehensive and consistent policy for opening up all government data quickly.
Ensure the data does not become an extractive industry – extracting information from local populations – but protects the public’s right to information about their own society by publishing data in a way that is accessible not just to the few but to all.
Introduce regular consultations with civil society organisations (CSO), local governments and businesses to inform the release of data that meets their needs and enables better participation in local governing processes and decisions.
'''2. Address real world questions with joined up and disaggregated data'''

Very few datasets tell a story in isolation. Answers to real world questions often need data from different sources to be joined up and disaggregated so that the impacts on different people and locations can be traced. Data can only be joined up if it can be compared – using common definitions and standards. We need urgent political will to establish basic pillars for the publication of data for all data publishers to adhere to. To get beyond the averages we need a major effort to gather disaggregated data on both the income and wellbeing (in health, education, water and sanitation) of the poorest 20% of people, ensuring no one is left behind.

'''3. Empower and upskill data users of the future through education'''

It is not enough to put the data out there: the data needs to be accessible and useable by all sections of society to overcome of the current lack of trust in data: otherwise the Data Revolution risks merely reinforcing the existing power dynamic. We need a widespread education programme that informs people of their access to information rights and empowers them with knowledge and skills to act on those rights.

=== Putting existing data to work ===

Lots of data exists already. Across the world, data availability and quality has improved dramatically during the past two decades. Aggregated development, social and health indicators have been in the public domain for many years. Yet much of the data in most national statistics systems is still private, leaving its economic and social potential untapped.

'''4. Examine existing frameworks and publish existing data'''

The Data Revolution should put to use the large amounts of data that already exist in national statistics and other information systems. Public data should be made public. All governments should start by examining the frameworks and publish data that already exists, in as detailed form as possible, with a particular focus on:

Administrative and geographic infrastructures
Budgets and censuses
Health, education and agricultural data from national management information systems
All anonymised microdata collected through publicly funded initiatives (such as household surveys)
Panel data measuring what has happened to the same people over time

'''5. Build an information bank of data assets'''

The private sector has expertise in gathering and using data on its customers, supply chains and the provenance of goods and services. Mobile technologies, internet and social media all create opportunities for gathering and communicating data – including from people and places that are currently least well served with data. To put these existing data assets to work, they need to be visible. Governments need to provide incentives for open publication of all data from private and public sources. National audits of data assets should be developed, bringing together data that is often held in sectoral silos. The private sector should work in partnership with governments to show how the data they own, such as mobile phone data, could be provided as a public good to complement and improve public data.

=== Gathering better data ===

'''6. Allocate funding available for better data according to national and sub-national priorities'''

There are limited resources to improve data and decision makers have different and sometimes conflicting needs. How the limited resources available to improve data are allocated should therefore be determined by national and sub-national priorities of where greatest impact on poverty can be felt. Allocations should not be driven by international commitments or donor requirements.

'''7. Strengthen national statistical systems’ capacity to collect data
'''
The challenges for national statistics systems and solutions are now well documented and must be addressed. They should be tackled through actions such as:[1]

Enhance the functional autonomy by recognising the national statistical system as an independent function and ensure national statistics offices receive greater independence from political influence.
Reduce donor dependency and fund national statistics offices more from national budgets, based on the business case for investing in better data.
Experiment with new institutional models such as public–private partnerships and crowd-sourcing to collect hard-to-get data or outsource data collection activities.
Build quality control mechanisms into data collection to improve accuracy.
Improve technical infrastructures for data collection, storage and publishing.

'''8. Implement a policy that data is ‘open by default’
'''
Where data is available, there are often limitations on how it can be accessed and used. Firstly, data sources are rarely openly licensed, so users are not clear whether they can use and redistribute the data. Secondly, the format is not always machine-readable. Much of the data lives in PDF files or websites. Users need different kinds of information for different purposes, so information needs to be published in a machine-readable format and under open licenses that allow users to access the data and re-purpose it to meet their individual needs.

'''9. Improve data quality by subjecting it to public scrutiny
'''
Good quality data – data that is accurate, complete and timely – is critical, and data providers should provide mechanisms for data users to feedback and suggest how it can be improved. Too often policy prescriptions fail to alert the reader of the underlying quality of the data. Hence policy makers are not alerted to the poor quality of the data, reducing their incentive to invest in improving it. Data users and policy makers need to adopt a code of practice and always ask, always tell on the provenance and quality of the data.

=== Ensuring better information ===

How data is produced and used matters for how beneficial it ultimately is. Despite the potential that ‘more data’ holds, publishing data on its own is not enough. More data does not always mean better information. Data needs combining, contextualising and explaining if it is to be turned into information that elected officials and civil society can act on.

'''10. Put information users’ needs first
'''
Data analysis and information delivery must be driven by the needs of national and sub-national decision-makers and those who need to hold them accountable. Too often published data meets the needs of producers rather than users of information, for whom it is inaccessible or too complex. The needs of data users and local decision-makers must be put first by asking themthrough regular consultations what information they need, how they need it, and when.

'''11. Recognise technology cannot solve all barriers to information'''

Getting the right information, in the right format, to right people, at the right time is challenging. Despite legal frameworks for freedom of information or open data, significant technological, human and bureaucratic challenges must still be overcome. These include unstable power supplies, the lack of functioning websites, very limited numbers of information technology specialists or dedicated information officers working in government, cumbersome procedures to access information, and publication in formats that are difficult to disseminate. Addressing these obstacles requires an understanding of the whole data ecosystem – not just a focus on technological solutions.

'''12. Invest in infomediaries’ capacity to translate data into information that policymakers, civil society and the media can actually use
'''
Most ‘users’ don’t want to handle raw data; they need it translated into accessible information. Open data does not in itself provide usable information. In short, data is for machines; information is for people. We need investment to develop and support a cadre of data literate infomediaries – including government departments, information communication technology, research and non-governmental organisations, and journalists to translate data into a form that policymakers, civil society and the media can actually use.

[1] Centre for Global Development and African Population and Health Research Center, Delivering on the Data Revolution in Sub-Saharan Africa, July 2014 www.cgdev.org/sites/default/files/delivering-data-revolution-sub-saharan-africa-pdf.pdf

Enlace:http://devinit.org/#!/post/data-manifesto-2, http://devinit.org/wp-content/uploads/2014/10/DI-data-revolution-manifesto21.pdf

Wayback Machine: http://web.archive.org/web/20160327233347/http://devinit.org/,

[[Categoría:Manifiestos]]
[[Categoría:Development Initiatives]]
[[Categoría:Inglés]]
[[Categoría:Reino Unido]]
[[Categoría:Kenia]]
[[Categoría:2014]]

2014 - The Data Manifesto - Development Initiatives

2016-04-07T00:00:07Z

Nevi:

=== Staging a Data Revolution ===

Accessible, useable, timely and complete data is core to sustainable development and social progress. Access to information provides people with a base to make better choices and have more control over their lives. Too often attempts to deliver sustainable economic, social and environmental results are hindered by the failure to get the right information, in the right format, to the right people, at the right time. Worse still, the most acute data deficits often affect the people and countries facing the most acute problems.

The Data Revolution should be about data grounded in real life. Data and information that gets to the people who need it at national and sub-national levels to help with the decisions they face – hospital directors, school managers, city councillors, parliamentarians. Data that goes beyond averages – that is disaggregated to show the different impacts of decisions, policies and investments on gender, social groups and people living in different places and over time.

We need a Data Revolution that sets a new political agenda, that puts existing data to work, that improves the way data is gathered and ensures that information can be used. To deliver this vision, we need the following steps.

'''12 steps to a Data Revolution'''

Implement a national ‘Data Pledge’ to citizens that is supported by governments, private and non-governmental sectors
Address real world questions with joined up and disaggregated data
Empower and up-skill data users of the future through education
Examine existing frameworks and publish existing data
Build an information bank of data assets
Allocate funding available for better data according to national and sub-national priorities
Strengthen national statistical systems’ capacity to collect data
Implement a policy that data is ‘open by default’
Improve data quality by subjecting it to public scrutiny
Put information users’ needs first
Recognise technology cannot solve all barriers to information
Invest in infomediaries’ capacity to translate data into information that policymakers, civil society and the media can actually use

'''It is time for data to become a central building block for better choices.'''
'''It is time to put the power of information to work.
'''

=== Setting a new agenda ===

A revolution in the production, access to and use of data demands a new agenda. Without clear political leadership and public commitments to a shared approach, the step-change in capacity for better data at every level will not be delivered. Three core political actions are necessary for the Data Revolution to release the power of information:

'''1. Implement a national ‘Data Pledge’ to citizens that is supported by governments, private and non-governmental sectors
'''
Commitments to better data must primarily be between a government and its people. All governments should make a public ‘Data Pledge’. Private and non-governmental sectors should follow suit and pledge to support national governments to fulfil the ‘Data Pledge’.

The national '''‘Data Pledge’''' should:

Publicly acknowledge the Data Revolution and the imperative to improve public data for decision-making, accountability and improved service delivery.
Commit to putting all existing data to work by publishing all data currently in government systems.
Produce a data investment plan to finance the systems and structures needed to achieve better data through to 2030.
Adopt a comprehensive and consistent policy for opening up all government data quickly.
Ensure the data does not become an extractive industry – extracting information from local populations – but protects the public’s right to information about their own society by publishing data in a way that is accessible not just to the few but to all.
Introduce regular consultations with civil society organisations (CSO), local governments and businesses to inform the release of data that meets their needs and enables better participation in local governing processes and decisions.
'''2. Address real world questions with joined up and disaggregated data'''

Very few datasets tell a story in isolation. Answers to real world questions often need data from different sources to be joined up and disaggregated so that the impacts on different people and locations can be traced. Data can only be joined up if it can be compared – using common definitions and standards. We need urgent political will to establish basic pillars for the publication of data for all data publishers to adhere to. To get beyond the averages we need a major effort to gather disaggregated data on both the income and wellbeing (in health, education, water and sanitation) of the poorest 20% of people, ensuring no one is left behind.

'''3. Empower and upskill data users of the future through education'''

It is not enough to put the data out there: the data needs to be accessible and useable by all sections of society to overcome of the current lack of trust in data: otherwise the Data Revolution risks merely reinforcing the existing power dynamic. We need a widespread education programme that informs people of their access to information rights and empowers them with knowledge and skills to act on those rights.

=== Putting existing data to work ===

Lots of data exists already. Across the world, data availability and quality has improved dramatically during the past two decades. Aggregated development, social and health indicators have been in the public domain for many years. Yet much of the data in most national statistics systems is still private, leaving its economic and social potential untapped.

'''4. Examine existing frameworks and publish existing data'''

The Data Revolution should put to use the large amounts of data that already exist in national statistics and other information systems. Public data should be made public. All governments should start by examining the frameworks and publish data that already exists, in as detailed form as possible, with a particular focus on:

Administrative and geographic infrastructures
Budgets and censuses
Health, education and agricultural data from national management information systems
All anonymised microdata collected through publicly funded initiatives (such as household surveys)
Panel data measuring what has happened to the same people over time

'''5. Build an information bank of data assets'''

The private sector has expertise in gathering and using data on its customers, supply chains and the provenance of goods and services. Mobile technologies, internet and social media all create opportunities for gathering and communicating data – including from people and places that are currently least well served with data. To put these existing data assets to work, they need to be visible. Governments need to provide incentives for open publication of all data from private and public sources. National audits of data assets should be developed, bringing together data that is often held in sectoral silos. The private sector should work in partnership with governments to show how the data they own, such as mobile phone data, could be provided as a public good to complement and improve public data.

=== Gathering better data ===

'''6. Allocate funding available for better data according to national and sub-national priorities'''

There are limited resources to improve data and decision makers have different and sometimes conflicting needs. How the limited resources available to improve data are allocated should therefore be determined by national and sub-national priorities of where greatest impact on poverty can be felt. Allocations should not be driven by international commitments or donor requirements.

'''7. Strengthen national statistical systems’ capacity to collect data
'''
The challenges for national statistics systems and solutions are now well documented and must be addressed. They should be tackled through actions such as:[1]

Enhance the functional autonomy by recognising the national statistical system as an independent function and ensure national statistics offices receive greater independence from political influence.
Reduce donor dependency and fund national statistics offices more from national budgets, based on the business case for investing in better data.
Experiment with new institutional models such as public–private partnerships and crowd-sourcing to collect hard-to-get data or outsource data collection activities.
Build quality control mechanisms into data collection to improve accuracy.
Improve technical infrastructures for data collection, storage and publishing.

'''8. Implement a policy that data is ‘open by default’
'''
Where data is available, there are often limitations on how it can be accessed and used. Firstly, data sources are rarely openly licensed, so users are not clear whether they can use and redistribute the data. Secondly, the format is not always machine-readable. Much of the data lives in PDF files or websites. Users need different kinds of information for different purposes, so information needs to be published in a machine-readable format and under open licenses that allow users to access the data and re-purpose it to meet their individual needs.

'''9. Improve data quality by subjecting it to public scrutiny
'''
Good quality data – data that is accurate, complete and timely – is critical, and data providers should provide mechanisms for data users to feedback and suggest how it can be improved. Too often policy prescriptions fail to alert the reader of the underlying quality of the data. Hence policy makers are not alerted to the poor quality of the data, reducing their incentive to invest in improving it. Data users and policy makers need to adopt a code of practice and always ask, always tell on the provenance and quality of the data.

=== Ensuring better information ===

How data is produced and used matters for how beneficial it ultimately is. Despite the potential that ‘more data’ holds, publishing data on its own is not enough. More data does not always mean better information. Data needs combining, contextualising and explaining if it is to be turned into information that elected officials and civil society can act on.

'''10. Put information users’ needs first
'''
Data analysis and information delivery must be driven by the needs of national and sub-national decision-makers and those who need to hold them accountable. Too often published data meets the needs of producers rather than users of information, for whom it is inaccessible or too complex. The needs of data users and local decision-makers must be put first by asking themthrough regular consultations what information they need, how they need it, and when.

'''11. Recognise technology cannot solve all barriers to information'''

Getting the right information, in the right format, to right people, at the right time is challenging. Despite legal frameworks for freedom of information or open data, significant technological, human and bureaucratic challenges must still be overcome. These include unstable power supplies, the lack of functioning websites, very limited numbers of information technology specialists or dedicated information officers working in government, cumbersome procedures to access information, and publication in formats that are difficult to disseminate. Addressing these obstacles requires an understanding of the whole data ecosystem – not just a focus on technological solutions.

'''12. Invest in infomediaries’ capacity to translate data into information that policymakers, civil society and the media can actually use
'''
Most ‘users’ don’t want to handle raw data; they need it translated into accessible information. Open data does not in itself provide usable information. In short, data is for machines; information is for people. We need investment to develop and support a cadre of data literate infomediaries – including government departments, information communication technology, research and non-governmental organisations, and journalists to translate data into a form that policymakers, civil society and the media can actually use.

[1] Centre for Global Development and African Population and Health Research Center, Delivering on the Data Revolution in Sub-Saharan Africa, July 2014 www.cgdev.org/sites/default/files/delivering-data-revolution-sub-saharan-africa-pdf.pdf

Enlace:http://devinit.org/#!/post/data-manifesto-2, http://devinit.org/wp-content/uploads/2014/10/DI-data-revolution-manifesto21.pdf

Wayback Machine: http://web.archive.org/web/20160327233347/http://devinit.org/,

[[Categoría:Manifiestos]]
[[Categoría:Development Initiatives]]
[[Categoría:Inglés]]
[[Categoría:Reino Unido]]
[[Categoría:Kenia]]
[[Categoría:2014]]

2014 - The Data Manifesto - Development Initiatives

2016-04-06T23:56:59Z

Nevi:

=== Staging a Data Revolution ===

Accessible, useable, timely and complete data is core to sustainable development and social progress. Access to information provides people with a base to make better choices and have more control over their lives. Too often attempts to deliver sustainable economic, social and environmental results are hindered by the failure to get the right information, in the right format, to the right people, at the right time. Worse still, the most acute data deficits often affect the people and countries facing the most acute problems.

The Data Revolution should be about data grounded in real life. Data and information that gets to the people who need it at national and sub-national levels to help with the decisions they face – hospital directors, school managers, city councillors, parliamentarians. Data that goes beyond averages – that is disaggregated to show the different impacts of decisions, policies and investments on gender, social groups and people living in different places and over time.

We need a Data Revolution that sets a new political agenda, that puts existing data to work, that improves the way data is gathered and ensures that information can be used. To deliver this vision, we need the following steps.

'''12 steps to a Data Revolution'''

Implement a national ‘Data Pledge’ to citizens that is supported by governments, private and non-governmental sectors
Address real world questions with joined up and disaggregated data
Empower and up-skill data users of the future through education
Examine existing frameworks and publish existing data
Build an information bank of data assets
Allocate funding available for better data according to national and sub-national priorities
Strengthen national statistical systems’ capacity to collect data
Implement a policy that data is ‘open by default’
Improve data quality by subjecting it to public scrutiny
Put information users’ needs first
Recognise technology cannot solve all barriers to information
Invest in infomediaries’ capacity to translate data into information that policymakers, civil society and the media can actually use

'''It is time for data to become a central building block for better choices.
It is time to put the power of information to work.
'''

=== Setting a new agenda ===

A revolution in the production, access to and use of data demands a new agenda. Without clear political leadership and public commitments to a shared approach, the step-change in capacity for better data at every level will not be delivered. Three core political actions are necessary for the Data Revolution to release the power of information:

'''1. Implement a national ‘Data Pledge’ to citizens that is supported by governments, private and non-governmental sectors
'''
Commitments to better data must primarily be between a government and its people. All governments should make a public ‘Data Pledge’. Private and non-governmental sectors should follow suit and pledge to support national governments to fulfil the ‘Data Pledge’.

The national '''‘Data Pledge’''' should:

Publicly acknowledge the Data Revolution and the imperative to improve public data for decision-making, accountability and improved service delivery.
Commit to putting all existing data to work by publishing all data currently in government systems.
Produce a data investment plan to finance the systems and structures needed to achieve better data through to 2030.
Adopt a comprehensive and consistent policy for opening up all government data quickly.
Ensure the data does not become an extractive industry – extracting information from local populations – but protects the public’s right to information about their own society by publishing data in a way that is accessible not just to the few but to all.
Introduce regular consultations with civil society organisations (CSO), local governments and businesses to inform the release of data that meets their needs and enables better participation in local governing processes and decisions.
'''2. Address real world questions with joined up and disaggregated data'''

Very few datasets tell a story in isolation. Answers to real world questions often need data from different sources to be joined up and disaggregated so that the impacts on different people and locations can be traced. Data can only be joined up if it can be compared – using common definitions and standards. We need urgent political will to establish basic pillars for the publication of data for all data publishers to adhere to. To get beyond the averages we need a major effort to gather disaggregated data on both the income and wellbeing (in health, education, water and sanitation) of the poorest 20% of people, ensuring no one is left behind.

'''3. Empower and upskill data users of the future through education'''

It is not enough to put the data out there: the data needs to be accessible and useable by all sections of society to overcome of the current lack of trust in data: otherwise the Data Revolution risks merely reinforcing the existing power dynamic. We need a widespread education programme that informs people of their access to information rights and empowers them with knowledge and skills to act on those rights.

Putting existing data to work

Lots of data exists already. Across the world, data availability and quality has improved dramatically during the past two decades. Aggregated development, social and health indicators have been in the public domain for many years. Yet much of the data in most national statistics systems is still private, leaving its economic and social potential untapped.

4. Examine existing frameworks and publish existing data

The Data Revolution should put to use the large amounts of data that already exist in national statistics and other information systems. Public data should be made public. All governments should start by examining the frameworks and publish data that already exists, in as detailed form as possible, with a particular focus on:

Administrative and geographic infrastructures
Budgets and censuses
Health, education and agricultural data from national management information systems
All anonymised microdata collected through publicly funded initiatives (such as household surveys)
Panel data measuring what has happened to the same people over time
5. Build an information bank of data assets

The private sector has expertise in gathering and using data on its customers, supply chains and the provenance of goods and services. Mobile technologies, internet and social media all create opportunities for gathering and communicating data – including from people and places that are currently least well served with data. To put these existing data assets to work, they need to be visible. Governments need to provide incentives for open publication of all data from private and public sources. National audits of data assets should be developed, bringing together data that is often held in sectoral silos. The private sector should work in partnership with governments to show how the data they own, such as mobile phone data, could be provided as a public good to complement and improve public data.

Gathering better data

6. Allocate funding available for better data according to national and sub-national priorities

There are limited resources to improve data and decision makers have different and sometimes conflicting needs. How the limited resources available to improve data are allocated should therefore be determined by national and sub-national priorities of where greatest impact on poverty can be felt. Allocations should not be driven by international commitments or donor requirements.

7. Strengthen national statistical systems’ capacity to collect data

The challenges for national statistics systems and solutions are now well documented and must be addressed. They should be tackled through actions such as:[1]

Enhance the functional autonomy by recognising the national statistical system as an independent function and ensure national statistics offices receive greater independence from political influence.
Reduce donor dependency and fund national statistics offices more from national budgets, based on the business case for investing in better data.
Experiment with new institutional models such as public–private partnerships and crowd-sourcing to collect hard-to-get data or outsource data collection activities.
Build quality control mechanisms into data collection to improve accuracy.
Improve technical infrastructures for data collection, storage and publishing.
8. Implement a policy that data is ‘open by default’

Where data is available, there are often limitations on how it can be accessed and used. Firstly, data sources are rarely openly licensed, so users are not clear whether they can use and redistribute the data. Secondly, the format is not always machine-readable. Much of the data lives in PDF files or websites. Users need different kinds of information for different purposes, so information needs to be published in a machine-readable format and under open licenses that allow users to access the data and re-purpose it to meet their individual needs.

9. Improve data quality by subjecting it to public scrutiny

Good quality data – data that is accurate, complete and timely – is critical, and data providers should provide mechanisms for data users to feedback and suggest how it can be improved. Too often policy prescriptions fail to alert the reader of the underlying quality of the data. Hence policy makers are not alerted to the poor quality of the data, reducing their incentive to invest in improving it. Data users and policy makers need to adopt a code of practice and always ask, always tell on the provenance and quality of the data.

Ensuring better information

How data is produced and used matters for how beneficial it ultimately is. Despite the potential that ‘more data’ holds, publishing data on its own is not enough. More data does not always mean better information. Data needs combining, contextualising and explaining if it is to be turned into information that elected officials and civil society can act on.

10. Put information users’ needs first

Data analysis and information delivery must be driven by the needs of national and sub-national decision-makers and those who need to hold them accountable. Too often published data meets the needs of producers rather than users of information, for whom it is inaccessible or too complex. The needs of data users and local decision-makers must be put first by asking themthrough regular consultations what information they need, how they need it, and when.

11. Recognise technology cannot solve all barriers to information

Getting the right information, in the right format, to right people, at the right time is challenging. Despite legal frameworks for freedom of information or open data, significant technological, human and bureaucratic challenges must still be overcome. These include unstable power supplies, the lack of functioning websites, very limited numbers of information technology specialists or dedicated information officers working in government, cumbersome procedures to access information, and publication in formats that are difficult to disseminate. Addressing these obstacles requires an understanding of the whole data ecosystem – not just a focus on technological solutions.

12. Invest in infomediaries’ capacity to translate data into information that policymakers, civil society and the media can actually use

Most ‘users’ don’t want to handle raw data; they need it translated into accessible information. Open data does not in itself provide usable information. In short, data is for machines; information is for people. We need investment to develop and support a cadre of data literate infomediaries – including government departments, information communication technology, research and non-governmental organisations, and journalists to translate data into a form that policymakers, civil society and the media can actually use.

[1] Centre for Global Development and African Population and Health Research Center, Delivering on the Data Revolution in Sub-Saharan Africa, July 2014 www.cgdev.org/sites/default/files/delivering-data-revolution-sub-saharan-africa-pdf.pdf

Enlace:http://devinit.org/#!/post/data-manifesto-2, http://devinit.org/wp-content/uploads/2014/10/DI-data-revolution-manifesto21.pdf

Wayback Machine: http://web.archive.org/web/20160327233347/http://devinit.org/,

[[Categoría:Manifiestos]]
[[Categoría:Development Initiatives]]
[[Categoría:Inglés]]
[[Categoría:Reino Unido]]
[[Categoría:Kenia]]
[[Categoría:2014]]

2014 - The Data Manifesto - Development Initiatives

2016-04-06T23:55:20Z

Nevi:

=== Staging a Data Revolution ===

Accessible, useable, timely and complete data is core to sustainable development and social progress. Access to information provides people with a base to make better choices and have more control over their lives. Too often attempts to deliver sustainable economic, social and environmental results are hindered by the failure to get the right information, in the right format, to the right people, at the right time. Worse still, the most acute data deficits often affect the people and countries facing the most acute problems.

The Data Revolution should be about data grounded in real life. Data and information that gets to the people who need it at national and sub-national levels to help with the decisions they face – hospital directors, school managers, city councillors, parliamentarians. Data that goes beyond averages – that is disaggregated to show the different impacts of decisions, policies and investments on gender, social groups and people living in different places and over time.

We need a Data Revolution that sets a new political agenda, that puts existing data to work, that improves the way data is gathered and ensures that information can be used. To deliver this vision, we need the following steps.

=== 12 steps to a Data Revolution ===

Implement a national ‘Data Pledge’ to citizens that is supported by governments, private and non-governmental sectors
Address real world questions with joined up and disaggregated data
Empower and up-skill data users of the future through education
Examine existing frameworks and publish existing data
Build an information bank of data assets
Allocate funding available for better data according to national and sub-national priorities
Strengthen national statistical systems’ capacity to collect data
Implement a policy that data is ‘open by default’
Improve data quality by subjecting it to public scrutiny
Put information users’ needs first
Recognise technology cannot solve all barriers to information
Invest in infomediaries’ capacity to translate data into information that policymakers, civil society and the media can actually use

'''It is time for data to become a central building block for better choices.
It is time to put the power of information to work.
'''

=== Setting a new agenda ===

A revolution in the production, access to and use of data demands a new agenda. Without clear political leadership and public commitments to a shared approach, the step-change in capacity for better data at every level will not be delivered. Three core political actions are necessary for the Data Revolution to release the power of information:

===== 1. Implement a national ‘Data Pledge’ to citizens that is supported by governments, private and non-governmental sectors =====

Commitments to better data must primarily be between a government and its people. All governments should make a public ‘Data Pledge’. Private and non-governmental sectors should follow suit and pledge to support national governments to fulfil the ‘Data Pledge’.

The national '''‘Data Pledge’''' should:

Publicly acknowledge the Data Revolution and the imperative to improve public data for decision-making, accountability and improved service delivery.
Commit to putting all existing data to work by publishing all data currently in government systems.
Produce a data investment plan to finance the systems and structures needed to achieve better data through to 2030.
Adopt a comprehensive and consistent policy for opening up all government data quickly.
Ensure the data does not become an extractive industry – extracting information from local populations – but protects the public’s right to information about their own society by publishing data in a way that is accessible not just to the few but to all.
Introduce regular consultations with civil society organisations (CSO), local governments and businesses to inform the release of data that meets their needs and enables better participation in local governing processes and decisions.
===== 2. Address real world questions with joined up and disaggregated data =====

Very few datasets tell a story in isolation. Answers to real world questions often need data from different sources to be joined up and disaggregated so that the impacts on different people and locations can be traced. Data can only be joined up if it can be compared – using common definitions and standards. We need urgent political will to establish basic pillars for the publication of data for all data publishers to adhere to. To get beyond the averages we need a major effort to gather disaggregated data on both the income and wellbeing (in health, education, water and sanitation) of the poorest 20% of people, ensuring no one is left behind.

===== 3. Empower and upskill data users of the future through education =====

It is not enough to put the data out there: the data needs to be accessible and useable by all sections of society to overcome of the current lack of trust in data: otherwise the Data Revolution risks merely reinforcing the existing power dynamic. We need a widespread education programme that informs people of their access to information rights and empowers them with knowledge and skills to act on those rights.

Putting existing data to work

Lots of data exists already. Across the world, data availability and quality has improved dramatically during the past two decades. Aggregated development, social and health indicators have been in the public domain for many years. Yet much of the data in most national statistics systems is still private, leaving its economic and social potential untapped.

4. Examine existing frameworks and publish existing data

The Data Revolution should put to use the large amounts of data that already exist in national statistics and other information systems. Public data should be made public. All governments should start by examining the frameworks and publish data that already exists, in as detailed form as possible, with a particular focus on:

Administrative and geographic infrastructures
Budgets and censuses
Health, education and agricultural data from national management information systems
All anonymised microdata collected through publicly funded initiatives (such as household surveys)
Panel data measuring what has happened to the same people over time
5. Build an information bank of data assets

The private sector has expertise in gathering and using data on its customers, supply chains and the provenance of goods and services. Mobile technologies, internet and social media all create opportunities for gathering and communicating data – including from people and places that are currently least well served with data. To put these existing data assets to work, they need to be visible. Governments need to provide incentives for open publication of all data from private and public sources. National audits of data assets should be developed, bringing together data that is often held in sectoral silos. The private sector should work in partnership with governments to show how the data they own, such as mobile phone data, could be provided as a public good to complement and improve public data.

Gathering better data

6. Allocate funding available for better data according to national and sub-national priorities

There are limited resources to improve data and decision makers have different and sometimes conflicting needs. How the limited resources available to improve data are allocated should therefore be determined by national and sub-national priorities of where greatest impact on poverty can be felt. Allocations should not be driven by international commitments or donor requirements.

7. Strengthen national statistical systems’ capacity to collect data

The challenges for national statistics systems and solutions are now well documented and must be addressed. They should be tackled through actions such as:[1]

Enhance the functional autonomy by recognising the national statistical system as an independent function and ensure national statistics offices receive greater independence from political influence.
Reduce donor dependency and fund national statistics offices more from national budgets, based on the business case for investing in better data.
Experiment with new institutional models such as public–private partnerships and crowd-sourcing to collect hard-to-get data or outsource data collection activities.
Build quality control mechanisms into data collection to improve accuracy.
Improve technical infrastructures for data collection, storage and publishing.
8. Implement a policy that data is ‘open by default’

Where data is available, there are often limitations on how it can be accessed and used. Firstly, data sources are rarely openly licensed, so users are not clear whether they can use and redistribute the data. Secondly, the format is not always machine-readable. Much of the data lives in PDF files or websites. Users need different kinds of information for different purposes, so information needs to be published in a machine-readable format and under open licenses that allow users to access the data and re-purpose it to meet their individual needs.

9. Improve data quality by subjecting it to public scrutiny

Good quality data – data that is accurate, complete and timely – is critical, and data providers should provide mechanisms for data users to feedback and suggest how it can be improved. Too often policy prescriptions fail to alert the reader of the underlying quality of the data. Hence policy makers are not alerted to the poor quality of the data, reducing their incentive to invest in improving it. Data users and policy makers need to adopt a code of practice and always ask, always tell on the provenance and quality of the data.

Ensuring better information

How data is produced and used matters for how beneficial it ultimately is. Despite the potential that ‘more data’ holds, publishing data on its own is not enough. More data does not always mean better information. Data needs combining, contextualising and explaining if it is to be turned into information that elected officials and civil society can act on.

10. Put information users’ needs first

Data analysis and information delivery must be driven by the needs of national and sub-national decision-makers and those who need to hold them accountable. Too often published data meets the needs of producers rather than users of information, for whom it is inaccessible or too complex. The needs of data users and local decision-makers must be put first by asking themthrough regular consultations what information they need, how they need it, and when.

11. Recognise technology cannot solve all barriers to information

Getting the right information, in the right format, to right people, at the right time is challenging. Despite legal frameworks for freedom of information or open data, significant technological, human and bureaucratic challenges must still be overcome. These include unstable power supplies, the lack of functioning websites, very limited numbers of information technology specialists or dedicated information officers working in government, cumbersome procedures to access information, and publication in formats that are difficult to disseminate. Addressing these obstacles requires an understanding of the whole data ecosystem – not just a focus on technological solutions.

12. Invest in infomediaries’ capacity to translate data into information that policymakers, civil society and the media can actually use

Most ‘users’ don’t want to handle raw data; they need it translated into accessible information. Open data does not in itself provide usable information. In short, data is for machines; information is for people. We need investment to develop and support a cadre of data literate infomediaries – including government departments, information communication technology, research and non-governmental organisations, and journalists to translate data into a form that policymakers, civil society and the media can actually use.

[1] Centre for Global Development and African Population and Health Research Center, Delivering on the Data Revolution in Sub-Saharan Africa, July 2014 www.cgdev.org/sites/default/files/delivering-data-revolution-sub-saharan-africa-pdf.pdf

Enlace:http://devinit.org/#!/post/data-manifesto-2, http://devinit.org/wp-content/uploads/2014/10/DI-data-revolution-manifesto21.pdf

Wayback Machine: http://web.archive.org/web/20160327233347/http://devinit.org/,

[[Categoría:Manifiestos]]
[[Categoría:Development Initiatives]]
[[Categoría:Inglés]]
[[Categoría:Reino Unido]]
[[Categoría:Kenia]]
[[Categoría:2014]]

2014 - The Data Manifesto - Development Initiatives

2016-04-06T23:53:44Z

Nevi:

=== Staging a Data Revolution ===

Accessible, useable, timely and complete data is core to sustainable development and social progress. Access to information provides people with a base to make better choices and have more control over their lives. Too often attempts to deliver sustainable economic, social and environmental results are hindered by the failure to get the right information, in the right format, to the right people, at the right time. Worse still, the most acute data deficits often affect the people and countries facing the most acute problems.

The Data Revolution should be about data grounded in real life. Data and information that gets to the people who need it at national and sub-national levels to help with the decisions they face – hospital directors, school managers, city councillors, parliamentarians. Data that goes beyond averages – that is disaggregated to show the different impacts of decisions, policies and investments on gender, social groups and people living in different places and over time.

We need a Data Revolution that sets a new political agenda, that puts existing data to work, that improves the way data is gathered and ensures that information can be used. To deliver this vision, we need the following steps.

=== 12 steps to a Data Revolution ===

Implement a national ‘Data Pledge’ to citizens that is supported by governments, private and non-governmental sectors
Address real world questions with joined up and disaggregated data
Empower and up-skill data users of the future through education
Examine existing frameworks and publish existing data
Build an information bank of data assets
Allocate funding available for better data according to national and sub-national priorities
Strengthen national statistical systems’ capacity to collect data
Implement a policy that data is ‘open by default’
Improve data quality by subjecting it to public scrutiny
Put information users’ needs first
Recognise technology cannot solve all barriers to information
Invest in infomediaries’ capacity to translate data into information that policymakers, civil society and the media can actually use

'''It is time for data to become a central building block for better choices.
It is time to put the power of information to work.
'''

=== Setting a new agenda ===

A revolution in the production, access to and use of data demands a new agenda. Without clear political leadership and public commitments to a shared approach, the step-change in capacity for better data at every level will not be delivered. Three core political actions are necessary for the Data Revolution to release the power of information:

===== 1. Implement a national ‘Data Pledge’ to citizens that is supported by governments, private and non-governmental sectors =====

Commitments to better data must primarily be between a government and its people. All governments should make a public ‘Data Pledge’. Private and non-governmental sectors should follow suit and pledge to support national governments to fulfil the ‘Data Pledge’.

The national '''‘Data Pledge’''' should:

Publicly acknowledge the Data Revolution and the imperative to improve public data for decision-making, accountability and improved service delivery.
Commit to putting all existing data to work by publishing all data currently in government systems.
Produce a data investment plan to finance the systems and structures needed to achieve better data through to 2030.
Adopt a comprehensive and consistent policy for opening up all government data quickly.
Ensure the data does not become an extractive industry – extracting information from local populations – but protects the public’s right to information about their own society by publishing data in a way that is accessible not just to the few but to all.
Introduce regular consultations with civil society organisations (CSO), local governments and businesses to inform the release of data that meets their needs and enables better participation in local governing processes and decisions.
===== 2. Address real world questions with joined up and disaggregated data =====

Very few datasets tell a story in isolation. Answers to real world questions often need data from different sources to be joined up and disaggregated so that the impacts on different people and locations can be traced. Data can only be joined up if it can be compared – using common definitions and standards. We need urgent political will to establish basic pillars for the publication of data for all data publishers to adhere to. To get beyond the averages we need a major effort to gather disaggregated data on both the income and wellbeing (in health, education, water and sanitation) of the poorest 20% of people, ensuring no one is left behind.

===== 3. Empower and upskill data users of the future through education
=====
It is not enough to put the data out there: the data needs to be accessible and useable by all sections of society to overcome of the current lack of trust in data: otherwise the Data Revolution risks merely reinforcing the existing power dynamic. We need a widespread education programme that informs people of their access to information rights and empowers them with knowledge and skills to act on those rights.

Putting existing data to work

Lots of data exists already. Across the world, data availability and quality has improved dramatically during the past two decades. Aggregated development, social and health indicators have been in the public domain for many years. Yet much of the data in most national statistics systems is still private, leaving its economic and social potential untapped.

4. Examine existing frameworks and publish existing data

The Data Revolution should put to use the large amounts of data that already exist in national statistics and other information systems. Public data should be made public. All governments should start by examining the frameworks and publish data that already exists, in as detailed form as possible, with a particular focus on:

Administrative and geographic infrastructures
Budgets and censuses
Health, education and agricultural data from national management information systems
All anonymised microdata collected through publicly funded initiatives (such as household surveys)
Panel data measuring what has happened to the same people over time
5. Build an information bank of data assets

The private sector has expertise in gathering and using data on its customers, supply chains and the provenance of goods and services. Mobile technologies, internet and social media all create opportunities for gathering and communicating data – including from people and places that are currently least well served with data. To put these existing data assets to work, they need to be visible. Governments need to provide incentives for open publication of all data from private and public sources. National audits of data assets should be developed, bringing together data that is often held in sectoral silos. The private sector should work in partnership with governments to show how the data they own, such as mobile phone data, could be provided as a public good to complement and improve public data.

Gathering better data

6. Allocate funding available for better data according to national and sub-national priorities

There are limited resources to improve data and decision makers have different and sometimes conflicting needs. How the limited resources available to improve data are allocated should therefore be determined by national and sub-national priorities of where greatest impact on poverty can be felt. Allocations should not be driven by international commitments or donor requirements.

7. Strengthen national statistical systems’ capacity to collect data

The challenges for national statistics systems and solutions are now well documented and must be addressed. They should be tackled through actions such as:[1]

Enhance the functional autonomy by recognising the national statistical system as an independent function and ensure national statistics offices receive greater independence from political influence.
Reduce donor dependency and fund national statistics offices more from national budgets, based on the business case for investing in better data.
Experiment with new institutional models such as public–private partnerships and crowd-sourcing to collect hard-to-get data or outsource data collection activities.
Build quality control mechanisms into data collection to improve accuracy.
Improve technical infrastructures for data collection, storage and publishing.
8. Implement a policy that data is ‘open by default’

Where data is available, there are often limitations on how it can be accessed and used. Firstly, data sources are rarely openly licensed, so users are not clear whether they can use and redistribute the data. Secondly, the format is not always machine-readable. Much of the data lives in PDF files or websites. Users need different kinds of information for different purposes, so information needs to be published in a machine-readable format and under open licenses that allow users to access the data and re-purpose it to meet their individual needs.

9. Improve data quality by subjecting it to public scrutiny

Good quality data – data that is accurate, complete and timely – is critical, and data providers should provide mechanisms for data users to feedback and suggest how it can be improved. Too often policy prescriptions fail to alert the reader of the underlying quality of the data. Hence policy makers are not alerted to the poor quality of the data, reducing their incentive to invest in improving it. Data users and policy makers need to adopt a code of practice and always ask, always tell on the provenance and quality of the data.

Ensuring better information

How data is produced and used matters for how beneficial it ultimately is. Despite the potential that ‘more data’ holds, publishing data on its own is not enough. More data does not always mean better information. Data needs combining, contextualising and explaining if it is to be turned into information that elected officials and civil society can act on.

10. Put information users’ needs first

Data analysis and information delivery must be driven by the needs of national and sub-national decision-makers and those who need to hold them accountable. Too often published data meets the needs of producers rather than users of information, for whom it is inaccessible or too complex. The needs of data users and local decision-makers must be put first by asking themthrough regular consultations what information they need, how they need it, and when.

11. Recognise technology cannot solve all barriers to information

Getting the right information, in the right format, to right people, at the right time is challenging. Despite legal frameworks for freedom of information or open data, significant technological, human and bureaucratic challenges must still be overcome. These include unstable power supplies, the lack of functioning websites, very limited numbers of information technology specialists or dedicated information officers working in government, cumbersome procedures to access information, and publication in formats that are difficult to disseminate. Addressing these obstacles requires an understanding of the whole data ecosystem – not just a focus on technological solutions.

12. Invest in infomediaries’ capacity to translate data into information that policymakers, civil society and the media can actually use

Most ‘users’ don’t want to handle raw data; they need it translated into accessible information. Open data does not in itself provide usable information. In short, data is for machines; information is for people. We need investment to develop and support a cadre of data literate infomediaries – including government departments, information communication technology, research and non-governmental organisations, and journalists to translate data into a form that policymakers, civil society and the media can actually use.

[1] Centre for Global Development and African Population and Health Research Center, Delivering on the Data Revolution in Sub-Saharan Africa, July 2014 www.cgdev.org/sites/default/files/delivering-data-revolution-sub-saharan-africa-pdf.pdf

Enlace:http://devinit.org/#!/post/data-manifesto-2, http://devinit.org/wp-content/uploads/2014/10/DI-data-revolution-manifesto21.pdf

Wayback Machine: http://web.archive.org/web/20160327233347/http://devinit.org/,

[[Categoría:Manifiestos]]
[[Categoría:Development Initiatives]]
[[Categoría:Inglés]]
[[Categoría:Reino Unido]]
[[Categoría:Kenia]]
[[Categoría:2014]]

2014 - The Data Manifesto - Development Initiatives

2016-04-06T23:51:53Z

Nevi:

=== Staging a Data Revolution ===

Accessible, useable, timely and complete data is core to sustainable development and social progress. Access to information provides people with a base to make better choices and have more control over their lives. Too often attempts to deliver sustainable economic, social and environmental results are hindered by the failure to get the right information, in the right format, to the right people, at the right time. Worse still, the most acute data deficits often affect the people and countries facing the most acute problems.

The Data Revolution should be about data grounded in real life. Data and information that gets to the people who need it at national and sub-national levels to help with the decisions they face – hospital directors, school managers, city councillors, parliamentarians. Data that goes beyond averages – that is disaggregated to show the different impacts of decisions, policies and investments on gender, social groups and people living in different places and over time.

We need a Data Revolution that sets a new political agenda, that puts existing data to work, that improves the way data is gathered and ensures that information can be used. To deliver this vision, we need the following steps.

=== 12 steps to a Data Revolution ===

Implement a national ‘Data Pledge’ to citizens that is supported by governments, private and non-governmental sectors
Address real world questions with joined up and disaggregated data
Empower and up-skill data users of the future through education
Examine existing frameworks and publish existing data
Build an information bank of data assets
Allocate funding available for better data according to national and sub-national priorities
Strengthen national statistical systems’ capacity to collect data
Implement a policy that data is ‘open by default’
Improve data quality by subjecting it to public scrutiny
Put information users’ needs first
Recognise technology cannot solve all barriers to information
Invest in infomediaries’ capacity to translate data into information that policymakers, civil society and the media can actually use
It is time for data to become a central building block for better choices.
It is time to put the power of information to work.

=== Setting a new agenda ===

A revolution in the production, access to and use of data demands a new agenda. Without clear political leadership and public commitments to a shared approach, the step-change in capacity for better data at every level will not be delivered. Three core political actions are necessary for the Data Revolution to release the power of information:

'''1. Implement a national ‘Data Pledge’ to citizens that is supported by governments, private and non-governmental sectors
'''
Commitments to better data must primarily be between a government and its people. All governments should make a public ‘Data Pledge’. Private and non-governmental sectors should follow suit and pledge to support national governments to fulfil the ‘Data Pledge’.

The national ‘Data Pledge’ should:

Publicly acknowledge the Data Revolution and the imperative to improve public data for decision-making, accountability and improved service delivery.
Commit to putting all existing data to work by publishing all data currently in government systems.
Produce a data investment plan to finance the systems and structures needed to achieve better data through to 2030.
Adopt a comprehensive and consistent policy for opening up all government data quickly.
Ensure the data does not become an extractive industry – extracting information from local populations – but protects the public’s right to information about their own society by publishing data in a way that is accessible not just to the few but to all.
Introduce regular consultations with civil society organisations (CSO), local governments and businesses to inform the release of data that meets their needs and enables better participation in local governing processes and decisions.
2. Address real world questions with joined up and disaggregated data

Very few datasets tell a story in isolation. Answers to real world questions often need data from different sources to be joined up and disaggregated so that the impacts on different people and locations can be traced. Data can only be joined up if it can be compared – using common definitions and standards. We need urgent political will to establish basic pillars for the publication of data for all data publishers to adhere to. To get beyond the averages we need a major effort to gather disaggregated data on both the income and wellbeing (in health, education, water and sanitation) of the poorest 20% of people, ensuring no one is left behind.

3. Empower and upskill data users of the future through education

It is not enough to put the data out there: the data needs to be accessible and useable by all sections of society to overcome of the current lack of trust in data: otherwise the Data Revolution risks merely reinforcing the existing power dynamic. We need a widespread education programme that informs people of their access to information rights and empowers them with knowledge and skills to act on those rights.

Putting existing data to work

Lots of data exists already. Across the world, data availability and quality has improved dramatically during the past two decades. Aggregated development, social and health indicators have been in the public domain for many years. Yet much of the data in most national statistics systems is still private, leaving its economic and social potential untapped.

4. Examine existing frameworks and publish existing data

The Data Revolution should put to use the large amounts of data that already exist in national statistics and other information systems. Public data should be made public. All governments should start by examining the frameworks and publish data that already exists, in as detailed form as possible, with a particular focus on:

Administrative and geographic infrastructures
Budgets and censuses
Health, education and agricultural data from national management information systems
All anonymised microdata collected through publicly funded initiatives (such as household surveys)
Panel data measuring what has happened to the same people over time
5. Build an information bank of data assets

The private sector has expertise in gathering and using data on its customers, supply chains and the provenance of goods and services. Mobile technologies, internet and social media all create opportunities for gathering and communicating data – including from people and places that are currently least well served with data. To put these existing data assets to work, they need to be visible. Governments need to provide incentives for open publication of all data from private and public sources. National audits of data assets should be developed, bringing together data that is often held in sectoral silos. The private sector should work in partnership with governments to show how the data they own, such as mobile phone data, could be provided as a public good to complement and improve public data.

Gathering better data

6. Allocate funding available for better data according to national and sub-national priorities

There are limited resources to improve data and decision makers have different and sometimes conflicting needs. How the limited resources available to improve data are allocated should therefore be determined by national and sub-national priorities of where greatest impact on poverty can be felt. Allocations should not be driven by international commitments or donor requirements.

7. Strengthen national statistical systems’ capacity to collect data

The challenges for national statistics systems and solutions are now well documented and must be addressed. They should be tackled through actions such as:[1]

Enhance the functional autonomy by recognising the national statistical system as an independent function and ensure national statistics offices receive greater independence from political influence.
Reduce donor dependency and fund national statistics offices more from national budgets, based on the business case for investing in better data.
Experiment with new institutional models such as public–private partnerships and crowd-sourcing to collect hard-to-get data or outsource data collection activities.
Build quality control mechanisms into data collection to improve accuracy.
Improve technical infrastructures for data collection, storage and publishing.
8. Implement a policy that data is ‘open by default’

Where data is available, there are often limitations on how it can be accessed and used. Firstly, data sources are rarely openly licensed, so users are not clear whether they can use and redistribute the data. Secondly, the format is not always machine-readable. Much of the data lives in PDF files or websites. Users need different kinds of information for different purposes, so information needs to be published in a machine-readable format and under open licenses that allow users to access the data and re-purpose it to meet their individual needs.

9. Improve data quality by subjecting it to public scrutiny

Good quality data – data that is accurate, complete and timely – is critical, and data providers should provide mechanisms for data users to feedback and suggest how it can be improved. Too often policy prescriptions fail to alert the reader of the underlying quality of the data. Hence policy makers are not alerted to the poor quality of the data, reducing their incentive to invest in improving it. Data users and policy makers need to adopt a code of practice and always ask, always tell on the provenance and quality of the data.

Ensuring better information

How data is produced and used matters for how beneficial it ultimately is. Despite the potential that ‘more data’ holds, publishing data on its own is not enough. More data does not always mean better information. Data needs combining, contextualising and explaining if it is to be turned into information that elected officials and civil society can act on.

10. Put information users’ needs first

Data analysis and information delivery must be driven by the needs of national and sub-national decision-makers and those who need to hold them accountable. Too often published data meets the needs of producers rather than users of information, for whom it is inaccessible or too complex. The needs of data users and local decision-makers must be put first by asking themthrough regular consultations what information they need, how they need it, and when.

11. Recognise technology cannot solve all barriers to information

Getting the right information, in the right format, to right people, at the right time is challenging. Despite legal frameworks for freedom of information or open data, significant technological, human and bureaucratic challenges must still be overcome. These include unstable power supplies, the lack of functioning websites, very limited numbers of information technology specialists or dedicated information officers working in government, cumbersome procedures to access information, and publication in formats that are difficult to disseminate. Addressing these obstacles requires an understanding of the whole data ecosystem – not just a focus on technological solutions.

12. Invest in infomediaries’ capacity to translate data into information that policymakers, civil society and the media can actually use

Most ‘users’ don’t want to handle raw data; they need it translated into accessible information. Open data does not in itself provide usable information. In short, data is for machines; information is for people. We need investment to develop and support a cadre of data literate infomediaries – including government departments, information communication technology, research and non-governmental organisations, and journalists to translate data into a form that policymakers, civil society and the media can actually use.

[1] Centre for Global Development and African Population and Health Research Center, Delivering on the Data Revolution in Sub-Saharan Africa, July 2014 www.cgdev.org/sites/default/files/delivering-data-revolution-sub-saharan-africa-pdf.pdf

Enlace:http://devinit.org/#!/post/data-manifesto-2, http://devinit.org/wp-content/uploads/2014/10/DI-data-revolution-manifesto21.pdf

Wayback Machine: http://web.archive.org/web/20160327233347/http://devinit.org/,

[[Categoría:Manifiestos]]
[[Categoría:Development Initiatives]]
[[Categoría:Inglés]]
[[Categoría:Reino Unido]]
[[Categoría:Kenia]]
[[Categoría:2014]]

2014 - The Data Manifesto - Development Initiatives

2016-04-06T23:48:45Z

Nevi:

'''Staging a Data Revolution
'''
Accessible, useable, timely and complete data is core to sustainable development and social progress. Access to information provides people with a base to make better choices and have more control over their lives. Too often attempts to deliver sustainable economic, social and environmental results are hindered by the failure to get the right information, in the right format, to the right people, at the right time. Worse still, the most acute data deficits often affect the people and countries facing the most acute problems.

The Data Revolution should be about data grounded in real life. Data and information that gets to the people who need it at national and sub-national levels to help with the decisions they face – hospital directors, school managers, city councillors, parliamentarians. Data that goes beyond averages – that is disaggregated to show the different impacts of decisions, policies and investments on gender, social groups and people living in different places and over time.

We need a Data Revolution that sets a new political agenda, that puts existing data to work, that improves the way data is gathered and ensures that information can be used. To deliver this vision, we need the following steps.

'''12 steps to a Data Revolution'''

Implement a national ‘Data Pledge’ to citizens that is supported by governments, private and non-governmental sectors
Address real world questions with joined up and disaggregated data
Empower and up-skill data users of the future through education
Examine existing frameworks and publish existing data
Build an information bank of data assets
Allocate funding available for better data according to national and sub-national priorities
Strengthen national statistical systems’ capacity to collect data
Implement a policy that data is ‘open by default’
Improve data quality by subjecting it to public scrutiny
Put information users’ needs first
Recognise technology cannot solve all barriers to information
Invest in infomediaries’ capacity to translate data into information that policymakers, civil society and the media can actually use
It is time for data to become a central building block for better choices.
It is time to put the power of information to work.

S'''etting a new agenda'''

A revolution in the production, access to and use of data demands a new agenda. Without clear political leadership and public commitments to a shared approach, the step-change in capacity for better data at every level will not be delivered. Three core political actions are necessary for the Data Revolution to release the power of information:

'''1. Implement a national ‘Data Pledge’ to citizens that is supported by governments, private and non-governmental sectors
'''
Commitments to better data must primarily be between a government and its people. All governments should make a public ‘Data Pledge’. Private and non-governmental sectors should follow suit and pledge to support national governments to fulfil the ‘Data Pledge’.

The national ‘Data Pledge’ should:

Publicly acknowledge the Data Revolution and the imperative to improve public data for decision-making, accountability and improved service delivery.
Commit to putting all existing data to work by publishing all data currently in government systems.
Produce a data investment plan to finance the systems and structures needed to achieve better data through to 2030.
Adopt a comprehensive and consistent policy for opening up all government data quickly.
Ensure the data does not become an extractive industry – extracting information from local populations – but protects the public’s right to information about their own society by publishing data in a way that is accessible not just to the few but to all.
Introduce regular consultations with civil society organisations (CSO), local governments and businesses to inform the release of data that meets their needs and enables better participation in local governing processes and decisions.
2. Address real world questions with joined up and disaggregated data

Very few datasets tell a story in isolation. Answers to real world questions often need data from different sources to be joined up and disaggregated so that the impacts on different people and locations can be traced. Data can only be joined up if it can be compared – using common definitions and standards. We need urgent political will to establish basic pillars for the publication of data for all data publishers to adhere to. To get beyond the averages we need a major effort to gather disaggregated data on both the income and wellbeing (in health, education, water and sanitation) of the poorest 20% of people, ensuring no one is left behind.

3. Empower and upskill data users of the future through education

It is not enough to put the data out there: the data needs to be accessible and useable by all sections of society to overcome of the current lack of trust in data: otherwise the Data Revolution risks merely reinforcing the existing power dynamic. We need a widespread education programme that informs people of their access to information rights and empowers them with knowledge and skills to act on those rights.

Putting existing data to work

Lots of data exists already. Across the world, data availability and quality has improved dramatically during the past two decades. Aggregated development, social and health indicators have been in the public domain for many years. Yet much of the data in most national statistics systems is still private, leaving its economic and social potential untapped.

4. Examine existing frameworks and publish existing data

The Data Revolution should put to use the large amounts of data that already exist in national statistics and other information systems. Public data should be made public. All governments should start by examining the frameworks and publish data that already exists, in as detailed form as possible, with a particular focus on:

Administrative and geographic infrastructures
Budgets and censuses
Health, education and agricultural data from national management information systems
All anonymised microdata collected through publicly funded initiatives (such as household surveys)
Panel data measuring what has happened to the same people over time
5. Build an information bank of data assets

The private sector has expertise in gathering and using data on its customers, supply chains and the provenance of goods and services. Mobile technologies, internet and social media all create opportunities for gathering and communicating data – including from people and places that are currently least well served with data. To put these existing data assets to work, they need to be visible. Governments need to provide incentives for open publication of all data from private and public sources. National audits of data assets should be developed, bringing together data that is often held in sectoral silos. The private sector should work in partnership with governments to show how the data they own, such as mobile phone data, could be provided as a public good to complement and improve public data.

Gathering better data

6. Allocate funding available for better data according to national and sub-national priorities

There are limited resources to improve data and decision makers have different and sometimes conflicting needs. How the limited resources available to improve data are allocated should therefore be determined by national and sub-national priorities of where greatest impact on poverty can be felt. Allocations should not be driven by international commitments or donor requirements.

7. Strengthen national statistical systems’ capacity to collect data

The challenges for national statistics systems and solutions are now well documented and must be addressed. They should be tackled through actions such as:[1]

Enhance the functional autonomy by recognising the national statistical system as an independent function and ensure national statistics offices receive greater independence from political influence.
Reduce donor dependency and fund national statistics offices more from national budgets, based on the business case for investing in better data.
Experiment with new institutional models such as public–private partnerships and crowd-sourcing to collect hard-to-get data or outsource data collection activities.
Build quality control mechanisms into data collection to improve accuracy.
Improve technical infrastructures for data collection, storage and publishing.
8. Implement a policy that data is ‘open by default’

Where data is available, there are often limitations on how it can be accessed and used. Firstly, data sources are rarely openly licensed, so users are not clear whether they can use and redistribute the data. Secondly, the format is not always machine-readable. Much of the data lives in PDF files or websites. Users need different kinds of information for different purposes, so information needs to be published in a machine-readable format and under open licenses that allow users to access the data and re-purpose it to meet their individual needs.

9. Improve data quality by subjecting it to public scrutiny

Good quality data – data that is accurate, complete and timely – is critical, and data providers should provide mechanisms for data users to feedback and suggest how it can be improved. Too often policy prescriptions fail to alert the reader of the underlying quality of the data. Hence policy makers are not alerted to the poor quality of the data, reducing their incentive to invest in improving it. Data users and policy makers need to adopt a code of practice and always ask, always tell on the provenance and quality of the data.

Ensuring better information

How data is produced and used matters for how beneficial it ultimately is. Despite the potential that ‘more data’ holds, publishing data on its own is not enough. More data does not always mean better information. Data needs combining, contextualising and explaining if it is to be turned into information that elected officials and civil society can act on.

10. Put information users’ needs first

Data analysis and information delivery must be driven by the needs of national and sub-national decision-makers and those who need to hold them accountable. Too often published data meets the needs of producers rather than users of information, for whom it is inaccessible or too complex. The needs of data users and local decision-makers must be put first by asking themthrough regular consultations what information they need, how they need it, and when.

11. Recognise technology cannot solve all barriers to information

Getting the right information, in the right format, to right people, at the right time is challenging. Despite legal frameworks for freedom of information or open data, significant technological, human and bureaucratic challenges must still be overcome. These include unstable power supplies, the lack of functioning websites, very limited numbers of information technology specialists or dedicated information officers working in government, cumbersome procedures to access information, and publication in formats that are difficult to disseminate. Addressing these obstacles requires an understanding of the whole data ecosystem – not just a focus on technological solutions.

12. Invest in infomediaries’ capacity to translate data into information that policymakers, civil society and the media can actually use

Most ‘users’ don’t want to handle raw data; they need it translated into accessible information. Open data does not in itself provide usable information. In short, data is for machines; information is for people. We need investment to develop and support a cadre of data literate infomediaries – including government departments, information communication technology, research and non-governmental organisations, and journalists to translate data into a form that policymakers, civil society and the media can actually use.

[1] Centre for Global Development and African Population and Health Research Center, Delivering on the Data Revolution in Sub-Saharan Africa, July 2014 www.cgdev.org/sites/default/files/delivering-data-revolution-sub-saharan-africa-pdf.pdf

Enlace:http://devinit.org/#!/post/data-manifesto-2, http://devinit.org/wp-content/uploads/2014/10/DI-data-revolution-manifesto21.pdf

Wayback Machine: http://web.archive.org/web/20160327233347/http://devinit.org/,

[[Categoría:Manifiestos]]
[[Categoría:Development Initiatives]]
[[Categoría:Inglés]]
[[Categoría:Reino Unido]]
[[Categoría:Kenia]]
[[Categoría:2014]]

2014 - The Data Manifesto - Development Initiatives

2016-04-06T23:47:40Z

Nevi:

Staging a Data Revolution

Accessible, useable, timely and complete data is core to sustainable development and social progress. Access to information provides people with a base to make better choices and have more control over their lives. Too often attempts to deliver sustainable economic, social and environmental results are hindered by the failure to get the right information, in the right format, to the right people, at the right time. Worse still, the most acute data deficits often affect the people and countries facing the most acute problems.

The Data Revolution should be about data grounded in real life. Data and information that gets to the people who need it at national and sub-national levels to help with the decisions they face – hospital directors, school managers, city councillors, parliamentarians. Data that goes beyond averages – that is disaggregated to show the different impacts of decisions, policies and investments on gender, social groups and people living in different places and over time.

We need a Data Revolution that sets a new political agenda, that puts existing data to work, that improves the way data is gathered and ensures that information can be used. To deliver this vision, we need the following steps.

12 steps to a Data Revolution

Implement a national ‘Data Pledge’ to citizens that is supported by governments, private and non-governmental sectors
Address real world questions with joined up and disaggregated data
Empower and up-skill data users of the future through education
Examine existing frameworks and publish existing data
Build an information bank of data assets
Allocate funding available for better data according to national and sub-national priorities
Strengthen national statistical systems’ capacity to collect data
Implement a policy that data is ‘open by default’
Improve data quality by subjecting it to public scrutiny
Put information users’ needs first
Recognise technology cannot solve all barriers to information
Invest in infomediaries’ capacity to translate data into information that policymakers, civil society and the media can actually use
It is time for data to become a central building block for better choices.
It is time to put the power of information to work.

Setting a new agenda

A revolution in the production, access to and use of data demands a new agenda. Without clear political leadership and public commitments to a shared approach, the step-change in capacity for better data at every level will not be delivered. Three core political actions are necessary for the Data Revolution to release the power of information:

1. Implement a national ‘Data Pledge’ to citizens that is supported by governments, private and non-governmental sectors

Commitments to better data must primarily be between a government and its people. All governments should make a public ‘Data Pledge’. Private and non-governmental sectors should follow suit and pledge to support national governments to fulfil the ‘Data Pledge’.

The national ‘Data Pledge’ should:

Publicly acknowledge the Data Revolution and the imperative to improve public data for decision-making, accountability and improved service delivery.
Commit to putting all existing data to work by publishing all data currently in government systems.
Produce a data investment plan to finance the systems and structures needed to achieve better data through to 2030.
Adopt a comprehensive and consistent policy for opening up all government data quickly.
Ensure the data does not become an extractive industry – extracting information from local populations – but protects the public’s right to information about their own society by publishing data in a way that is accessible not just to the few but to all.
Introduce regular consultations with civil society organisations (CSO), local governments and businesses to inform the release of data that meets their needs and enables better participation in local governing processes and decisions.
2. Address real world questions with joined up and disaggregated data

Very few datasets tell a story in isolation. Answers to real world questions often need data from different sources to be joined up and disaggregated so that the impacts on different people and locations can be traced. Data can only be joined up if it can be compared – using common definitions and standards. We need urgent political will to establish basic pillars for the publication of data for all data publishers to adhere to. To get beyond the averages we need a major effort to gather disaggregated data on both the income and wellbeing (in health, education, water and sanitation) of the poorest 20% of people, ensuring no one is left behind.

3. Empower and upskill data users of the future through education

It is not enough to put the data out there: the data needs to be accessible and useable by all sections of society to overcome of the current lack of trust in data: otherwise the Data Revolution risks merely reinforcing the existing power dynamic. We need a widespread education programme that informs people of their access to information rights and empowers them with knowledge and skills to act on those rights.

Putting existing data to work

Lots of data exists already. Across the world, data availability and quality has improved dramatically during the past two decades. Aggregated development, social and health indicators have been in the public domain for many years. Yet much of the data in most national statistics systems is still private, leaving its economic and social potential untapped.

4. Examine existing frameworks and publish existing data

The Data Revolution should put to use the large amounts of data that already exist in national statistics and other information systems. Public data should be made public. All governments should start by examining the frameworks and publish data that already exists, in as detailed form as possible, with a particular focus on:

Administrative and geographic infrastructures
Budgets and censuses
Health, education and agricultural data from national management information systems
All anonymised microdata collected through publicly funded initiatives (such as household surveys)
Panel data measuring what has happened to the same people over time
5. Build an information bank of data assets

The private sector has expertise in gathering and using data on its customers, supply chains and the provenance of goods and services. Mobile technologies, internet and social media all create opportunities for gathering and communicating data – including from people and places that are currently least well served with data. To put these existing data assets to work, they need to be visible. Governments need to provide incentives for open publication of all data from private and public sources. National audits of data assets should be developed, bringing together data that is often held in sectoral silos. The private sector should work in partnership with governments to show how the data they own, such as mobile phone data, could be provided as a public good to complement and improve public data.

Gathering better data

6. Allocate funding available for better data according to national and sub-national priorities

There are limited resources to improve data and decision makers have different and sometimes conflicting needs. How the limited resources available to improve data are allocated should therefore be determined by national and sub-national priorities of where greatest impact on poverty can be felt. Allocations should not be driven by international commitments or donor requirements.

7. Strengthen national statistical systems’ capacity to collect data

The challenges for national statistics systems and solutions are now well documented and must be addressed. They should be tackled through actions such as:[1]

Enhance the functional autonomy by recognising the national statistical system as an independent function and ensure national statistics offices receive greater independence from political influence.
Reduce donor dependency and fund national statistics offices more from national budgets, based on the business case for investing in better data.
Experiment with new institutional models such as public–private partnerships and crowd-sourcing to collect hard-to-get data or outsource data collection activities.
Build quality control mechanisms into data collection to improve accuracy.
Improve technical infrastructures for data collection, storage and publishing.
8. Implement a policy that data is ‘open by default’

Where data is available, there are often limitations on how it can be accessed and used. Firstly, data sources are rarely openly licensed, so users are not clear whether they can use and redistribute the data. Secondly, the format is not always machine-readable. Much of the data lives in PDF files or websites. Users need different kinds of information for different purposes, so information needs to be published in a machine-readable format and under open licenses that allow users to access the data and re-purpose it to meet their individual needs.

9. Improve data quality by subjecting it to public scrutiny

Good quality data – data that is accurate, complete and timely – is critical, and data providers should provide mechanisms for data users to feedback and suggest how it can be improved. Too often policy prescriptions fail to alert the reader of the underlying quality of the data. Hence policy makers are not alerted to the poor quality of the data, reducing their incentive to invest in improving it. Data users and policy makers need to adopt a code of practice and always ask, always tell on the provenance and quality of the data.

Ensuring better information

How data is produced and used matters for how beneficial it ultimately is. Despite the potential that ‘more data’ holds, publishing data on its own is not enough. More data does not always mean better information. Data needs combining, contextualising and explaining if it is to be turned into information that elected officials and civil society can act on.

10. Put information users’ needs first

Data analysis and information delivery must be driven by the needs of national and sub-national decision-makers and those who need to hold them accountable. Too often published data meets the needs of producers rather than users of information, for whom it is inaccessible or too complex. The needs of data users and local decision-makers must be put first by asking themthrough regular consultations what information they need, how they need it, and when.

11. Recognise technology cannot solve all barriers to information

Getting the right information, in the right format, to right people, at the right time is challenging. Despite legal frameworks for freedom of information or open data, significant technological, human and bureaucratic challenges must still be overcome. These include unstable power supplies, the lack of functioning websites, very limited numbers of information technology specialists or dedicated information officers working in government, cumbersome procedures to access information, and publication in formats that are difficult to disseminate. Addressing these obstacles requires an understanding of the whole data ecosystem – not just a focus on technological solutions.

12. Invest in infomediaries’ capacity to translate data into information that policymakers, civil society and the media can actually use

Most ‘users’ don’t want to handle raw data; they need it translated into accessible information. Open data does not in itself provide usable information. In short, data is for machines; information is for people. We need investment to develop and support a cadre of data literate infomediaries – including government departments, information communication technology, research and non-governmental organisations, and journalists to translate data into a form that policymakers, civil society and the media can actually use.

[1] Centre for Global Development and African Population and Health Research Center, Delivering on the Data Revolution in Sub-Saharan Africa, July 2014 www.cgdev.org/sites/default/files/delivering-data-revolution-sub-saharan-africa-pdf.pdf

Enlace:http://devinit.org/#!/post/data-manifesto-2, http://devinit.org/wp-content/uploads/2014/10/DI-data-revolution-manifesto21.pdf

Wayback Machine: http://web.archive.org/web/20160327233347/http://devinit.org/,

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2010 - Manifesto of Speculative Posthumanism - David Roden

2016-04-06T23:45:08Z

Nevi:

Over the last decade the possibility of innovations in areas such as artificial intelligence or biotechnology contributing to the emergence of a ‘posthuman’ life form has become a focal point of public debate and mainstream artistic concern. This multi-disciplinary discourse is premised on developments in the so-called ‘NBIC’ technologies – Nanotechnology, Biotechnology, Information Technology and Cognitive Science. The transhumanist claim that human nature should be improved technologically is likewise predicated on the NBIC suite affording the necessary means for enhancement.

In philosophy, discussion of the posthuman has been dominated by concerns about the ethics of enhancement or by metaphysical issues of embodiment and mind. Transhumanists draw on Enlightenment conceptions of human nature as an improvable ‘work in progress’ in arguing for the moral benefits of enhancement and its political legitimacy. Likewise, ‘bioconservative’ critics of transhumanism employ traditional frameworks such as Christian theology and Aristotelianism to argue that such developments may violate the biological integrity of species or undermine constitutive conditions for the good furnished by an unbiddable nature.

Speculative Posthumanism does not deny the importance of these debates but claims that they are too regional in scope to address the potential for ontological novelty implied by NBIC technologies. If it is possible for our technical activity to ultimately engender radically non-human forms of life we must confront the possibility that our ‘wide’ technological descendants will be so alien as to fall outside the public ethical frameworks employed by the majority of transhumanists and bioconservatives.

Among the intellectuals to have appreciated the ontological stakes are those poststructuralists and ‘critical posthumanists’ who claim that the trajectory of current technoscientific change ‘deconstructs’ the philosophical centrality of the human subject in epistemology and politics – by, for example, levelling differences between human subjects, non-human animals, or cybernetic systems. However, while critical posthumanism has yielded important insights it is hamstrung by a default anti-realism inherited from the dominant traditions in post-Kantian continental philosophy. The deconstruction of subjectivity is an ambivalent philosophical achievement at best; one that cedes ground to potent forms of humanism while failing to address the cosmic likelihood of a posthuman dispensation.

Speculative Posthumanism accordingly rejects the post-Kantian epistemology that deploys the ‘posthuman’ as a fashionable trope to mark intrinsic limits on thought. Its project is ‘speculative’ insofar as it explores ways of conceiving the posthuman independently of its relationship to human cognitive forms or phenomenology. It argues, instead, that the posthuman should be understood as a real, though not-yet actual, condition resulting from the technological modification of humans or their wide technological descendants.

Speculative Posthumanism claims that an augmentation history of this kind is metaphysically and technically possible. It does not imply that the posthuman would improve upon the human state or that there would exist a scale of values by which human and posthuman lives could be compared. If radically posthuman lives were very non-human indeed, we should not assume them to be prospectively evaluable using the ethical frameworks available to us. This does not indicate that the posthuman is ‘impossible’ or, like the God of negative theology, transcends our epistemic capacities. Rather this proposition indicates a problem that is still ‘ours’ insofar as the posthuman could result from an iteration of our current technical praxis.

Enlace: http://enemyindustry.net/blog/?p=422

Wayback Machine: http://web.archive.org/web/20160327235833/http://enemyindustry.net/blog/?p=422

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