Open Data

You are currently browsing articles tagged Open Data.

Article written by: Amanda Hunter & Tracey P. Lauriault

The Organisation for Economic Co-operation and Development (OECD) recently published a policy response to COVID-19 in which they suggest that open science, and the policies & standards that support it, can accelerate the health, social, and economic responses to the virus as barriers to information access are eliminated.

As the first in a series of blog posts about Open Science (OS) and FAIR principles in Canada, here we highlight the key role open science plays in communicating and disseminating official COVID-19 research and public health data before assessing if official COVID-19 reporting in Canada adheres to OS principles.

In a next post, we will analyze official COVID-19 reporting in Canada to assess whether or not these follow Open Science, FAIR principles, and the Open Data Charter in the sharing of COVID-19 data.

What is Open Science?

The OECD Open Science program states that the benefits of open science is that it promotes a more accurate verification of scientific results, reduces duplication, increases productivity, and promotes trust in science.

https://www.oecd.org/science/inno/open-science.htm

Open science (OS) is a movement, a practice and a policy toward transparent, accessible, reliable, trusted and reproducible science. This is achieved by sharing how research and data collection are done so as to make research results accessible and standardized, created once and reused by many. This includes techniques, tools, technologies, and platforms should also be open source wherever possible.

In OS the outputs of the scientific process are considered to be a public good, thus wherever possible articles are published in open access (OA) journals, and research data are shared with the public and other scientists who may want to re-purpose those data in new work, or by people who want to verify the veracity of research results. Reporting COVID-19 Cases by normalizing an open by default approaches means that health scientists, population health experts and government officials make this part of their workflow (maintaining individual privacy of course), and by doing so decision makers beyond government, can scrutinize the results, leading to trust the results while also increasing data sharing.

What role does open science play in combating COVID-19?

In the early stages of the pandemic, knowing the genome provided crucial information to help scientists and researchers identify the origin of the outbreak, treat the infection, develop a diagnostic test and work on the vaccine. In other words, the easier—and quicker—researchers can produce, share and access scientific data, the quicker and the more informed is the collaborative response to the virus.

During the 2002-03 SARS outbreak it took five months to publish a full genome of the virus largely due to information blackouts and lack of data sharing. In contrast, the full genome of COVID-19 was published to an open-access platform nearly a month after the first patient was admitted to the hospital in Wuhan. This provided researchers around the world with a head start. Since OS policies have been operationalized during the pandemic, the resulting free flow of ideas in terms of biomedical research has accelerated (OECD).

The implementation of OS standards during COVID-19 has indeed been largely successful. OECD described how collaborative research and  thee global sharing of information reached unprecedented levels, for example:

  • In March 2020, 12 countries (including Canada) launched the Public Health Emergency COVID-19 Initiative at the level of Chief Science advisors, calling for open access to publications and machine-readable access to data related to COVID-19.
  • Open online platform Vivli offers an easy way to request anonymized data from clinical trials.
  • A COVID-19 Open Research Dataset [CORD-19] was developed that hosts 157,000 + scholarly articles about COVID-19 and related coronaviruses; 75,000 of which are full-text machine-readable data that can be used for AI and natural language processing.

These online, open-source platforms have supported rapid scientific COVID-19 research. OS, facilitated by standards, shared infrastructure and techniques, policies and licences, has been instrumental in the global fight against the pandemic.

Yet, despite the numerous successes, many challenges remain. For example, not all COVID-19 related health research and data adhere to the FAIR principles. FAIR principles are a standards approach which support the application of open science by making data Findable, Accessible, Interoperable, and Reusable. Failure to adhere to FAIR principles has led to an overall lack of communication and coordination during the pandemic. In Canada, data should also adhere to CARE principles, which address issues of Indigenous data governance with respect to Indigenous knowledge along with the OCAP Principles of the First Nation Information Governance Centre (FNIGC). More on this in the following section.

The reporting COVID-19 demographic data and reports in Canada to date falls short on standardized classifications in terms of demographics, as we discussed in an earlier blog post, which makes doing a comparative analysis difficult or impossible: for example, many countries define “recoveries” differently, and in Canada, since health is the jurisdictional responsibility of the provinces and territories, each report in their own way. Even though numerous official organizations publish COVID-19 and health related data, as open data databases or in open data portals, there remains an overall lack of interoperability, comparability and standards.

Where does Canada stand on Open Science?

Canada was implementing an open science framework before the pandemic as follows.

National Action Plan on Open Government

The Government of Canada recently published Canada’s 2018-2020 National Action Plan on Open Government, listing ten commitments to furthering the open government initiative. The plan asserts five commitments to implementing OS in Canada by the end of 2020, as seen below:

A screenshot showing a portion of Canada's 2018-2020 National Action Plan on  Open Government. The main issue addressed here is the difficulty for Canadians to access scientific research outputs: thus the commitments focus on making federal science, scientific data, and scientists themselves more accessible.

The OS portion of Canada’s 2018-2020 National Action Plan on Open Government. It aims to address the difficulty for Canadians to access scientific research: thus the commitments on making federal science, scientific data, and scientists themselves more accessible (Government of Canada, 2018).

The Action Plan addresses issues of accessibility and transparency of scientific research and outlines 5 commitments to amending these issues. These commitments include:

  1. Development of an OS roadmap,
  2. Providing an open access platform for publications,
  3. Raising awareness of federal scientists’ work,
  4. Promoting OS and soliciting feedback on stakeholder needs, and
  5. Measuring progress & benefits of the OS implementation.

Despite the comprehensiveness of the Roadmap (see below), Canada has not yet moved past the Action Plan’s second commitment—to provide a platform for Canadians to find and access open access (OA) publications from federal scientists—despite the projected March 2020 deadline. Also, at the time of writing, there is no federal open science platform or portal for users to access open science data in Canada even though there is an open data portal. The New Digital Research Infrastructure Organization (NDRIO) does show promise.

There are however some open data initiatives, such as the Federal Open Government and COVID-19 section on the Open Government Canada Portal.  Here Epidemiological and economic research data, with mathematical modeling reports, a map of cases and deaths by province, daily and weekly detailed epidemiological reports, and an ongoing dataset of COVID-19 cases, deaths, recoveries, and testing rates in Canada’s provinces and territories are made available. This is a significant improvement from the early days of reporting, as data journalist Kenyon Wallace discovered that on a daily basis, the Province of Ontario published new data but each time they did they overrode the previous day’s reports. His article and some work by Lauriault with the Ontario Open Government team resulted in changing that practice and raw data are now updated daily and reported. Open data is but one part of the OS process as we will see when we look at the FAIR principles.

Open Science Roadmap

The plan’s first commitment, to “develop a Canada Open Science Roadmap…” was completed and published in February 2020. The document provides ten recommendations made by Chief Science Advisor, Dr. Mona Nemer, to advance Canada’s OS initiatives. Like the policy brief by OECD, the roadmap is driven by the importance of trust among collaborators, inclusiveness of varying perspectives, and transparent processes throughout.

A screenshot of the cover of Canada’s Roadmap for Open Science (Government of Canada, 2020)

Canada’s Roadmap for Open Science (Government of Canada, 2020)

Most importantly, the Roadmap describes a commitment to developing an OS framework, including adopting the FAIR principles and “open by design and by default” specifications. The roadmap asserts Canada’s commitment to upholding these standards and policies via 10 recommendations:

10 recommendations made in the Roadmap for Open Science. Key points include the adoption of an OS framework in Canada, making federal scientific research outputs ‘open by default’, and implementing FAIR principles. (Government of Canada, 2020).

10 recommendations in the Roadmap for Open Science. Key points include the adoption of an OS framework, making federal scientific research outputs ‘open by default’, and implementing FAIR principles (Government of Canada, 2020).

Model Science Integrity Policy

Canada also has a Model Science Integrity Policy (MSIP) for the public service. The MSIP represents an internal commitment to integrity and accountability in science. Various mandates in the MSIP state that their purpose is to increase public trust in the credibility and reliability of government research and scientific activities, and ensure that research and scientific information are made available in keeping with the Government of Canada’s Directive on Open Government. The MSIP echoes Canada’s commitment to OS.

Indigenous Data Governance 

Finally, Canada has some commitment to supporting Indigenous rights to self-determination and data governance, but does not incorporate standards such as CARE principles which support OS  nor the OCAP Principles when it comes to Indigenous data governance. These extend the FAIR principles.

The Global Indigenous Data Alliance (GIDA) introduced the CARE principles to complement the FAIR principles in 2019. The CARE principles for Indigenous data governance were developed to address a lack of engagement between the open science movement and Indigenous rights and interests (GIDA, 2019).

The FAIR principles focus on data accessibility of data and sharing but fail to address power differences and the impact of colonialism experienced by Indigenous peoples and their right to exercise control and ownership of data about them and local and traditional knowledge. The CARE principles are crucial for the recognition and advancement of these rights as they encourage open science (and other ‘open’ movements) to “consider both people and purpose in their advocacy and pursuits” (GIDA, 2019). The CARE principles are contrasted with the FAIR principles in the below image from the GIDA website:

The CARE principles, which are “collective benefit, authority to control, responsibility, and ethics”, contrasted with the FAIR principles, which are “findable, accessible, interoperable, and reusable” (GIDA, 2019)

The CARE principles are “collective benefit, authority to control, responsibility, and ethics”, contrasted with the FAIR principles, which are “findable, accessible, interoperable, and reusable” (GIDA, 2019)

The OCAP Principles of Ownership, Control, Access and Possession are another set of important principles, that are a better fit in the Canadian Context.  Members of our project currently taking the Fundamentals of OCAP course and we hope to better incorporate these approaches in our work and in how we assess official reporting. Though Indigenous data governance and handling of Indigenous knowledge are not addressed in the Open Science Roadmap, the Data Strategy Roadmap for the Federal Public Service does demonstrate a federal approach to supporting Indigenous data strategies (see below):

Recommendation #8 from the Data Strategy Roadmap for the Federal Public Service which states Canada’s recognition of the Indigenous right to self-determination and data governance (Government of Canada, 2019)

Recommendation #8 from the Data Strategy Roadmap for the Federal Public Service which states Canada’s recognition of the Indigenous right to self-determination and data governance (Government of Canada, 2019)

Next Steps

Much progress has been made in terms of publishing, reporting and communicating data in the short time since COVID-19 began (though not without pressure from the media!). Open access to scientific research and public health reports have been helpful to facilitate the rapid response to the virus and keeping the public informed on how science informs governments actions. There is, however, much left to be done.

  1. Open Science should consider bias in data as well as invisibilities for example interdisciplinary work that helps paint the fuller picture of the impact of the virus. For example, interdisciplinary and intersectional approaches to data categories, including research based in critical race theory (CRT), Indigenous perspectives, socio-demographics and gig labour groups for example.
  2. Second, as suggested by the OECD, making COVID-19 data Findable, Accessible, Interoperable and Reusable is critical for a more effective rapid response. Lack of adherence to FAIR principles currently presents challenges to open science research.
  3. Finally, a meaningful Canadian OS framework should also incorporate standards for Indigenous Data Governance such as CARE Principles and OCAP Principles ensure respectful data practices are followed.

The Tracing COVID-19 Data team is in the process of developing a framework to assess official COVID-19 reporting in Canada to see if they comply with OS, FAIR, CARE, OCAP, and open-by-default at all levels of government. We will draw on Canada’s commitments OS and FAIR in – Canada’s 2018-2020 National Action Plan on Open Government, Open Science Roadmap, the Model Science Integrity Policy and the Open Data Charter.

Is Canada FAIR?

Stay tuned!

Recommendation

All official Federal, Provincial/Territorial and City public COVID-19 data reporting should be open data, open by design and by default, research should be published in open access (OA) Journals and should adhere to open science (OS) such as the FAIR principles , CARE Principles, OCAP Principles and the Open Data Charter.

References

Canadian Internet Policy and Public Interest Clinic. Open Data, Open Citizens? https://cippic.ca/en/open_governance/open_data_and_privacy

Centres for Disease Control and Prevention. (n.d.). SARS- Associated Coronavirus (SARS-CoV) Sequencing. https://www.cdc.gov/sars/lab/sequence.html

CTVNews. (2020). Project Pandemic: Reporting on COVID-19 in Canada. 
https://www.ctvnews.ca/health/coronavirus/project-pandemic

Federated Research Data Repository. (2018). FAIR Principles. 
https://www.frdr-dfdr.ca/docs/en/fair_principles/

Global Indigenous Data Alliance. (2019). CARE Principles for Indigenous Data Governance. 
https://www.gida-global.org/care

Government of Canada. (2014). Directive on open government. 
https://www.tbs-sct.gc.ca/pol/doc-eng.aspx?id=28108

Government of Canada. (May, 2016). Open by default and modern, easy to use formats. 
https://open.canada.ca/en/content/open-default-and-modern-easy-use-formats

Government of Canada. (2017). Model policy on scientific integrity.
https://www.ic.gc.ca/eic/site/063.nsf/eng/h_97643.html

Government of Canada. (2018). Canada’s 2018-2020 National Action Plan on Open Government. https://open.canada.ca/en/content/canadas-2018-2020-national-action-plan-open-government#toc8

Government of Canada. (2018). Report to the Clerk of the Privy Council: A Data Strategy Roadmap for the Federal Public Service. https://www.canada.ca/content/dam/pco-bcp/documents/clk/Data_Strategy_Roadmap_ENG.pdf

Government of Canada. (2020). Coronavirus disease (COVID-19): Outbreak update.
https://www.canada.ca/en/public-health/services/diseases/coronavirus-disease-covid-19.html?utm_campaign=not-applicable&utm_medium=vanity-url&utm_source=canada-ca_coronavirus

Government of Canada. (2020). Office of the Chief Science Advisorhttps://www.ic.gc.ca/eic/site/063.nsf/eng/h_97646.html

Government of Canada. (2020). Open Government Portal.
https://open.canada.ca/data/en/dataset

Lauriault, T. (2020, April 17). Tracing COVID-19 Data: COVID-19 Demographic Reporting. Datalibre.
http://datalibre.ca/2020/04/17/covid-19-demographic-reporting/

National Centre for Biotechnology Information. (2020). Public Health Emergency COVID-19 Initiative.
https://www.ncbi.nlm.nih.gov/pmc/about/covid-19/?cmp=1

Open Data Charter. (n.d.). The International Open Data Charter.
https://opendatacharter.net

Organisation for Economic Co-operation and Development. (2020, May 12). OECD Policy Responses to Coronavirus (COVID-19): Why open science is critical to combatting COVID-19.
http://www.oecd.org/coronavirus/policy-responses/why-open-science-is-critical-to-combatting-covid-19-cd6ab2f9/

Ford & Airhihenbuwa. (2010). The public health critical race methodology: Praxis for antiracism research. Science Direct.
https://www.sciencedirect.com/science/article/abs/pii/S0277953610005800#!

Semantic Scholar. (2020). CORD-19: COVID-19 Open Research Dataset.
shorturl.at/wETZ5 

The Lancet. (January, 2020). Genomic characterization and epidemiology of 2019 novel coronavirus: implications for virus origins and receptor binding.
https://www.thelancet.com/journals/lancet/article/PIIS0140-6736(20)30251-8/fulltext

The National Academies of Science, Engineering, Medicine. (2018). Open Science by Design: Realizing a Vision for 21st Century Research. Chapter 1, Front Matter. 
https://www.nap.edu/read/25116/chapter/1

The Star. (2020). Coronavirus & COVID-19 Data. https://www.thestar.com/coronavirus/data.html

Vivli. (2020).
https://vivli.org/about/overview-2/

Tags: , , ,

I was just awarded a small but not insignificant award as part of the Carleton University COVID-19 Rapid Response Research Grants. Below is a description of what I will be up to, along with some great students and expert advisors.  I will share everyone’s names later.  Results of the work will be published here as it becomes available!  Stay tuned. Also, let me know if you want to contribute in any way! Tracey dot Lauriault at Carleton dot CA

Research Summary

There is much official COVID-19 data reporting by federal, provincial, territorial and Indigenous Communities. As the pandemic evolves, and more information comes to light, there is a call to add data attributes about Indigenous, Black and Racialized groups and of the affected labour force, and to report where cases predominate. The pandemic also revealed that foundational datasets are missing, such as a national list of elder care homes, maps of local health regions and data about the digital divide. This project will embrace technological citizenship, adopt a critical data studies theoretical framework and a data humanitarian approach to rapidly assess data shortfalls, identify standards, and support the building of infrastructure. This involves training students, conducting rapid response research, developing a network of experts, learning by doing and a transdisciplinary team of peer reviewers to assess results. The knowledge will be mobilized in open access blog posts, infographics, policy briefs and scholarly publications.

Research challenge:

Official COVID-19 public heath reports by Federal, Provincial, and Territorial (F/P/T) and First Nation Communities are uneven and there are calls to improve them ( 1 CBC News, Toronto Star). Asymmetries can be attributed to dynamically evolving challenges associated with the pandemic, such as working while practicing social distancing; jurisdictional divisions of power in terms of health delivery; and responding to a humanitarian crisis, where resources are stretched and infrastructures are splintered (i.e. digital divide, nursing home conditions).

The Harvard Humanitarian Initiative (HHI) developed a rights-based approach to the management of data and technologies during crisis situations which includes the right to: be informed, protection, privacy and security, data agency and rectification and redress (2). These apply to contact tracing (3 ITWorld, Scassa) and to equity groups calling for demographic data (1). Other have conducted rapid response data reporting, for example after the Haiti Earthquake volunteers developed real-time crowdsourcing data collection systems to support humanitarian responders (4 Meier) and WeRobotics mobilizes local drone expertise to objectively assess proposed pandemic response technologies (5 WeRobotics).

This research will apply a critical data studies (CDS) theoretical framework (6 Kitchin & Lauriault), the principles of the HHI and, practice technological citizenship (7 Feenbert) to the study of the Canadian COVID-19 data response. Lauriault will leverage her expertise and Canadian and international network of open data, open government, civic technology experts in government, civil society, and Indigenous Communities (see CV) as seen in the policy briefs published on DataLibre.ca (8) to rapidly assess and support COVID-19 data management and reporting.

The objective is to carry out the following activities:

  1. Compare official COVID-19 public health data reports to identify gaps and best practices (9 Lauriault & Shields).
  2. Identify and support the building of framework datasets to standardize reporting (10 Lauriault).
  3. Analyze data standards and protocols to support data management, interoperability and cross-jurisdictional reporting (11 GeoConnections).
  4. Publish case-studies, resources, an archives of official reporting, and a glossary and
  5. Rapidly conduct expert analysis, peer review, knowledge mobilization and provide evidence-based recommendations to improve data reporting.

The rationale for this research is as follows:

  1. Official COVID-19 public health data are inconsistently reported, impeding comparability, and the ability to assess impact and target actions. Also, predictions missed seniors’ homes, precarious labour, and Indigenous communities and social determinants (12 Global News, NCCDH), resulting in an increase in cases and deaths. Currently job classifications and Indigenous, Black, and Racialized people classifications (13 CTV News) remain absent. This research will create a corpus of F/P/T and Indigenous Communities’ official reports, compare results, identify gaps.
  2. Framework data are standard information infrastructures upon which other analysis can consistently be done (14 Toronto Star). When this is lacking analysis is impeded, for example there is no national reporting by health region since no national framework dataset exists (15 Lauriault), and mitigating the digital divide is thwarted with a lack of broadband maps (16 Potter & Lauriault et al.). Other missing national datasets include senior care facilities, homeless shelters, precarious labour, and Indigenous Communities (17 Gaetz et al.). Needed framework datasets will be identified and if necessary coordinate their building (18 SPCOStatCan LODE), advocacy for the opening of public datasets such as corporate registries may be carried out (19 Fed. Registry,  Open Corporate, Open Contracting), and experts from public health , social planning, and Indigenous Communities will help identify localized frameworks.
  3. Consistent COVID-19 reporting requires an interoperable infrastructure which builds upon standards developed through consensus processes (20 CIHI, PHAC). Current uneven reporting may be attributed to a lack of standards adoption and formalization in terms of data flows. This research will develop a repository of standards and protocols and share these with decision-makers to improve interoperability (i.e. Data Standards for the Identification and Monitoring of Systemic Racism (21 ON Govt) and FNIGC OCAP Principles (22 FNIGC)).
  4. Rapidly mobilizing knowledge is important to improve reporting and manage data, and to build a crisis data reporting infrastructure for the future. This project will compile, and archive information, rapidly assess and peer review results with experts and report results on DataLibre.ca and other websites, will produce infographics and policy briefs, deliver online webinars, and help administrators and Indigenous Communities improve their data and technology policies.

A CDS framework recognizes that data have social and material shaping qualities and that they are never politically neutral while also being inseparable from the people and institutions who create them including practices, techniques, and infrastructures. This involves a team of data, technology, legal, social and health, and Indigenous experts to rapidly assess official COVID-19 data assemblages and to act as technological citizens by applying knowledge in real time and mobilize results to mitigate the data shortfalls witnessed during this crisis and support decision makers to respond with a data humanitarian and rights-based approach for now and to better respond in the future.

Expected Impact:

The target audience for this rapid response data and technology reporting is F/P/T public officials and Indigenous Community Leaders who manage public health, socio-economic, statistical and official record data flows; and civil society actors and the public involved in open data, open government and open contracting, transparency and accountability. This includes C-class executives, chief technology, information data, and digital officers.

The outcome of this research is to standardize and improve humanitarian crisis data management and data reporting in the short term to ensure consistent reporting, and in the long term establish standardized data workflows and operationalize data infrastructures for this pandemic in preparation for the next.

The timing to compile, inventory and build an open access archives of official data reporting is now as the fractures in the system have become apparent in real-time and have had negative consequences. It is important to monitor the response as it evolves so as to be able to improve it while our collective institutional memory is fresh and to have the evidence available as a reminder for if and when we forget, but also to build more robust systems.

The results of this research will be continuously reported and made openly accessible as it becomes available and will lead to the formation of a new research team.

Tags: , , , , , , ,

Below is and excerpt from a blogpost on the Programmable City website.  I work there now, and post quite a bit of open data, big data, data infrastructure posts there.  Most do not include any CanCon so I do not always put them here.  The Open Government Partnership is big for the Federal Government in Canada, and the OGP Independant Reporting Mechanism report by the Independant Reviewer Dr. Mary Francoli, was not particularly kind to our Action Plan, and rightly so.  The OGP is however not that big a deal on the ground or with civil society in Canada.  It is however really important elsewhere, in Ireland for example, the EU and the OGP are leveraged as a way to bring and promote progressive practices, regulation, laws, and so on.  In developing countries, it is a way for civil society organizations to have a voice and meet officials they would otherwise not get to interact with at home, and again have a transnational organization promote change.

I will try and post here more often!  Took me time to adjust to my new home.  Rest assured though, that I have not forgotten you nor do I not pay attention to the data shenanigans ongoing in Canada!

********************************

I attended the European Regional Meeting of the Open Government Partnership at the Dublin Castle Conference Centre in May of this year.  The meeting was a place for performance and evaluation wonks to show their wares, especially at the following sessions: Open Government Standards and Indicators for Measuring Progress, The EU’s Role in Promoting Transparency and Accountability and Engagement with the OGP, and Open Contracting: Towards a New Global Norm.  I did not attend the Independent Reporting Mechanism (IRM) sessions, but having read the IRM report for Canada, I know that it too is an emerging performance evaluation indicator space, which is affirmed by a cursory examination of the IRMs two major databases.  The most promising, yet the most disappointing session was the Economic Impact of Open Data session.  This is unfortunate as there are now a number of models by which the values of sharing, disseminating and curating data have been measured.  It would have been great to have heard either a critical analysis or a review of the newly released Ordinance Survey of Ireland report, Assessment of the Economic Value of the Geospatial Information Industry in Ireland, the many economic impact models listed here in the World Bank Toolkit, or the often cited McKinsey Global Institute Open data: Unlocking innovation and performance with liquid information report.  Oh Well!

While there I was struck by the number of times maps were displayed.  The mapping of public policy issues related to openness seems to have become a normalized communication method to show how countries fare according to a number of indicators that aim to measure how transparent, prone to corruption, engagemed civil society is, or how open in terms of data, open in terms of information, and open in terms of government nation states are.

What the maps show is how jurisdictionally bound up policy, law and regulatory matters concerning data are.  The maps reveal how techno-political processes are sociospatial practices and how these sociospatial matters are delineated by territorial boundaries.  What is less obvious, are the narratives about how the particularities of the spatial relations within these territories shape how the same policies, laws and regulation are differentially enacted.

Below are 10 world maps which depict a wide range of indicators and sub-indicators, indices, scorecards, and standards.  Some simply show if a country is a member of an institution or is a signatory to an international agreement.  Most are interactive except for one, they all provide links to reports and methodologies, some more extensive than others.  Some of the maps are a call to action; others are created to solicit input from the crowd, while most are created to demonstrate how countries fare against each other according to their schemes.  One map is a discovery map to a large number of indicators found in an indicator portal while another shows the breadth of civil society participation.  These maps are created in a variety of customized systems while three rely on third party platforms such as Google Maps or Open Street Maps.  They are published by a variety of organizations such as transnational institutions, well resourced think tanks or civil society organizations.

We do not know the impact these maps have on the minds of the decision makers for whom they are aimed, but I do know that these are often shown as backdrops to discussions at international meetings such as the OGP to make a point about who is and is not in an open and transparent club.  They are therefore political tools, used to do discursive work.  They do not simply represent the open data landscape, but actively help (re)produce it.  As such, they demand further scrutiny as to the data assemblage surrounding them (amalgams of systems of thought, forms of knowledge, finance, political economies, governmentalities and legalities, materialities and infrastructures, practices, organisations and institutions, subjectivities and communities, places, and marketplaces), the instrumental rationality underpinning them, and the power/knowledge exercised through them.

This is work that we are presently conducting on the Programmable City project, which will  complement a critical study concerning city data, indicators, benchmarking and dashboards, and we’ll return to them in future blog posts.

1.       The Transparency International Corruption by Country / Territory Map

Users land on a blank blue world map of countries delineated by a thick white line, from which they select a country of interest.  Once selected a series of indicators and indices such as the ‘Corruption measurement tools’, ‘Measuring transparency’ and ‘Other governance and development indicators’ appear.  These are measured according rankings to a given n, scored as a percentage and whether or not the country is a signatory to a convention and if it is enforced.  The numbers are derived from national statistics and surveys.  The indicators are:

  • Corruption Perceptions Index (2013), Transparency International
  • Control of Corruption (2010), World Bank dimension of Worldwide Governance Indicators
  • The Bribe Payer’s Index (2011), Transparency International
  • Global Corruption Barometer (2013), Transparency International
  • OECD Anti-Bribery Convention (2011)
  • Financial Secrecy Index (2011), Tax Justice Network
  • Open Budget Index (2010), International Budget Partnership
  • Global Competitiveness Index (2012-2013), World Economic Forum Global Competitiveness Index
  • Judicial Independence (2011-2012), World Economic Forum Global Competitiveness Index
  • Human Development Index (2011), United Nations
  • Rule of Law (2010), World Bank dimension of Worldwide Governance Indicators
  • Press Freedom Index (2011-2012) Reporters Without Borders
  • Voice & Accountability (2010), World Bank dimension of Worldwide Governance Indicators

By clicking on the question mark beside the indicators, a pop up window with some basic metadata appears. The window describes what is being measured and points to its source.

The page includes links to related reports, and a comments section where numerous and colourful opinions are provided!

*****************************

View the rest at Programmable City.

Tags: , , ,