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New report: Governing by rankings – How the Global Open Data Index helps advance the open data agenda

- November 29, 2017 in Featured, Global Open Data Index, godi, GODI16, open data survey, research

This blogpost was jointly written by Danny Lämmerhirt and Mária Žuffová (University of Strathclyde). We are pleased to announce our latest report Governing by rankings – How the Global Open Data Index helps advance the open data agenda. The Global Open Data Index (GODI) is one of the largest worldwide assessments of how well governments publish open data, coordinated by Open Knowledge International since 2013. Over the years we observed how GODI is used to monitor open data publication. But to date, less was known how​ ​GODI​ ​may​ ​translate​ ​into​ ​open​ ​data​ ​policies​ ​and publication​. How does GODI mobilise support for open data? Which actors are mobilised? Which aspects of GODI are useful, and which are not? Our latest report provides insights to these questions.

Why does this research matter?

Global governance indices like GODI enjoy great popularity due to their capacity to count, calculate, and compare what is otherwise hardly comparable. A wealth of research – from science and technology studies to sociology of quantification and international policy – shows that the effects of governance indicators are complex (our report provides an extensive reading list). Different audiences can take up indices to different (unintended) ends. It is therefore paramount to trace the effects of governance indicators to inform their future design. The report argues that there are multiple ways of looking for ‘impacts’ depending on different audiences, and how they put GODI into practice. Does a comparative open data ranking like GODI help mobilise high-level policy commitments? Does it incentivise individual government agencies to adjust and improve the publication of open data? Does it open up spaces for discussion and deliberation between government and civil society? This thinking builds on an earlier report by Open Knowledge International arguing that indicators have different audiences, with different lived experiences, needs, and agendas. While any form of measurement needs to align with these needs to become actionable (which affects how the impact of indicators will take shape), it also needs to retain comparability.

Our findings

We used Argentina, United Kingdom and Ukraine as case studies to represent different degrees of open data publication, economic development and political set-up. Our report, drawing from a series of twelve interviews and document analysis, suggests that GODI drives change primarily from within government. We assume this finding is partly due to our limited sample size. While key actors in the government are easy to identify, as open data publication is often one of their job responsibilities,  further research is needed to identify more civil society actors and how they engage with GODI. Below we describe nine ways how GODI influences open data policy and publication.
  1. Getting international visibility and achieving progress in country rankings or generally high ranking may incentivise and maintain high-level political support for open data, despite non-comparability of results across years.  
  2. In the absence of open data legislation, GODI has been used by Argentinian government as a soft policy tool to pressure other government agencies to publish data.
  3. Government agencies tasked with implementing open data used GODI to reward and point out progress made by other agencies, but also flag blockages to high-level politicians.  
  4. GODI sets standards what datasets to publish and sets a baseline for improvement. Outcomes are debatable around categories where the central government does not have easy political levers to publish data.
  5. GODI may be confounded with broader commitments to open government and used as an argument to reduce investment in other aspects of open government agenda. In the past, some high-level politicians presented  high ranking in GODI as evidence of government transparency and obsoletion of other ways of providing government information.  
  6. This effect may possibly be exacerbated by superficial media coverage that reports on the ranking without engaging with broader information and transparency policies. An analysis of Google News results suggests that journalists tend to reproduce (mostly politicians’) misconceptions and confound a good ranking in GODI with a high degree of government transparency and openness.
  7. Our findings suggest that individuals and organisations working around transparency and anti-corruption make little use of GODI due to a lack of detail and a misalignment with their specialised work tasks. For instance, Transparency International Ukraine uses the Transparent Public Procurement Rating to evaluate the legal framework, aside from the publication of open data.
  8. On the other hand, academics show interest to GODI to develop new governance indicators. They also often use country scores as a proxy for measuring open data availability.
  9. GODI has a potential for use in data journalism. Data journalism trainers may use it as a source of government data during their trainings.  

What we learned and the road ahead

Our research suggests that governments in all analysed countries pay attention to GODI.  With a few exceptions, they use it mostly to support open data publication and pave the way for new open data policies. While this is a promising finding, it has important implications for GODI and its design. If GODI sets standards in open data publication, as some interviewees from the government suggest, it needs to make sure to represent different data demands in the assessment and to encourage the implementation of sound policies. The challenge is to support policy development, which is often a lengthy process as opposed to short-lived rank-seeking. Some interviewees suggested valuable avenues for GODI’s design. For instance, assessing progress in open data publication perpetually rather than once a year over a limited timespan would require a long-term commitment to open data publication and better opportunities for civic engagement, as it would prevent governments from updating datasets once a year before GODI’s deadline only. Another route forward is discussed in another recent research by OKI, highlighting the potential to adjust an open data index to align it more closely to specific needs of topical expert organisations. Beyond engaging via GODI, civil society and academia might also participate in the development of new data monitoring instruments such as the Open Data Survey, that are relevant for their mission.    

How do open data measurements help water advocates to advance their mission?

- November 23, 2017 in Global Open Data Index, godi, GODI16, open data survey, WASH, water quality

This blogpost was jointly written by Danny Lämmerhirt and Nisha Thompson (DataMeet). Since its creation, the open data community has been at the heart of the Global Open Data Index (GODI). By teaming up with expert civil society organisations we define key datasets that should be opened by government to align with civil society’s priorities. We assumed that GODI also teaches our community to become more literate about government institutions, regulatory systems and management procedures that create data in the first place – making GODI an engagement tool with government.

Tracing the publics of water data

Over the past few months we have reevaluated these assumptions. How do different members of civil society perceive the data assessed by GODI? Is the data usable to advance their mission? How can GODI be improved to accommodate and reflect the needs of civil society? How would we go about developing user-centric open data measurements and would it be worth to run more local and contextual assessments? As part of this user research, OKI and DataMeet (a community of data science and open data enthusiasts in India) teamed up to investigate the needs of civic organisations in the water, sanitation and health (WASH) sector. GODI assesses whether governments release information on water quality, that is pollution levels, per water source. In detail this means that we check whether water data is available at potentially a household level or  at each untreated public water source such as a lake or river. The research was conducted by DataMeet and supervised by OKI, and included interviews and workshops with fifteen different organisations. In this blogpost we share insights on how law firms, NGOs, academic institutions, funding and research organisations perceive the usefulness of GODI for their work. Our research focussed on the South Asian countries India, Pakistan, Nepal, and Bangladesh. All countries face similar issues with ensuring safe water to their populations because of an over-reliance on groundwater, geogenic pollutants like arsenic, and high pollutants from industry, urbanisation, farming, and poor sanitation.

According to the latest GODI results, openness of water quality data remains low worldwide.

What kinds of water data matter to organisations in the water sector?

Whilst all interviewed organisations have a stake in access to clean water for citizens, they have very different motivations to use water quality data. Governmental water quality data is needed to
  1. Monitor government activities and highlight general issues with water management (for advocacy groups).
  2. Create a baseline to compare against civil society data (for organisations implementing water management systems)
  3. Detect geographic target areas of under-provision as well as specific water management problems to guide investment choices (for funding agencies and decision-makers)
Each use case requires data with different quality. Some advocacy interviewees told us that government data, despite a potential poor reliability, is enough to make the case that water quality is severely affected across their country. In contrast, researchers have a need for data that is provided continuously and at short updating cycles. Such data may not be provided by government. Government data is seen as support for their background research, but not a primary source of information. Funders and other decision-makers use water quality data largely for monitoring and evaluation – mostly to make sure their money is being used and is impactful. They will sometimes use their own water quality data to make the point that government data is not adequate. Funders push for data collection at a project level not continuous monitoring which can lead to gaps in understanding. GODI’s definition of water quality data is output-oriented and of general usefulness. It enables finding the answer to whether the water that people can access is clean or not. Yet, organisations on the ground need other data – some of which is process-oriented – to understand how water management services are regulated and governed or what laboratory is tasked to collect data. A major issue for meaningful engagement with water-related data is the complexity of water management systems. In the context of South Asia, managing, tracking, and safeguarding water resources for use today and in the future is complex. Water management systems, from domestic to industrial to agricultural ones, are diverse and hard to examine and keep accountable. Where water is coming from, how much of it is being used and for what, and then how waste is being disposed of are all crucial questions to these systems. Yet there is very little data available to address all these questions.

How do organisations in the WASH sector perceive the GODI interface?

GODI has an obvious drawback for the interviewed organisations: transparency is not a goal for organisations working on the ground and does not in itself provoke an increase in access to safe water or environmental conservation. GODI measures the publication of water quality data, but is not seen to stimulate improved outcomes. It also does not interact with the corresponding government agency. One part of GODI’s theory of change is that civil society becomes literate about government institutions and can engage with government via the publication of government data. Our interviews suggest that our theory of change needs to be reconsidered or new survey tools need to be developed that can enhance engagement between civil society and government. Below we share some ideas for future scenarios.

Our learnings and the road ahead

Adding questions to GODI

Interviews show that GODI’s current definition of water quality data does not always align with the needs of organisations on the ground. If GODI wants to be useful to organisations in the WASH sector, new questions can be added to the survey and be used as a jumping off point for outreach to groups. Some examples include:
  1. Add a question regarding metadata and methodology documentation to capture quality and provenance water data, but also where we found and selected data.
  2. Add a question regarding who did the data collection government or partner organisation. This allows community members to trace the data producers and engage with them.
  3. Assess transparency of water reports. Reports should be considered since they are an important source of information for civil society.

Customising the Open Data Survey for regional and local assessments

Many interviewees showed an interest in assessing water quality data at the regional and hyperlocal level. DataMeet is planning to customise the Open Data Survey and to team up with local WASH organisations to develop and maintain a prototype for a regional assessment of water quality. India will be our test case since there is local data for the whole country available at varying degrees across states. This may include to also assess quality of data and access to metadata. Highest transparency would mean to have water data from each individual lab were the samples are sent. Another use case of the Open Data Survey would include to measure the transparency of water laboratories. Bringing more transparency and accountability to labs would be the most valuable for ground groups sending samples to labs across the country.

Map of high (> 30 mg/l) fluoride values from 2013–14. From: The Gonda Water Data story

Storytelling through data

Whilst some interviewees saw little use in governmental water quality data, its usefulness can be greatly enhanced when combined with other information. As discussed earlier, governmental water data gives snapshots and may provide baseline values that serve NGOs as rough orientation for their work. Data visualisations could present river and water basin quality and tell stories about the ecological and health effects. Behavior change is a big issue when adapting to sanitation and hygiene interventions. Water quality and health data can be combined to educate people. If you got sick, have you checked your water? Do you use a public toilet? Are you washing your hands? This type of narration does not require granular accurate data.

Comparing water quality standards

Different countries and organisations have different standards for what counts as high water pollution levels. Another project could assess how the needs of South Asian countries are being served by a comparing pollution levels with different standards. For instance, fluorosis is an issue in certain parts of India: not just from high fluoride levels but also because of poor nutrition in those areas. Should fluoride affected areas have lower permissible amounts in poorer countries? These questions could be used to make water quality data actionable to advocacy  groups.

The future of the Global Open Data Index: assessing the possibilities

- November 1, 2017 in Global Open Data Index, godi, GODI16, Open Government Data, open-government

In the last couple of months we have received questions regarding the status of the new Global Open Data Index (GODI) from a few members of our Network. This blogpost is to update everyone on the status of GODI and what comes next. But first, some context: GODI is one of the biggest assessments of the state of open government data globally, alongside the Web Foundation’s Open Data Barometer. We notice persistent obstacles for open data year-by-year. High-income countries regularly secure top rankings, yet overall there is little to no development in many countries. As our latest State Of Open Government Data in 2017 report shows, data is often not made available publicly at all. If so, we see many issues around findability, quality, processability, and licensing. Individual countries are notable exceptions to the rule. The Open Data Barometer made similar observations in its latest report, mentioning a slow uptake of policy, as well as persistent data quality issues in countries that provide open data. So there is still a lot of work to be done. To resolve issues like engagement with our community, we started to explore alternative paths for GODI. This includes a shift in focus from a mere measurement tool to a stronger conversational device between our user groups throughout the process. We understand that we need to speak to new audiences and focus on measurement as a tool in real world applications. We need to focus more on this. We want to understand the use cases of the Open Data Survey (the tool that powers GODI and the Open Data Census) in different contexts and with different goals. We have barely seen a few of the possible uses of the tool in the open data sphere and we want to see even more. In order to learn more about how GODI is taken up by different user groups, we are also currently exploring GODI’s effects on open data policy and publication. We wish to understand more systematically how individual elements of the GODI interface (such as country ranking, dataset results, discuss forum entries) help mobilising support for open data among different user groups. Our goal is to understand how to improve our survey design and workflow so that they more directly support action around open data policy and publication. In addition we are developing a new vision for the Open Data Index to either measure open data on a regional and city-level or by topical areas. We will elaborate on this vision in a follow-up blogpost soon. Taking this all into account, we have decided to focus on working on the aforementioned use cases and a regional Index during 2018. In the meantime, we will still work with our community to define a vision that will make GODI a sustainable measurement tool: we understand that tracking the changes in government data publication is crucial for the activists and governments themselves. We know that progress around open data is slower than we would like it to be, but therefore we need to ensure that discussions around open data do not end. Please do not hesitate to submit new discussions around country entries on our forum or reach out to us if you have any ideas on how to take GODI forwards and improve. If you’re running an Open Data Census, we we’ll continue giving you support in the measurement you’re currently working on, whether it’s local, regional or you have any new idea of a Census you’d like to try. If you want to run your own Census, you can request it here, or send an email to index@okfn.org to see how we could collaborate further.

Open data quality – the next shift in open data?

- May 31, 2017 in Data Quality, Global Open Data Index, GODI16, Open Data

This blog post is part of our Global Open Data Index blog series. It is a call to recalibrate our attention to the many different elements contributing to the ‘good quality’ of open data, the trade-offs between them and how they support data usability (see here some vital work by the World Wide Web Consortium). Focusing on these elements could help support governments to publish data that can be easily used. The blog post was jointly written by Danny Lämmerhirt and Mor Rubinstein.   Some years ago, open data was heralded to unlock information to the public that would otherwise remain closed. In the pre-digital age, information was locked away, and an array of mechanisms was necessary to bridge the knowledge gap between institutions and people. So when the open data movement demanded “Openness By Default”, many data publishers followed the call by releasing vast amounts of data in its existing form to bridge that gap. To date, it seems that opening this data has not reduced but rather shifted and multiplied the barriers to the use of data, as Open Knowledge International’s research around the Global Open Data Index (GODI) 2016/17 shows. Together with data experts and a network of volunteers, our team searched, accessed, and verified more than 1400 government datasets around the world. We found that data is often stored in many different places on the web, sometimes split across documents, or hidden many pages deep on a website. Often data comes in various access modalities. It can be presented in various forms and file formats, sometimes using uncommon signs or codes that are in the worst case only understandable to their producer. As the Open Data Handbook states, these emerging open data infrastructures resemble the myth of the ‘Tower of Babel’: more information is produced, but it is encoded in different languages and forms, preventing data publishers and their publics from communicating with one another. What makes data usable under these circumstances? How can we close the information chain loop? The short answer: by providing ‘good quality’ open data.  

Understanding data quality – from quality to qualities

The open data community needs to shift focus from mass data publication towards an understanding of good data quality. Yet, there is no shared definition what constitutes ‘good’ data quality. Research shows that there are many different interpretations and ways of measuring data quality. They include data interpretability, data accuracy, timeliness of publication, reliability, trustworthiness, accessibility, discoverability, processability, or completeness.  Since people use data for different purposes, certain data qualities matter more to a user group than others. Some of these areas are covered by the Open Data Charter, but the Charter does not explicitly name them as ‘qualities’ which sum up to high quality. Current quality indicators are not complete – and miss the opportunity to highlight quality trade-offs Also, existing indicators assess data quality very differently, potentially framing our language and thinking of data quality in opposite ways. Examples are: Some indicators focus on the content of data portals (number of published datasets) or access to data. A small fraction focus on datasets, their content, structure, understandability, or processability. Even GODI and the Open Data Barometer from the World Wide Web Foundation do not share a common definition of data quality.
 Arguably, the diversity of existing quality indicators prevents from a targeted and strategic approach to improving data quality.

At the moment GODI sets out the following indicators for measuring data quality:
  • Completeness of dataset content
  • Accessibility (access-controlled or public access?)
  • Findability of data
  • Processability (machine-readability and amount of effort needed to use data)
  • Timely publication
This leaves out other qualities. We could ask if data is actually understandable by people. For example, is there a description what each part of the data content means (metadata)?   Improving quality by improving the way data is produced Many data quality metrics are (rightfully so) user-focussed. However, it is critical that government as data producers better understand, monitor and improves the inherent quality of the data they produce. Measuring data quality can incentivise governments to design data for impact: by raising awareness of the quality issues that would make data files otherwise practically impossible to use. At Open Knowledge International, we target data producers and the quality issues of data files mostly via the Frictionless Data project. Notable projects include the Data Quality Spec which defines some essential quality aspects for tabular data files. GoodTables provides structural and schema validation of government data, and the Data Quality Dashboard enables open data stakeholders to see data quality metrics for entire data collections “at a glance”, including the amount of errors in a data file. These tools help to develop a more systematic assessment of the technical processability and usability of data.

A call for joint work towards better data quality

We are aware that good data quality requires solutions jointly working together. Therefore, we would love to hear your feedback. What are your experiences with open data quality? Which quality issues hinder you from using open data? How do you define these data qualities? What could the GODI team improve?  Please let us know by joining the conversation about GODI on our forum.

Hilf mit, die Offenheit der österreichischen Regierung zu erfassen: Der Global Open Data Index 2016 ist hier!

- November 22, 2016 in Global Open Data Index 2016, GODI16, Open Data

Mach mit beim Global Open Data Index – dem internationalen Zensus zu Open Government Data. GODI 2016 is here! Open Knowledge International ruft zum vierten Mal die Open Data Community auf, gemeinsam den Status Quo von Open Government Data in der Welt sichtbar zu machen. Dieses Jahr werden beim Global Open Data Index, kurz GODI, Informationen zu 15 verschiedenen Datensätzen gesammelt um so die Qualität der Open Government Data Initiativen weltweit miteinander zu vergleichen. Österreich hatte beim Index 2015 den 23. Platz von 122 Nationen erreicht, wir sind schon gespannt wie wir dieses Mal abschneiden.

Zeitplan

Die Einreichung ist bereits möglich und noch bis 15. Dezember für alle geöffnet. Im Januar beginnt dann der Review. Danach werden die Einreichungen an die jeweilige Regierung für Kommentare gesendet. Die finale Entscheidung treffen die Reviewer. Wenn alle Reviews fertig und die Datensets von den Regierungen evaluiert worden sind wird der finale Score auf index.okfn.org angezeigt.

Der Survey

Mitmachen und selber Datensätze eintragen ist ganz einfach. Auf global.survey.okfn.org gehen, das Land, zu dem man gerne Eintragungen machen möchte, suchen (z. B. Austria) und beim passenden Datenset auf “+Add” klicken. Dieses Jahr wird zur Anmeldung via Google oder Facebook gefragt. Dabei werden von der Open Knowledge International keine Daten gespeichert – wenn du möchtest kannst du auch anonym einreichen. Bei Fragen bitte in den FAQ nachsehen, oder im Forum Fragen stellen. Bei spezielleren Fragen oder wenn eine schnelle Antwort nötig ist kannst du auch an index@okfn.org schreiben. Wer mehr Infos zur neuen Erhebungs-Methode für 2016 erfahren will, kann dies in einem Blog Post nachlesen.

Bleib zu weiteren Aktivitäten von Open Knowledge Österreich am Laufenden und melde dich für den Newsletter an!


Hilf mit die Offenheit der österreichischen Regierung zu erfassen: Der Global Open Data Index 2016 ist hier!

- November 22, 2016 in Global Open Data Index 2016, GODI16, Open Data

Mach mit beim Global Open Data Index – dem internationalen Zensus zu Open Government Data. GODI 2016 is here! Open Knowledge International ruft zum vierten Mal die Open Data Community auf, gemeinsam den Status Quo von Open Government Data in der Welt sichtbar zu machen. Dieses Jahr werden beim Global Open Data Index, kurz GODI, Informationen zu 15 verschiedenen Datensätzen gesammelt um so die Qualität der Open Government Data Initiativen weltweit miteinander zu vergleichen. Österreich hatte beim Index 2015 den 23. Platz von 122 Nationen erreicht, wir sind schon gespannt wie wir dieses Mal abschneiden.

Zeitplan

Die Einreichung ist bereits möglich und noch bis 15. Dezember für alle geöffnet. Im Januar beginnt dann der Review. Danach werden die Einreichungen an die jeweilige Regierung für Kommentare gesendet. Die finale Entscheidung treffen die Reviewer. Wenn alle Reviews fertig und die Datensets von den Regierungen evaluiert worden sind wird der finale Score auf index.okfn.org angezeigt.

Der Survey

Mitmachen und selber Datensätze eintragen ist ganz einfach. Auf global.survey.okfn.org gehen, das Land, zu dem man gerne Eintragungen machen möchte, suchen (z. B. Austria) und beim passenden Datenset auf “+Add” klicken. Je mehr Einreichungen es pro Datensatz es gibt, desto besser wird die Qualität des Rankings (fünf und mehr Beitragende pro Land und Datensatz  w#ren ideal). Dieses Jahr wird zur Anmeldung via Google oder Facebook gefragt. Dabei werden von der Open Knowledge International keine Daten gespeichert – wenn du möchtest kannst du auch anonym einreichen. Bei Fragen bitte in den FAQ nachsehen, oder im Forum Fragen stellen. Bei spezielleren Fragen oder wenn eine schnelle Antwort nötig ist kannst du auch an index@okfn.org schreiben. Wer mehr Infos zur neuen Erhebungs-Methode für 2016 erfahren will, kann dies in einem Blog Post nachlesen.

Bleib zu weiteren Aktivitäten von Open Knowledge Österreich am Laufenden und melde dich für den Newsletter an!