Ahead of this year’s International Open Data Conference #iodc16, Danny Lämmerhirt and Stefaan Verhulst provide information on the Measuring and Increasing Impact Action Session, which will be held on Friday October 7, 2016 at IODC in Room E. Further information on the session can be found here.

Lord Kelvin’s famous quote “If you can not measure it, you can not improve it” equally applies to open data. Without more evidence of how open data contributes to meeting users’ needs and addressing societal challenges, efforts and policies toward releasing and using more data may be misinformed and based upon untested assumptions.

When done well, assessments, metrics, and audits can guide both (local) data providers and users to understand, reflect upon, and change how open data is designed. What we measure and how we measure is therefore decisive to advance open data.

Back in 2014, the Web Foundation and the GovLab at NYU brought together open data assessment experts from Open Knowledge International, Organisation for Economic Co-operation and Development, United Nations, Canada’s International Development Research Centre, and elsewhere to explore the development of common methods and frameworks for the study of open data. It resulted in a draft template or framework for measuring open data. Despite the increased awareness for more evidence-based open data approaches, since 2014 open data assessment methods have only advanced slowly. At the same time, governments publish more of their data openly, and more civil society groups, civil servants, and entrepreneurs employ open data to manifold ends: the broader public may detect environmental issues and advocate for policy changes, neighbourhood projects employ data to enable marginalized communities to participate in urban planning, public institutions may enhance their information exchange, and entrepreneurs embed open data in new business models.


In 2015, the International Open Data Conference roadmap made the following recommendations on how to improve the way we assess and measure open data.

  1. Reviewing and refining the Common Assessment Methods for Open Data framework. This framework lays out four areas of inquiry: context of open data, the datapublished, use practices and users, as well as the impact of opening data.
  2. Developing a catalogue of assessment methods to monitor progress against the International Open Data Charter (based on the Common Assessment Methods for Open Data).
  3. Networking researchers to exchange common methods and metrics. This helps to build methodologies that are reproducible and increase credibility and impact of research.
  4. Developing sectoral assessments.

In short, the IODC called for refining our assessment criteria and metrics by connecting researchers, and applying the assessments to specific areas. It is hard to tell how much progress has been made in answering these recommendations, but there is a sense among researchers and practitioners that the first two goals are yet to be fully addressed.

“…there seems to be a disconnect between top-level frameworks and on-the-ground research”

Instead we have seen various disparate, yet well meaning, efforts to enhance the understanding of the release and impact of open data. A working group was created to measure progress on the International Open Data Charter, which provides governments with principles for implementing open data policies. While this working group compiled a list of studies and their methodologies, it has not (yet) deepened the common framework of definitions and criteria to assess and measure the implementation of the Charter. In addition, there is an increase of sector- and case-specific studies that are often more descriptive and context specific in nature, yet do contribute to the need for examples that illustrate the value proposition for open data.

As such, there seems to be a disconnect between top-level frameworks and on-the-ground research, preventing the sharing of common methods and distilling replicable experiences about what works and what does not. How to proceed and what to prioritize will be the core focus of the “Action Track: Measurement” at IODC 2016. The role of research for (scaling) open data practice and policy and how to develop a common open data research infrastructure will also be discussed at various workshops during the Open Data Research Summit, and the findings will be shared during the Action Track.

In particular, the Action Track will seek to focus on:

  • Demand and use: Specifically, whether and how to study the demand for and use of open data—including user needs and data life cycle analysis (as opposed to being mainly focused on the data supply or capturing evidence of impact), given the nascent nature of many initiatives around the world. And how to identify how various variables including local context, data supply, types of users, and impact relate to each other, instead of regarding them as separate. To be more deductive, explanatory, and generate insights that are operational (for instance, with regard to what data sets to release) there may be a need to expand the area of demand and use case studies (such as org).
  • Informing supply and infrastructure: How to develop deeper collaboration between researchers and domain experts to help identify “key data” and inform the government data infrastructure needed to provide them. Principle 1 of the International Open Data Charter states that governments should provide key data open by default, yet the questions remains in how to identify “key” data (e.g., would that mean data relevant to society at large?). Which governments (and other public institutions) should be expected to provide key data and which information do we need to better understand government’s role in providing key data? How can we evaluate progress around publishing these data coherently if countries organize the capture, collection, and publication of this data differently?
  • Networking research and researchers: How to develop more and better exchange among the research community to identify gaps in knowledge, to develop common research methods and frameworks and to learn from each other? Possible topics to consider and evaluate include collaborative platforms to share findings (such as Open Governance Research Exchange – OGRX), expert networks (such as https://networkofinnovators.org/), implementing governance for collaboration, dedicated funding, research symposia (more below on ODRS), and interdisciplinary research projects.

Make the most of this Action Track: Your input is needed

To maximize outcomes, the Measurement Action Area will catalyze input from conversations prior to the IODC. Researchers who want to shape the future agenda of open data research are highly encouraged to participate and discuss in following channels:

1) The Measurement and Increasing Impact Action Session, which will take place on Friday October 7, 2016 at IODC in Room E (more details here).

2) The Open Data Research Symposium, which is further outlined below. You can follow this event on Twitter with the hashtag #ODRS16.


The Open Data Research Symposium

The Measurement and Increasing Impact Action Session will be complemented by the second Open Data Research Symposium (#ODRS16), held prior to the International Open Data Conference on October 5, 2016 from 9:00am to 5:00pm (CEST) in Madrid, Spain (view map here for exact location). Researchers interested in the Measurement and Increasing Impact Action Session are encouraged to participate in the Open Data Research Symposium.

The symposium offers open data researchers an opportunity to reflect critically on the findings of their completed research and to formulate the open data research agenda.

Special attention is paid to the question how we can increase our understanding of open data’s use and impacts. View the list of selected papers here and the tentative conference program here.

Interested researchers may register here. Please note that registration is mandatory for participation.

This piece originally appeared on the IODC blog and is reposted with permission.

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Danny Lämmerhirt works on the politics of data, sociology of quantification, metrics and policy, data ethnography, collaborative data, data governance, as well as data activism. You can follow his work on Twitter at @danlammerhirt. He was research coordinator at Open Knowledge Foundation.