Wednesday, 19 December 2018; 10:00-11:00 am EST
There are many steps between producing and using data for policy making and more effective governance. Most of the efforts to increase data use, historically, has been placed in opening more datasets without thought to how people measure the uptake and use of such datasets. This focus is beginning to shift with the Publish with Purpose movement and with research from Development Gateway, AidData, Open Data Watch, PARIS21, and others. The aim is to shift the focus away from promoting the importance of data use and towards taking action to measure and understand it.
This webinar will bring together speakers to discuss methods for measuring data use; efforts to increase the capacity of producers to understand users’ needs on one end of the data value chain and policy makers and citizens to use the data on the other end; and what we can learn from current initiatives focusing on measuring data use. It is important for audience members of this webinar to think critically about how the methods presented are not only intended to be programmed into statistical capacity building initiatives for national statistical offices or other data producers but how a user-centric strategy can be implemented to better understand how their own data, whether it is new research or reports, can be used.
The goal of this webinar is to connect the dots between data production and data impact by highlighting lessons learned from recent research, strategies for increasing the use of data for decision making, and good practices on understanding and measuring use.
Questions to be addressed
- Why measuring data use is important? What is needed to better understand data use to improve data quality and trust in data?
- What are some of quick wins that countries could take advantage of to better monitor and hopefully increase data use? What are good practices and methods for measuring data use?
- How can different actors within the data for development ecosystem create an enabling environment to increase data use?
- How do policy makers access and use data for decision making? What are important case studies that demonstrate how to increase and encourage data use?
- How do we build data use into the processes, principles, and data quality assessments that guide the production side of data?
- What organizations or projects are working to understand and improve data use? What are the important resources they have assembled?
- Eric Swanson, Open Data Watch
- Tanya Sethi, AidData
- Muchiri Nyaggah, Local Development Research Institute (LDRI)
- Shaida Badiee, Open Data Watch (moderator)
Video – Connecting the Dots – Webinar 2
Following Webinar 2, participants had a few questions that are addressed below:
Q: We would like to know what were the criteria for evaluation. Do the data used in evaluating the level of coverage and use only consider NSO data or also data from other Algerian institutions mentioned in the spreadsheet?
A: (from Eric Swanson) – The Open Data Inventory (ODIN) assesses data found on the NSO website (http://www.ons.dz) or linked to the website. Therefore, data from other Algerian government agencies are included if they can be found by starting from the NSO website. ODIN assess the coverage of data in 21 statistical categories by looking at the availability of specific, “sentinel” indicators and their disaggregations. It assesses the openness of the same indicators using the criteria of the Open Definition 2.0: data should be freely available in non-proprietary, machine readable formats and accompanied by suitable metadata. Users should have options for downloading some or all of a dataset and the use of the data should be licensed under a Creative Common Public Domain (CC0) or by Attribution (CC-BY) license. More information on the ODIN methodology is available here.
Q: The SDGs approval promotes and active role of civil society and academia. According with our last “poll”, the Government Agencies and NSO should be leading an effort to increase data literacy and the use of data. How Civil Society and NGOs could support NSOs and Agencies to achieve that?
A: (from Eric Swanson) – Civil society and non-governmental organizations can support efforts to increase data literacy by demonstrating the appropriate use of statistics in their reports and advocacy documents. They could also work with the NSO and other national statistical agencies to increase the openness and availability of official statistics.
A: (from Tanya Sethi) – NGOs and civil society should be prolific users of NSO-produced data and highlight gaps in these datasets to put pressure on NSOs and the government to improve the timeliness and accuracy of these datasets. For this, they should work with other NGOs, as putting forward demands as a coalition is likely to have a greater impact than going it alone. Since civil society collects a lot of very useful and local/disaggregated data, they can work with local and national governments to see how this “unofficial” data can fill some of the gaps that exist in official data sources.
Q: What are some examples of ways data producers like NSOs should change their behavior from analytics or other information about their users (from analytics or other sources)?
A: (from Eric Swanson) – Here are a couple of suggestions: 1) Use surveys or other forms of user feedback to identify data that users want but cannot find; 2) Monitor patterns of page visits to gauge user response to new releases or to changes in the presentation of data on their websites and reward successful innovations by agency staff.
A: (from Tanya Sethi) – Note that “users” itself is a very broad term, and NSOs will need to think about which users — users in the government, users in CSOs/NGOs, users in donor organizations etc. Once they identify the group of users NSOs whose views they would most like to know, they could use web analytics or user surveys to (a) determine exactly what datasets these users want and (b) what barriers they face with respect to accessing and using that data (e.g., is the relevant documentation missing or insufficient? is the dataset available to download?) They should then use these insights to make the desired improvements thereby increasing the value of that data.
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