An Introduction to Data Visualisation

1. An Introduction to Data Visualisation For Open Access advocacy Marieke Guy Marieke.guy@okfn.org An Introduction to Data Visualisation

2. PASTEUR4OA http://pasteur4oa.eu/ • PASTEUR4OA: Open Access Policy Alignment Strategies for European Union Research • EU-funded project 2014 – 2016 • Supports the development and/or reinforcement of open access strategies and policies at the national level and facilitate their coordination among all Member States • 15 partners across Europe • Key nodes - Europe-wide network of centres of expertise on open access and scholarly communication • EC’s policy for Open Access in Horizon 2020 is the foundation of the PASTEUR4OA advocacy work An Introduction to Data Visualisation

3. ROARMAP http://roarmap.eprints.org/ • ROARMAP: Registry of Open Access Repository Mandates and Policies • Searchable international registry charting the growth of open access mandates adopted by universities, research institutions and research funders • PASTEUR4OA work involved developing a new classification scheme for the registry • Project has also added almost 300 new policy entries to the ROARMAP database. On 24th August 2015 contains 725 policies. • Interesting data, wanted to show in interesting ways! An Introduction to Data Visualisation

4. WRITING A SPECIFICATION

5. Data Viz Brief http://pasteur4oa-dataviz.okfn.org/ • Exploit the ROARMAP database and create visuals to be produced for advocates to use in presentations, literature etc. • Develop ways to show the statistics in an attractive form, e.g.: • Maps (Europe, the world, individual continents) showing where policies are • Charts showing data such as funder type, what is mandatory, etc. • Create interactive online visualisations using data dumps • Use live data if possible • For policy makers, institutions, researchers, individuals An Introduction to Data Visualisation

6. Spec: Things to think about • What is the budget for the work? • How much time and resources are available for the work? • How will you get the data out of the system it is in? API, URL or other? • Where will you store the visualisations? • Where will you store the new data created? Will you release it openly? • How often will the data be updated? • Who can help you with your work? • What is genuinely do-able? An Introduction to Data Visualisation

7. From Tableau An Introduction to Data Visualisation

8. DECIDE EARLY ON THE QUESTIONS YOU WANT TO ANSWER

9. TALK TO EXPERTS AND SEE WHAT THEY THINK

10. CHOOSING DATASETS

11. Open Access Policies by country – shows the top 10 countries From Infogram An Introduction to Data Visualisation

12. Data Sets Used • ROARMAP data - http://roarmap.eprints.org/ • Open Access (OA) policy effectiveness study – collected by PASTEUR4OA Project • Bibliographic metadata indexed by the Thompson-Reuters database (WoK) - http://wokinfo.com/ • Publication date was estimated based on the Altmetrics database and WoK publication date - http://www.altmetric.com/ An Introduction to Data Visualisation

13. Data Sets: Things to think about • Is it a reputable source? • Is it openly available? • How up to date is the data? • Is the data easy to get out and work on? • Has the data been manipulated? • Are there omissions of data? • Will you need to combine data sets? • Do you need to add in other data e.g. country codes/names An Introduction to Data Visualisation

14. From Tableau 07/11/2019 An Introduction to Data Visualisation 14

15. MANIPULATING DATA

16. Useful Excel Functions • Sum – adding up • Count – the number of cells in a range that have numbers in them • Vlookup- lets you search for specific information in your spreadsheet • Concatenate – lets you combine text from different cells into one cell • Trim – removes extra spaces • Substitute – like replace but more versatile • Sheet/page layout – hide rows, filter data, lock columns etc. An Introduction to Data Visualisation

17. Data: Things to Think About • You do need to be able to use excel…well • Have you checked your data recently? • Have you saved versions of your data and labelled them well? • Are you keeping notes about what you are doing? • Are you being consistent with your data? • Make sure you document processes • Countries can be tricky – make sure you are clear and consistent An Introduction to Data Visualisation

18. REGULARLY CARRY OUT SANITY CHECKSON THE DATA

19. From Tableau An Introduction to Data Visualisation

20. CONTROL HOW YOUR SPREADSHEET IS LAID OUT- LESS IS MORE

21. LEARN EARLY ON HOW TO REPLACE YOUR DATA SETIN THE TOOL

22. SAVE REGULAR VERSIONSOF THE DATA

23. Open Access Policies Worldwide by Continent From Infogram An Introduction to Data Visualisation

24. CHOOSING TOOLS

25. Tools Used • Tableau Public: http://public.tableau.com/s/ • Open Refine: http://openrefine.org/ • Python Pandas: http://pandas.pydata.org/ • Many Eyes: http://www-01.ibm.com/software/analytics/many-eyes/ • CartoDB: https://cartodb.com/ • Raw: http://raw.densitydesign.org/ • Datawrapper: https://datawrapper.de/ • Infogram: https://infogr.am • Easel.ly: http://www.easel.ly/ • Piktochart: http://piktochart.com/ http://selection.datavisualization.ch/ An Introduction to Data Visualisation

26. PLAY WITH LOTS OF TOOLS AND THEN COMMIT TO ONE OR TWO

27. HAVING SEVERAL MACHINES TO USE CAN BE USEFUL

28. From Tableau An Introduction to Data Visualisation

29. Tools: Things to Think About • Does it cost to use? • What is the licence? • Do you have the correct OS? • Can you get the visualisation out of the tool? • Can you link to live data? • Can you embed it? • Can you make a graphic of it? • Can you download it? • Does the tool expect you to be able to programme? An Introduction to Data Visualisation

30. DELIVERING DATA VISUALISATIONS

31. Delivery: Things to Think About • Does it cost to use? • What are the infographics going to be used for? • What format should they be in? • Is there a colour theme? What colours look good? • Can you create a custom palette • Can you distinguish between different parts of the chart? • Is it clear what question the visualisation is answering? • Is there enough information on the data visualisation? • Is there a heading, comment box, labels, annotation, legend etc.? • Is the result honest? Make sure you document where all the visualisations are An Introduction to Data Visualisation

32. WORKING ON LIVE DATAIS A WHOLE DIFFERENT BALLGAME

33. Live data From Google maps An Introduction to Data Visualisation

34. Useful Links • Data vizsite: http://pasteur4oa-dataviz.okfn.org/ • Githubsite: https://github.com/okfn/PASTEUR4OA-dataviz/ • Pad: https://pad.okfn.org/p/pasteur4oa-data-viz • My Tableau profile: https://public.tableau.com/profile/marieke.guy#!/ • My infogram profile: https://infogr.am/mariekeguy • Live ROARMAP data: http://bit.ly/1Ri7rjl • Data stored at: https://zenodo.org/deposit/36339/ • Seeing data : http://seeingdata.org/about-seeing-data/ An Introduction to Data Visualisation

35. Open Access Policies Worldwide by Continent From Infogram An Introduction to Data Visualisation

36. http://pasteur4oa-dataviz.okfn.org/

37. Thanks! Contact… Marieke Guy, Open Knowledge Marieke.guy@okfn.org www.pasteur4oa.eu An Introduction to Data Visualisation