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Kyeongan Kwon - PhD Dissertation 2016

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Abstract

In this dissertation, I have developed scalable data visualization methods to depict a scholar's accomplishments at a glance. The evaluation of scholarly achievements in academia is largely based on the researcher's publication record. This record is communicated in exhaustive detail in the researcher's curriculum vitae (CV) or in summary via her/his h-index. The h-index, although a convenient abstraction, does not consider neither the time of the publication nor the impact factor (IF) of the journal where it appeared. I present a novel method that visually complements the h-index, revealing at a glance the nature of a researcher's scholastic record. This method (which includes the visualizations Scholar Plot and Academic Garden) is particularly appropriate for web interfaces, as it produces information that is compact and simple, yet highly illuminating.

Scholar Plot uses Google Scholar, Impact Factor, and NSF/NIH/NASA funding data to create a temporal representation of a researcher's publication/funding record that blends publication prestige with paper popularity and funding information. Scholar Plot affords an insightful appraisal of academics at one's fingertips. Academic Garden applies to individual academics, departments, colleges, and any other academic group thereof, such as a research lab or a project team. Academic Garden uses the flower metaphor to visually articulate performance of academic entities. The width of the flower's stem is commensurate to the academic funding the entity received (`juice conduit'). The height of the flower's stem is commensurate to the impact of the entity's intellectual products (`visibility'). The diameter of the flower's disc is commensurate to the prestige of the venues where these products appeared (`fancy factor'). Scholar Plot and Academic Garden bring clarity, transparency, and fairness in hiring, promotion, tenure, and funding decisions.

For the validation of the Academic Garden, I ran data analysis using Endowed Chaired Faculty, a prestigious honor in the United States, for the top 10 universities according to the US News Report 2015. The analysis demonstrated that chaired faculty can be predicted using the 3 merit criteria of citations, impact factor, and funding.

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Kyeongan Kwon - PhD Dissertation 2016

  1. 1. … 30, 40, 50 ... pages
  2. 2. + Free; inclusive - Publications only; little visualization + Publications; funding - Requires extensive set-up Missing about 2,000 citations, 16 h-index
  3. 3. Article Author Year Conclusion “Visualization of the citation impact environments of scientific journals” Journal of the American Society for Information Science andTechnology L Leydesdorff 2007 Effort focused on visualizing citation patterns using a journal data set “Augmenting the exploration of digital libraries with web-based visualizations” IEEE Fourth International Conference on Digital Information Management (ICDIM 2009) P Bergstrom D Atkinson 2009 Exploring patterns in the literature using a static data set at CiteSeer “SciVal experts: A collaborative tool” Medical Reference Services Quarterly EVardell T Feddern-Bekcan M Moore 2011 Summary of researchers’ profiles using Scopus “Scholarometer: A system for crowdsourcing scholarly impact metrics” Proceedings of the 2014 ACM Conference onWeb Science (WebSci 2014) J Kaur M JafariAsbagh F Radicchi F Menczer 2014 Citation analysis using Google Scholar, but no Impact Factor and no funding information
  4. 4. 1 3 2
  5. 5. A. Google Scholar Profile B. CurriculumVitae C. Scholar Plot
  6. 6. Histogram of IF IF Frequency 0 10 20 30 40 50 0100030005000 IFs Journals #1 <= 2 5554 #2 2 - 4 1948 #3 4 - 16 808 #4 16 >= 62 * IF - Impact Factor IF Journals
  7. 7. A
  8. 8. B
  9. 9. CBA
  10. 10. Prestige Impact Team
  11. 11. HTTP request: (jQuery, Ajax) HTTP response: (JSON) HTTP request: id = author name HTTP response: author details 1 Web Server (PHP 5.5) Client (Web browsers) 2 3 Database Server (MySQL 5.5) 6 Table Scholar authors, Impact Factor, NSF, NIH, etc. Table Table 7 Render in SVG (HTML5+CSS3, nvd3) 4 5 SQL Query Google Scholar Authors Impact Factor NSF, NIH, NASA Dynamic data – On Demand Yearly Update
  12. 12. I Pavlidis First Initial + Lastname
  13. 13. Daniel M. Smith Daniel Michael Smith M % Daniel Daniel M % Daniel Michael Daniel Michael Google Profile Funding
  14. 14. • 1.1 :The scheme should reveal causal relationships among merit criteria • Funding + pre-production credit + post-production credit • 1.2:The scheme should be scale invariant • Individual or Department or College (composite personhood)
  15. 15. • Scholar Plot is good for individuals • Not scalable to groups No!!!
  16. 16. • 1.1 :The scheme should reveal causal relationships among merit criteria • Funding + pre-production credit + post-production credit • 1.2:The scheme should be scale invariant • Individual or Department or College (composite personhood) • Scholar Plot is good for individuals • Not scalable to groups • Scholar Plot draws from Google Scholar,Thompson Reuters, and OpenGov • It is a public product working flawlessly! (ScholarPlot.com) • Scaling interface was still pending Work-in-progress  Done  Done  Done Work-in-progress
  17. 17. Impact Prestige Funding
  18. 18. Earth and Atmospheric Sciences PhysicsBiology and Biochemistry
  19. 19. Impact Prestige Funding College of ….. Citations
  20. 20. • Local – same department • Global – same discipline
  21. 21. • Local - same department • Global - same discipline
  22. 22. • Local – same department • Global – same discipline
  23. 23. • 1.1 :The scheme should reveal causal relationships among merit criteria • Funding + pre-production credit + post-production credit • 1.2:The scheme should be scale invariant • Individual or Department or College (composite personhood) • Scholar Plot is good for individuals • Not scalable to groups • Scholar Plot draws from Google Scholar,Thompson Reuters, and OpenGov • It is a public product working flawlessly! (ScholarPlot.com) • Scaling interface is still pending • Validates the design choice of the three criteria for the visualization  Done  Done  Done
  24. 24. Fall 2011 (1st year) Spring 2012 Fall 2012 (2nd year) Spring 2013 Fall 2013 (3rd year) Spring 2014 Fall 2014 (4th year) Spring 2015 Fall 2015 (5th year) Spring 2016 S Taamneh, M Dcosta, K Kwon and I Pavlidis "SubjectBook: Web- based Visualization Of Multimodal Affective Datasets", ACM Human Factors in Computing Systems, CHI 2016, San Jose, CA D Majeti, K Kwon, P Tsiamyrtzis and I Pavlidis "Dissecting Scholarly Patterns in Biology and Computer Science", The Science of Team Science, SciTS 2015, Bethesda, MD K Kwon, D Shastri and I Pavlidis "Information Visualization in Affective User Studies", The IEEE Visual Analytics Science and Technology, IEEE Information Visualization, and IEEE Scientific Visualization, VIS 2014, Paris, France K Kwon, D Shastri and I Pavlidis "Interfacing Information in Affective User Studies", The 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing, Ubicomp 2014, Seattle, WA T Feng, Z Liu, K Kwon, W Shi, B Carbunar, Y Jiang and N Nguyen, "Enhancing Mobile Security with Continuous Authentication Based on Touchscreen Gestures", The twelfth annual IEEE Conference on Technologies for Homeland Security, HST 2012, Waltham, MA J Lee, Z Liu, X Tian, D Woo, W Shi, D Boumber, Y Yan, and K Kwon, "Acceleration of Bulk Memory Operations in a Heterogeneous Multicore Architecture", 21st International Conference on Parallel Architectures and Compilation Techniques, PACT 2012, Minneapolis Conference Presentations K Kwon, "Design Principles: Information Visualization in User Studies", Proceedings of the 2015 US-Korea Conference on Science, Technology and Entrepreneurship, UKC 2015 Atlanta K Kwon, "Interfacing Information with Mixed Methods", Proceedings of the 2014 US-Korea Conferenceon Science, Technology and Entrepreneurship, UKC 2014 San Francisco, CA Activities / Membership 2012 PhD Student Association Officer 2014 Computer Science PhD Showcase 2014 Graduate Research and Scholarship Projects (GRaSP) 2015 Graduate Research and Scholarship Projects (GRaSP) 2016 Volunteering Judges M.S.Switched Lab Released Released
  25. 25. Scholar Plot

Abstract In this dissertation, I have developed scalable data visualization methods to depict a scholar's accomplishments at a glance. The evaluation of scholarly achievements in academia is largely based on the researcher's publication record. This record is communicated in exhaustive detail in the researcher's curriculum vitae (CV) or in summary via her/his h-index. The h-index, although a convenient abstraction, does not consider neither the time of the publication nor the impact factor (IF) of the journal where it appeared. I present a novel method that visually complements the h-index, revealing at a glance the nature of a researcher's scholastic record. This method (which includes the visualizations Scholar Plot and Academic Garden) is particularly appropriate for web interfaces, as it produces information that is compact and simple, yet highly illuminating. Scholar Plot uses Google Scholar, Impact Factor, and NSF/NIH/NASA funding data to create a temporal representation of a researcher's publication/funding record that blends publication prestige with paper popularity and funding information. Scholar Plot affords an insightful appraisal of academics at one's fingertips. Academic Garden applies to individual academics, departments, colleges, and any other academic group thereof, such as a research lab or a project team. Academic Garden uses the flower metaphor to visually articulate performance of academic entities. The width of the flower's stem is commensurate to the academic funding the entity received (`juice conduit'). The height of the flower's stem is commensurate to the impact of the entity's intellectual products (`visibility'). The diameter of the flower's disc is commensurate to the prestige of the venues where these products appeared (`fancy factor'). Scholar Plot and Academic Garden bring clarity, transparency, and fairness in hiring, promotion, tenure, and funding decisions. For the validation of the Academic Garden, I ran data analysis using Endowed Chaired Faculty, a prestigious honor in the United States, for the top 10 universities according to the US News Report 2015. The analysis demonstrated that chaired faculty can be predicted using the 3 merit criteria of citations, impact factor, and funding.

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