Ce diaporama a bien été signalé.
Nous utilisons votre profil LinkedIn et vos données d’activité pour vous proposer des publicités personnalisées et pertinentes. Vous pouvez changer vos préférences de publicités à tout moment.

Using Bibliometrics to Keep Up with the Joneses

Presented at SLA MD's Nebulous Connections April 2017. Discusses techniques for doing environmental scans and mapping a technology landscape

  • Identifiez-vous pour voir les commentaires

Using Bibliometrics to Keep Up with the Joneses

  1. 1. Using Bibliometrics to Keep Up with the Joneses Christina K. Pikas, BS, MLS, PhD Johns Hopkins University Applied Physics Laboratory Nebulous Connections, April 4, 2017
  2. 2. How do you know what’s going on in the world?
  3. 3. How do you understand a technology landscape outside your own?
  4. 4. You could interview lots of people, make site visits, and/or … use bibliometrics!wocintechchat.com
  5. 5. Agenda ◎Questions to answer ◎General approach ◎Tips and techniques ◎Verification & validation
  6. 6. 1. Questions to Answer
  7. 7. Given a topic What is the volume of work and how is it trending? What are the top venues? Where is the work being done? Countries? Organizations?
  8. 8. Who funds this work? What methods, models, etc. are used? How is this field related to other fields? Who are the top researchers/ groups? How well connected are they?
  9. 9. Given an organization Over what distribution of topics do they publish? With whom do they collaborate? Who funds their work? How well cited is their work? Is it taught in schools? Does it have clinical applications?
  10. 10. Are there clinical or practical implications/spin-offs/products? Are there regulatory or policy implications? Is the work discussed in the news? By Congress?
  11. 11. 2. General Approach
  12. 12. Define topic Search CleanAnalyze Report
  13. 13. Define Topic ◎Not too big, not too small ◎Best to do this with the end user of the report ◎Work iteratively with a subject matter expert if possible ◎Reference interview!
  14. 14. Search ◎Citation databases BUT ALSO ◎Domain databases with high quality metadata ◎Technical report servers ◎Google Scholar, Microsoft Academic ◎Funding databases (NSF, Reporter, URED if you are DoD) Document your searches as you go!
  15. 15. Clean
  16. 16. Validity & Reliability ◎Count all the things ◎Associate correct terms ◎Show accurate trends Tool Selection ◎Correct input for the tool ◎Be able to answer the desired question with the tool ◎Merge multiple sources Note: This slide is from Monday’s talk about data preparation
  17. 17. Analyze Relevant to the questions you are answering, not what your favorite tool can do 
  18. 18. Report ◎Sometimes tables are better than visualizations ◎Include narrative with results ◎Take time to include a backup section with a clear description of what methods you used and searches you performed
  19. 19. 3. Tips & Techniques
  20. 20. Geography Geocoding correspondence address is actually doable! Sci2 and R are two paths.
  21. 21. Done with R
  22. 22. VantagePoint ($)
  23. 23. Text ◎VOS viewer does co-word graphing using the abstract – free! ◎Can do in Gephi, but need to do pre- processing elsewhere ◎R Remember to remove copyright statements from abstracts first to avoid publisher names being your top result!
  24. 24. PNNL In-Spire (free to US Government & contractors)
  25. 25. PNNL In-Spire (free to US Government & contractors)
  26. 26. Networks Co-authorship Nodes as: authors, groups, organizations, countries Citation Citing/Cited, co-citation, bibliographic coupling Funder – Researcher Supplier – Builder Co-word, semantic, topic, etc. Gephi, Pajek, VOS viewer, Sci2, CitNetExplorer And more…
  27. 27. A.Q. Rogers et al. (2015) You get what you pay for: examining the true cost of delivering utility with small satellites. 31st Space Symposium. Colorado Springs, CO Done in R
  28. 28. Patent network with 1528 patents. Colored by clusters. Sized by degree. Labeled by clusters. Done in Quid ($$$) Data Cleaning Enterprise Resource Planning Data Acquisition Data Integration & Transmission Image & Visual Data Vehicle Data Signal Processing Printing Applications Data Cleansing (records) Power Grid Applications Multi-Dimensional Data Multi-Media Data Data Production & Metadata Equipment Control Mobile Devices Test Data Integration Data Enrichment Sensor Networks Electronic Payments Sewing and Embroidery Data Integration Management Data Preparation Assistance Medical Applications Data Integration (business processes) Mask Data Preparation (electronics manufacturing)
  29. 29. VantagePoint ($$)
  30. 30. 4. Verification & Validation
  31. 31. Sounds more official than it probably is! ◎ Check with subject matter experts: ○ What is missing? ○ Does anything look amiss? ◎ For results, check for competing hypotheses ◎ Put it in to Google ◎ Re-check for citing articles (recent or other) ◎ Carefully review all visualizations for weirdness
  32. 32. Conclusions
  33. 33. ◎Bibliometrics can provide a useful tool for looking at a research landscape ◎Best done iteratively with subject matter experts ◎Librarians can provide this service best because of the searching and analyses required ◎Be sure to not overstate results!
  34. 34. Questions? You can find me at: @cpikas Christina.Pikas@jhuapl.edu https://www.slideshare.net/cpikas http://christinaslisrant.scientopia.org/
  35. 35. Credits Special thanks to all the people who made and released these awesome resources for free: ◎ Presentation template by SlidesCarnival ◎ Photographs by Unsplash & Death to the Stock Photo (license)

×