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2016 AAUDE
- 1. Data-Driven Solutions toSupport Your Research Enterprise Ann Beynon THOMSON REUTERS Simon Pratt UNIVERSITY OF TORONTO AAUDE conference April 2016
- 2. THE WEB OFSCIENCE CORE COLLECTION- OUR FOUNDATION FOR ANALYTICS • High-quality, peer-reviewed content; independent, unbiased selection • 61 million records: the largest and most consistent citation database, with 1 billion cited references, back to 1900, all searchable • Multidisciplinary: Journals (12,760), Conferences (161,000), and Books (70,000) indexed in the Sciences, Social Sciences, and Arts & Humanities • Comprehensive metadata due to our cover-to-cover indexing, all authors/addresses, funding acknowledgements, editorial policies and oversight • Used by 7,000+ institutions globally, including major research institutions, governments, international rankings…and all AAU universities and AAU administration • Emerging Sources Citation Index (new)
- 3. InCites- analyze and benchmarkyour research productivity and impact
- 4. INCITES-bibliometric analysis ofpeople, organizations, and funding agencies Users: • Institutional Research • Faculty Affairs • Library • Office of Research • Provost • President
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- 6. 5 INCITES BENCHMARKING ANDANALYTICS 5 Web of Science Core Collection data – normalized for analytics • Multidisciplinary content, indexed metadata, and true citation indexing • Science Citation Index Expanded, Social Science Citation Index, and Arts & Humanities Citation Index (12,760 high impact scholarly journals) • Conference Proceedings Citation Index • Book Citation Index • Normalized data and benchmarks updated bimonthly • Unified institutions (5,900 +); Unified funders (700) • 1980 to present • All document types (articles, reviews, editorials, book chapters, etc.) • Subject area schema for comparing: Web of Science, Essential Science Indicators and 8 regional schemes • Save to InCites – import Web of Science results sets of up to 50,000 records for analysis!
- 7. InCites: Normalized citationdata 6 Busine ss Oncology Substance Abuse Respiratory System Biolog yLaw Agronomy CATEGORY citation patterns differ by subject category e.g. nanotechnology vs law Review Article Editorial DOCUMENT TYPE citations differ by document type within a journal e.g. reviews are generally more heavily cited than articles, and editorials, book reviews etc. may go uncited NORMALIZATION PUTS DATA INTO CONTEXT— IS AN ENTITY DOING BETTER OR WORSE THAN WOULD BE EXPECTED IN A JOURNAL OR CATEGORY? TIME citations accumulate over time and at different rates depending on article age and category e.g. new articles may accumulate citations quickly, older ones more slowly or not at all 2015 timescited 1990
- 8. Is 20 citationsgood or bad? Article Article Article Article Article Article Article Article Article Article Article Article Article Article Article also ORGANIZATIONS, COUNTRIES, RESEARCH AREAS NORMALIZED RATIO OF ACTUAL / EXPECTED CITATIONS EXPECTED NUMBER OF CITATIONS FOR ARTICLE SET* AVERAGE CALCULATED FROM SUM OF ALL DOCUMENTS IN THE SELECTED GROUP 20 2 32 5 0 189 2 1218 1 1 87 23 158 Total Cites in group 15 documents in group 10.5 Expected cites Article 12 Article 12 Total 10.5 Expected 1.14 Normalized 8 People 8 Total 10.5 Expected 0.76 Normalized *for journal/category, publication year, and document type
- 9. 8 INSTITUTIONAL BENCHMARKING • AAUtop ten • 2006-2015 • # Web of Science Core Collection documents
- 10. 9 INSTITUTIONAL BENCHMARKING • AAUtop ten • 2006-2015 • Document trend
- 11. 10 INSTITUTIONAL BENCHMARKING • AAUtop ten • 2006-2015 • Category normalized citation impact
- 12. 11 FACULTY EVALUATION ANDRECRUITMENT • University of Toronto authors • Use radar charts to compare multiple indicators
- 13. 12 COLLABORATION ANALYSIS • Universityof Toronto • Government and corporate collaborators • Ranked by # documents • Indicator shown is category normalized citation impact
- 14. 13 IMPACT OF FUNDEDRESEARCH • University of Toronto • Documents funded by NSERC • Ranked by % documents in top 1% of category • Web of Science categories
- 15. 14 IMPACT IN ATOPIC- GOLD NANOPARTICLES • AAU top 5 • Ranked by % hot papers (published in last two years; high citations in last two months)
- 16. Customized reports- support yourstrategic decisions with expert consultancy
- 17. CUSTOMIZED REPORTS • Compareyour research activity to peers • Identify topical strengths/weaknesses/opportunities/threats • Recommendations on improving rankings or meeting research goals
- 18. • How muchresearch is taking place and in what field(s) at my institution? • Where is this research being published? • What are the disciplinary strengths and opportunities in this body of research? • How does our publication output and impact compare against competitors? • Who most commonly funds this disciplinary research? CUSTOMIZED REPORTS- Bibliometric Performance Report Bibliometric overview of your university vs. select peers
- 19. CUSTOMIZED REPORTS- EmergingResearch Areas Report Topical analysis of your strengths/weaknesses/opportunities/threats • In what research areas do we have strengths, opportunities, weakness, or threats? • What are the emerging research areas relevant for my portfolio? What are the global trends in these areas? • Who at my institutions performs research in these areas? • Who is funding this research?
- 20. Tailored reports- Answer yourspecific questions and provide recommendations on improving rankings or meeting research goals GLOBAL INSTITUTIONAL PROFILES DATA Publication output share by year from US Top 20 Journals by Impact Factor BIBLIOMETRIC DATA
- 21. Converis- manage faculty dataand reporting efficiently
- 22. CONVERIS – afaculty information system Growing client base – 100+ globally
- 23. • Converis isdesigned for easy integration of existing data • Example of systems for integration: – Login servers (e.g. Shibboleth, LDAP, Kerberos, CAS, often with SSO) – HR systems (e.g. Resource Link, SAP-HR, PeopleSoft) – Finance systems (e.g. SAP, PeopleSoft, Agresso, Oracle, Raindance, MACH) – Student record systems (e.g. BANNER, PeopleSoft CS, SITS, Ladok, AIS) – Grants systems (e.g. Cayuse, Huron, Kuali, InfoEd, etc.) – Institutional repositories (e.g. DSpace, EPrints, Fedora, Digital Commons) – External publication databases (e.g. Web of Science, InCites, PubMed, Scopus, ORCID, etc.) – Build and maintain researcher profiles for research networking like VIVO, Harvard Profiles, Loki, etc. CONVERIS INTEGRATION OF EXISTING SYSTEMS
- 24. CONVERIS – AFACULTY ACTIVITY REPORTING SYSTEM Converis has a comprehensive data model, covering activities across all departments: You can also add your own activity types FACULTY ACTIVITIES Publication Type Type of Activity Type of Creative Work Type of Teaching Activity Type of Service Type of Project Annotation Award Artwork Advising Clinical Service Charity Funded Book Chapter Lecture Audio/Visual Work Continuing Education Clinical Trial Clinical Trial Confererence Proceeding Poster Musical Performance Graduate Editor/Reviewer Contract Research Journal Article Presentation Software Multimedia Mentoring Professional Societies Fellowship Journal Review Professional Membership Other Creative Work Professional Student Group Advising (NEA) Project Report Seminar Undergraduate Univ Committee (NIH) Project Thesis Speech (NSF) Project
- 25. We can addyour specific faculty review templates. Configure the approval workflow for your local faculty management needs. -promotion and tenure -annual review -sabbatical CONVERIS – A FACULTY ACTIVITY REPORTING SYSTEM
- 26. Data integration- integrate trustedWeb of Science and InCites data into university systems
- 27. 26 DATA INTEGRATION- viaAPIs or data delivery • Multidisciplinary • Cover-to-cover indexing • Funding acknowledgements • Citations back to 1900 • Unbiased selection • Normalized bibliometric indicators back to 1980 • Collaboration indicators
- 28. 27 DATA INTEGRATION- viaAPIs or data delivery Example: populating publication and citation data into a research portal (VIVO)
- 29. 28 DATA INTEGRATION- viaAPIs or data delivery Example: populating publication and citation data into an institutional repository http://hub.hku.hk/
- 30. University of TorontoCase Study Simon Pratt Director, Policy and Analysis
- 31. University of Toronto 30 We use bibliometric data in a variety of ways: – Reports to Executive Committee and Governing Council – Promoting our excellence – Grant support – Research Management
- 32. Reports to ExecutiveCommittee and Governing Council 31
- 33. Reports to ExecutiveCommittee and Governing Council 32
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- 36. 35 Top 30 Urban Regions ResearchPublications 2011-13 Research Publications, % Change 1996-1998 to 2011-13 Promote our excellence
- 37. Grant support 36 CanadaFirst Research Excellence Fund (CFREF-2) $900 million funds available (this round) U of T submission is on “Data Driven Solutions” (DDS) an initiative to transform the way data is applied to the most complex and urgent social, environmental, health and economic challenges.
- 38. Grant support 37 Searchedthe Web of Science using a set of keywords related to DDS – Vetted and refined with input from academics in the field Exported the results to InCites for analysis – Identified collaborating countries and institutions – Created trend benchmarks to predict future performance
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- 40. Grant support 39 Identified400 scholars across the university with expertise in the field. – Many faculty/departments represented – Multidisciplinary – Created “bio-sketches” of each, with some bibliometric data included (h-index).
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- 42. Research Management TheUniversity of Toronto is a very large university and the individual faculty have a high degree of autonomy. The Faculty of Medicine maintains a variety of resources to assist researchers secure funding One of the biggest challenges is maintaining accurate lists of publications and integrating those lists with the Canadian Common CV 41
- 43. Research Management Historically,the Faculty of Medicine has done a huge amount of work to manually clean the data and to feed the cleaned data back to Thomson Reuters for integration with InCites However, we are currently implementing Converis as our research information system which will automate many of these processes and link with external resources. 42
- 44. Data-Driven Solutions toSupport Your Research Enterprise [email protected] Visit our table for a complimentary research report on your university Visit our website: http://stateofinnovation.thomsonreuters.com/