Elsevier’s SciVal Suite - Scopus Literature Database  - SciVal Experts - SciVal Funding - SciVal Spotlight
Scopus Literature Database
Indexes more than 19,500 titles Database of 46 million records “ Articles-in-Press” from over 3,850 journals Accesible by UMN affiliates Trial currently active:  http://www.scopus.com/home.url Scopus Literature Database
Scopus Coverage by Discipline Data:  9,300  vs   1 7 ,300 Ti tles Physical, Chemical  and Earth Sciences Humanities &  creative arts Engineering & environmental   Sciences Social,  Behavioural &  Economic Sciences Mathematics, Information   & Communication Sciences  Biological  Sciences and Biotechnology Biomedical & Clinical Research  Public and Allied  Health and Health Services Nearest Competitor Scopus 0 2500 5000
Profile of Herman S. Cheung taken from the University of Miami’s SciVal Experts instance. SciVal Experts @ the U of MN Similar Experts: Displays similar scholars from the same institution. The scholars’ names are provided by the institution. Subject area matching is done by the SciVal Experts’ system. Publications/Journals:  These lists are built from the Scopus citation database.  “Fingerprinting” technology is employed to ensure the match between scholar name and publication titles is accurate.  Networks: Lists both internal departments/organizations, and external institutions that are connected to this expert. Also displays scholars who have coauthored articles (regardless of affiliation). Directory Entry: Names of scholars, along with their affiliations, and contact information are supplied by the institution. At the University of Minnesota, this information will be supplied from the UMN Data Warehouse. Photos will not be included or sent to Elsevier. Trends/Research Network: Graphical displays of the research concepts and coauthors/collaborators that have been most significantly present over this researcher's career. Grants/Patents: Lists funded research that has been awarded to this scholar. Data is both supplied by the institution and harvested from public sources.  Patent awards can also be displayed here.
A  Public  Profile includes: Demographics: Name, Titles, Contact Info,  Affiliations (Departments, Colleges) Publications (pulled automatically from Scopus) Research networks (i.e, co-authors, co-workers, institutions of co-authors, etc.) Potential to include UMN supplied data for: grant awards; patent awards; & courses taught. Graphical displays: research trends & networks SciVal Experts @ the U of MN
1.  Automatic Review Algorithm using identifying elements determines clusters: Name Location Co-Authors Key Concepts Journals more… 2.  Manual Review Human QA team builds profiles, reviews results quarterly SciVal Experts: Disambiguating Results J. Smith
Aggregating individual fingerprints across organizational units allows for the organization to know what individuals know  and  what groups know together… What new publications and grants have been produced? What trends have emerged over time? Who is working together?  With what other organizations (internal and external) are we collaborating? What do we know? Aggregated Fingerprints SciVal Experts: Aggregating Fingerprints
Under Consideration: All UMN - TC Faculty (those with a “Primary” faculty job code) UMN TC Administrators w/ tenure, or on the tenure track Post-Docs Coordinate Campuses – dependent on contributions SciVal Experts: Who will be included?
Arizona State University http://www.experts.scival.com/asu/default.asp   University of Michigan: http://www.experts.scival.com/umichigan/ University of North Carolina at Chapel Hill and North Carolina State University http://www.experts.scival.com/reachnc/ SciVal Experts -
SciVal Funding – Sources Included Category Description Sources Examples Government All federal grant-making institutions and selected state or other (local) government agencies 650+ National Institutes of Health National Science Foundation Canadian Institute of Health Research Department of Health (UK) Private All private foundations providing research funding, either corporate, family or other type of philanthropic giving 2800+ Bill & Melinda Gates Foundation Cystic Fibrosis Canada Cancer Research UK Corporate Corporations providing research grants and contracts [1]. 380+ DuPont Alberta Innovates - Health Solutions Rolls-Royce Other International, non-governmental organization (NGO), etc. 540+ United Nations Global Fund to Fight AIDS, Tuberculosis and Malaria British Academy
SciVal Funding – Search & Browse
SciVal Funding – Integrated with Experts
 
SciVal Funding – Customize Results
Produces unique graphical views of an institution’s research performance from an interdisciplinary perspective Results can be compared with those of top competing institutions Assists in identifying potential new hires for specific research areas SciVal Spotlight
SciVal Spotlight – Circle Map
SciVal Spotlight – Matrix View
SciVal Spotlight – Details View
Contacts for questions or more information: Kate McCready, University Libraries – SciVal Project Manager [email_address] , 6-4357 Layne Johnson, University Libraries/Health Informatics – UMN Profiles  [email_address] , 5-8673 Tom Hays, College of Biological Sciences  [email_address] , 6.2949 Scopus & SciVal Suite

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UMN Scopus & SciVal Meeting 12-1-11

  • 1. Elsevier’s SciVal Suite - Scopus Literature Database - SciVal Experts - SciVal Funding - SciVal Spotlight
  • 3. Indexes more than 19,500 titles Database of 46 million records “ Articles-in-Press” from over 3,850 journals Accesible by UMN affiliates Trial currently active: http://www.scopus.com/home.url Scopus Literature Database
  • 4. Scopus Coverage by Discipline Data: 9,300 vs 1 7 ,300 Ti tles Physical, Chemical and Earth Sciences Humanities & creative arts Engineering & environmental Sciences Social, Behavioural & Economic Sciences Mathematics, Information & Communication Sciences Biological Sciences and Biotechnology Biomedical & Clinical Research Public and Allied Health and Health Services Nearest Competitor Scopus 0 2500 5000
  • 5. Profile of Herman S. Cheung taken from the University of Miami’s SciVal Experts instance. SciVal Experts @ the U of MN Similar Experts: Displays similar scholars from the same institution. The scholars’ names are provided by the institution. Subject area matching is done by the SciVal Experts’ system. Publications/Journals: These lists are built from the Scopus citation database. “Fingerprinting” technology is employed to ensure the match between scholar name and publication titles is accurate. Networks: Lists both internal departments/organizations, and external institutions that are connected to this expert. Also displays scholars who have coauthored articles (regardless of affiliation). Directory Entry: Names of scholars, along with their affiliations, and contact information are supplied by the institution. At the University of Minnesota, this information will be supplied from the UMN Data Warehouse. Photos will not be included or sent to Elsevier. Trends/Research Network: Graphical displays of the research concepts and coauthors/collaborators that have been most significantly present over this researcher's career. Grants/Patents: Lists funded research that has been awarded to this scholar. Data is both supplied by the institution and harvested from public sources. Patent awards can also be displayed here.
  • 6. A Public Profile includes: Demographics: Name, Titles, Contact Info, Affiliations (Departments, Colleges) Publications (pulled automatically from Scopus) Research networks (i.e, co-authors, co-workers, institutions of co-authors, etc.) Potential to include UMN supplied data for: grant awards; patent awards; & courses taught. Graphical displays: research trends & networks SciVal Experts @ the U of MN
  • 7. 1. Automatic Review Algorithm using identifying elements determines clusters: Name Location Co-Authors Key Concepts Journals more… 2. Manual Review Human QA team builds profiles, reviews results quarterly SciVal Experts: Disambiguating Results J. Smith
  • 8. Aggregating individual fingerprints across organizational units allows for the organization to know what individuals know and what groups know together… What new publications and grants have been produced? What trends have emerged over time? Who is working together? With what other organizations (internal and external) are we collaborating? What do we know? Aggregated Fingerprints SciVal Experts: Aggregating Fingerprints
  • 9. Under Consideration: All UMN - TC Faculty (those with a “Primary” faculty job code) UMN TC Administrators w/ tenure, or on the tenure track Post-Docs Coordinate Campuses – dependent on contributions SciVal Experts: Who will be included?
  • 10. Arizona State University http://www.experts.scival.com/asu/default.asp University of Michigan: http://www.experts.scival.com/umichigan/ University of North Carolina at Chapel Hill and North Carolina State University http://www.experts.scival.com/reachnc/ SciVal Experts -
  • 11. SciVal Funding – Sources Included Category Description Sources Examples Government All federal grant-making institutions and selected state or other (local) government agencies 650+ National Institutes of Health National Science Foundation Canadian Institute of Health Research Department of Health (UK) Private All private foundations providing research funding, either corporate, family or other type of philanthropic giving 2800+ Bill & Melinda Gates Foundation Cystic Fibrosis Canada Cancer Research UK Corporate Corporations providing research grants and contracts [1]. 380+ DuPont Alberta Innovates - Health Solutions Rolls-Royce Other International, non-governmental organization (NGO), etc. 540+ United Nations Global Fund to Fight AIDS, Tuberculosis and Malaria British Academy
  • 12. SciVal Funding – Search & Browse
  • 13. SciVal Funding – Integrated with Experts
  • 14.  
  • 15. SciVal Funding – Customize Results
  • 16. Produces unique graphical views of an institution’s research performance from an interdisciplinary perspective Results can be compared with those of top competing institutions Assists in identifying potential new hires for specific research areas SciVal Spotlight
  • 17. SciVal Spotlight – Circle Map
  • 18. SciVal Spotlight – Matrix View
  • 19. SciVal Spotlight – Details View
  • 20. Contacts for questions or more information: Kate McCready, University Libraries – SciVal Project Manager [email_address] , 6-4357 Layne Johnson, University Libraries/Health Informatics – UMN Profiles [email_address] , 5-8673 Tom Hays, College of Biological Sciences [email_address] , 6.2949 Scopus & SciVal Suite

Editor's Notes

  • #2: Decisions: The University of Minnesota is actively working on licensing and developing these products. The University Libraries are coordinating the contracts and implementation. OIT is dedicating resources to ensure data accuracy and currency. OHR, SPA, ASR, and the Office of Commercial Tech have all been engaged to provide data feeds to Elsevier.
  • #3: A huge database of publications. SciVerse Scopus at a glance July 2011: 18,500 peer-reviewed journals (including 1,800 Open Access journals). 425 trade publications. 325 book series. 250 conference proceedings. 25 million records with references back to 1996 (of which 78% include references). 21 million records pre-1996 which go back as far as 1823. 4.8 million conference papers from proceedings and journals. 375 million scientific web pages indexed via Scirus. 24.8 million patent records from five patent offices.
  • #4: SciVerse Scopus at a glance July 2011: 18,500 peer-reviewed journals (including 1,800 Open Access journals). 425 trade publications. 325 book series. 250 conference proceedings. 25 million records with references back to 1996 (of which 78% include references). 21 million records pre-1996 which go back as far as 1823. 4.8 million conference papers from proceedings and journals. 375 million scientific web pages indexed via Scirus. 24.8 million patent records from five patent offices.
  • #5: Source: Scopus content coverage analysis , Ove Kahler, April 2008 This is a disciplinary comparison of WoS and Scopus titles based on Scopus’ subject classification . The study was conducted based on the title list from 2007. The recent “regional” titles added by Thomson to WoS are not included in this analysis. Please be aware that a journal could belong to more than one subject category. Therefore, the sum of the number of titles in each of the bar chart will not add up to 17,300 but more. Adding 8,00 titles per year
  • #6: Public Profile
  • #7: Anyone, anywhere, can search the U of MN’s instance of SciVal Experts. It is a public view. The OVPR’s office and U Relations can point interested business partners & the media to this site to identify experts.
  • #8: In addition to the Fingerprint process, we also have to ensure the publications are associated to the correct authors, as institutions need reliable data in order to help drive their research strategy. We do this in two ways:   We disambiguate author names automatically via an algorithm. We use metadata like name, location, journal, topics they publish on, who they coauthor with, to automatically group the documents together as precisely as possible. Then we have a specialized QA team that manually reviews and verifies all of the information to ensure all of the publications are associated to the correct authors   This disambiguation process ensures the author profiles are accurate, comprehensive and current.
  • #9: We can then aggregate Fingerprints at the department, institute and research group level (across multiple locations). For example, we can aggregate the fingerprints of all the researchers in a department and develop a departmental fingerprint, which represents the content in all of the publications produced across the entire department.   This enables a customer to identify # of grants awarded to the dept, new publications produced by the dept, emerging trends within the dept, and who is working across the dept and the institution. Fingerprints help customers answer the question ‘what do we know as an organization?
  • #11: Used at many institutions
  • #12: Researchers can: Find the Right Funding Opportunities Easy one-stop access to funding opportunities Conduct key word and full text searches of funding database Search with the combine fingerprints of faculty in distinct disciplines to identify funding for projects at the interface of disciplines. Analyze the funding environment Examine award history- what is the performance of previously funded faculty; evaluation of opportunities and strategic planning for applications. Evaluate what research and researchers an agency prefers to fund by examining the researchers and publications linked to funding programs. Find collaborators and learn about potential competitors Maximize Award Chances Receive funding recommendations and alerts tailored to faculty fingerprints. Craft proposals based on knowledge of what previously funded research. Weigh the chances of success based on historic information. Enables VPRs, deans, and department heads to find and support researchers who are working together across disciplines to discover innovative solutions and problem-solving methods.
  • #13: Anyone affiliated with the University of Minnesota can access SciVal Funding directly. It is fully searchable and you can create alerts for opportunities directly within this tool.
  • #14: It is also integrated into SciVal Experts – it pushes information about opportunities to each seat holder.
  • #15: Both on their profile (visible only to the seat holder) and via email. A user can set his/her preferences for notifications.
  • #16: The integration between SciVal Funding and Experts is done by matching the “fingerprints”. But, a seat holder can alter the subject areas of the opportunities that are presented.
  • #17: Spotlight employs an analytical, co-citation methodology to identify areas of existing and emerging strengths. Spotlight informs resource allocation for “team” science, retention and recruitment strategies. Evaluate your institution’s output and standing relative to competition. Establish or adjust strategic directions of programs. Use spotlight to evaluate the relative leadership position of a research strength to understand the resources and development necessary to support it. Execute a strategy. Identify potential collaborators to strengthen a grant application and determine the top researchers to recruit and retain.
  • #18: Each circle represents an Emerging or Distinctive Competency for an institution or country. Competencies positioned towards the middle of the circle imply more interdisciplinary research. A larger competency indicates there are more global publications in this research area.
  • #19: Identify specific areas of research excellence and emerging strengths. Understand where you have been gaining or losing ground over time. Identify new leadership opportunities. Determine areas for further investment.
  • #20: Identify potential collaborators. Determine top researchers to recruit and retain.