THOMSON REUTERS—GLOBAL INSTITUTIONAL PROFILES PROJECT DR. NAN MA SCIENCE AND SOLUTION CONSULTANT THOMSON REUTERS OCT 19 TH, 2010.

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Presentation transcript:

THOMSON REUTERS—GLOBAL INSTITUTIONAL PROFILES PROJECT DR. NAN MA SCIENCE AND SOLUTION CONSULTANT THOMSON REUTERS OCT 19 TH, 2010

INTRODUCTION & OVERVIEW The Global Institutional Profiles Project aims to capture a comprehensive picture of academic institutions around the globe The first use of this data is to inform the 2010 Times Higher Education World University Rankings. Access to the data will be available as a commercial service in 2011

About Times Higher Education The weekly magazine for all higher education professionals

TIMES HIGHER EDUCATION In November 2009, Times Higher Education (THE) announced: “We have signed an agreement with Thomson Reuters, the world’s leading research data specialist, to provide all the data for our annual World University Rankings from 2010 and beyond We have decided to end our relationship with QS, who will have no further involvement in Times Higher Education's annual World University Rankings.” Thomson Reuters will provide the data for the World University Rankings for 2010 and beyond

THOMSON REUTERS RESPONSE We are carefully listening to stakeholders in institutional evaluation and developing services based on their requirements Thomson Reuters do not produce a ranking We capture data from various sources and provide expert analysis and interpretation to that data. The biggest challenge is to make fair comparisons across international boundaries: –Information on a various aspects of performance –Subject specific data –Information that is valid, relevant and internationally comparable –Sensible use of proxies

THREE MAIN SOURCES OF DATA Profiles Project Institution submitted data Bibliometric data Academic reputation survey

PROFILES PROJECT – OPINION SURVEY, PLATFORM GROUP 7 We wanted to hear what stakeholders had to say about rankings and comparisons Opinion Survey to staff and researchers about university rankings –85% of respondents said that comparisons were either ‘extremely/very useful’ or ‘somewhat useful’ –Current data and methodology perceived unfavourably by many, widespread concern about data quality –Current analyses tend to favour English speaking nations “Platform Group” has provided feedback and sense checking on –Data to be collected –Development of the project –Evolving methodology Members include university heads, research strategy staff and academics

PROFILES PROJECT – OPINION SURVEY 8

PROFILES PROJECT – ACADEMIC REPUTATION SURVEY Asked academics around the world to give feedback on the reputation of academic institutions, with a clear distinction between the reputation for Research and Teaching –Produced with the help of a 3 rd party specialist –Invitation only to prevent manipulation of results –Structured sampling of invitations for regional and subject balance –Respondents rate reputation within their own area of expertise –Survey was translated into multiple languages to over come English language bias –Post survey analysis per country to overcome regional differences in response rate The survey completed in May 2010 with record levels of response

REPUTATION SURVEY RESULTS ANALYSIS 13,388 responses received –America38% –Africa 4% –Asia Pacific30% –Europe 28% Mixed function of respondents –Academic Staff69% –Research staff15% –Institutional leadership 7% –Graduate/post grad students 6%

PROFILES PROJECT – INSTITUTIONAL DATA GATHERING Collect factual data directly from the participating institutions Institutions provide detailed information about their activities across multiple subject areas Thomson Reuters has made considerable efforts to collect high quality, comparable data with a minimum work burden for the participating institutions. –Use existing data sources when available –Common data definitions for all institutions –Worked with external advisors to fine tune the definitions and make them comparable across international boundaries –Utilizing existing international standards for statistical reporting of education and research (UNESCO & OECD) –Strong support structure, documentation, webinars etc.

PROFILES PROJECT – DATA VALIDATION Data needs to be validated to make sure it is accurate and complete. –Cross-check with publicly available data sources –Logical data check –“Reality” check – identifying outliers and anomalies Because this is a new project, there are no prior data collections to make comparisons

PROFILES PROJECT – INSTITUTIONAL DATA GATHERING We collect information on the institution’s publication activity including the number of articles and citations. –Our data source is the Web of Science, widely recognised as the gold standard for research evaluation –Performed a detailed name unification process conforming to common guidelines for inclusion and exclusion of affiliated institutions. We normalised the data to overcome differences in the citation behaviour of different subjects

PROFILES PROJECT – DATA INTERPRETATION Data, where possible is normalized to create comparability across different fields of study. For example citation impact. However, we recognize that there are also differences in other aspects, such as funding. –We did not collect enough subject specific data this year to normalize for differences in funding and other areas. –We are focusing our efforts to collect this data in more detail. We also used Purchasing Power Parity to modify for differences in costs globally. We used other regional modifications to overcome regional trends

World University Ranking – methodology

PROFILES The World University Ranking only provide a limited analysis of the universities performance Thomson Reuters Profiles create an informative picture of the university as a whole Also provide an in-depth analysis and comparison of many different aspects of performance

SUMMARY The Profiles Project has made an excellent start at capturing relevant information for international comparisons of academic institutions Hundreds of participating institutions Quality data that is internationally comparable Single subject classification across multiple data types Expert interpretation and analysis We look forward to working with the community for incremental improvements.

THANK YOU To find out more: