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Scholarly Metrics Recommendations for Research Libraries: Deciphering the Trees in the Forest Table of Contents

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Scholarly Metrics Recommendations for Research Libraries: Deciphering the Trees in the Forest Table of Contents EUROPE’S RESEARCH LIBRARY NETWORK Scholarly Metrics Recommendations for Research Libraries: Deciphering the Trees in the Forest Table of Contents 01 3D. Learn About Platforms Before Implementing Them In Services & 15 INTRODUCTION 03 Homogenize Different Sources ABOUT LIBER 3E. Work With Researchers To Build Awareness Of Benefits But Educate 16 1. DISCOVERY & DISCOVERABILITY 05 About Weaknesses of Scholarly Metrics 1A. Provide Contextual Information To Allow the Discovery of Related 05 3F. Expand Your Perspective When Developing Services; Avoid Single- 17 Work & Users Purpose Approaches 1B. Exploit Rich Network Structures & Implement Bibliometric Methods To 07 3G. Teach Colleagues New Skills & Library Goals & Services 17 Enable Discovery 1C. Encourage Sharing Of Library Collections Under Open Licenses 08 4. RESEARCH ASSESSMENT 19 4A. Establish Appropriate Goals for Assessment Exercises Before Selecting 19 2. SHOWCASING ACHIEVEMENTS 09 Databases & Metrics; Be Transparent About Use & Interpretation 2A. Incentivize Researchers To Share Scholarly Works, Promote Achievements 09 4B. Use Different Data Sources to Include Various Scholarly Works & 20 Online & Engage With Audiences Disciplinary Communication & Publication Cultures 2B. Encourage Researchers To Showcase Scientific Contributions & Monitor 11 4C. Rely on Objective, Independent & Commonly-Accepted Data Sources 21 Impact To Provide Sound & Transparent Scholarly Metrics 4D. Avoid Using Composite Indicators & Conflating Different Aspects 21 3. SERVICE DEVELOPMENT 13 Of Scholarly Works & Impact; Don’t Lose The Multifaceted Nature of 3A. Join Forces With Stakeholders To Provide Services Reusing Existing 13 Metrics & Distort Interpretation Resources, Tools, Methods & Data 3B. Value Various Levels of Engagement; Favour Standardized, Well-Established 15 23 CONCLUSION & CALL FOR ACTION Practices & Easy-To-Use Tools 25 REFERENCES 3C. Make Full Use Of Open Data Sources; Sustain Not-For-Profit Enterprises 15 27 CREDITS With Open Business Models; Openly Share Data, Tools & Services OPEN SCHOLARLY The recommendations in this report are METRICS INTRODUCTION organised into three levels: z Initial Steps (circular bullet) Open scholarly metrics are output Intermediate Steps (square bullet) and impact indicators whose data S Advanced Steps (triangular bullet) are open. We use ‘open’ in the sense of the Open Definition3 and we Which recommendations a library adopts apply it to data, metrics, indicators, will depend on their current level of methods, software, and services. In engagement with scholarly metrics. addition, open data should follow the FAIR Principles.4 The order in which the recommendations appear are in correlation with the potential When talking about data we mean importance they can have for an (bibliographic) metadata, data institution. related to scholarly outputs (e.g., The digital era is bringing new and exciting The recommendations are grouped into number of published articles), data changes to scholarly communication. four sections: These two indications of use were devel- related to the impact of scholarly Modern scientific libraries and information oped during the Working Group’s works (e.g., number of citations), infrastructures are obliged to face these 1. Discovery and Discoverability workshop during LIBER’s 2017 Annual and qualitative information challenges in a professional way, and 2. Showcasing Achievements Conference. They are there to assist in pri- about engagement with scholarly sooner rather than later. 3. Service Development oritizing, but are not mandatory to follow works and other stakeholders 4. Research Assessment and are not dependent on each other. of the research enterprise (e.g., The monitoring and execution of policies, demographic information about the facilitation of Open Access publishing, Each section covers a set of activities, and users tweeting a scientific article and support for research data manage- makes suggestions for libraries which want and the tweet containing the DOI to ment are but a few examples of adaptation to promote the transparent, standardized the article). to the digital era. The use of scholarly met- and responsible use of scholarly metrics. rics1 is also an emerging field for academic Open should be the default way libraries, brought on by digital change. As part of LIBER’s focus on Open Science, of providing scholarly metrics and the Working Group has placed a special of developing services and tools. To foster this vision, LIBER’s Innovative emphasis on recommendations addressing Where openness is not possible (e.g., Metrics Working Group2 has set out rec- open scholarly metrics. 1 Following Haustein (2016, p. 416) we define scholarly because of third party restrictions), ommendations on how academic libraries metrics as “indicators based on recorded events of acts transparency should be aimed for. (e.g., viewing, reading, saving, diffusing, mentioning, citing, and information infrastructures can deal reusing, modifying) related to scholarly documents (e.g., with scholarly metrics, and how to get papers, books, blog posts, datasets, code) or scholarly started with the development of services agents (e.g., researchers, universities, funders, journals)”. to support this. Concepts such as altmetrics or bibliometrics are subsumed under this definition. 2 https://libereurope.eu/strategy/innovative-scholarly- communication/metrics 3 https://opendefinition.org 4 https://www.force11.org/group/fairgroup/fairprinciples 1 2 OUR NETWORK About LIBER libraries are at the heart of our net- Anyone working in a LIBER library is invited work. Staff from these libraries directly both to follow the progress of these groups LIBER influence LIBER’s work by serving on our and to get involved. Participating in a Executive Board, Steering Committees and Working Group is a wonderful way to ex- LIBER (Ligue des Bibliothèques Européennes By 2022, we envision a world where: Working Groups. change experiences and challenges with de Recherche – Association of European Re- your professional peers, while at the same search Libraries) represents 430 university, • Open Access is the predominant form of The Innovative Metrics group which pro- time making a valuable contribution to the national and special libraries in 40 countries, publishing; duced this document is one of nine current wider research library community. making us Europe’s largest research library • Research Data is Findable, Accessible, LIBER Working Groups. The activities network. Interoperable and Reusable (FAIR); undertaken by each group are varied but To learn more about participating, simply • Digital Skills underpin a more open they share one common aim: to advance contact the chair of the group which you Our 2018-2022 Strategy, Powering Sus- and transparent research life cycle; Open Science. would like to join. Contact details are avail- tainable Knowledge in the Digital Age, • Research Infrastructure is participatory, able on LIBER’s website. outlines how libraries can prepare them- tailored and scaled to the needs of the selves for coming changes in the research diverse disciplines; www.libereurope.eu landscape. It is based on three key focus • The cultural heritage of tomorrow is built areas: Innovative Scholarly Publishing, on today’s digital information. Digital Skills and Services, and Research Infrastructures. 3 4 FIVE PRINCIPLES FOROpen OPENKnowledge ACCESS Maps.20 The list is information about their users that expanding as you read. add to the understanding of who is Discovery & z NEGOTIATIONSReveal the relations between WITH concerned with research results. 1. PUBLISHERSscholarly works by using ranking Depending on the user base usage Discoverability functionalities (by year, times cited, information can reflect societal h-index, journal impact factor, usage, impact of scholarly works, Scholarly metrics can be used to discover scholarly works and researchers, and to highlight or other metrics or formal metadata). institutions, disciplines, and ways of increasing their discoverability. Context, such as reader demographics, helps when S Visualize knowledge flows via researchers. Readership and evaluating scholarly works. Context can also aid stakeholders of the scientific enterprise, for citation networks (where does attention metrics can be found in example, to address the right target group in articles or to find the right publication outlet for knowledge come from, i.e. reference services like Altmetric, PlumX the topic. Metadata and scholarly metrics are rich sources for the provision of context on works, list, where does it go, i.e. citations). Metrics and Kudos.25 publication venues, institutions and individuals. Moreover, scholarly metrics support knowledge Use tools like VOSViewer,21 Gephi22 Solicit platforms to focus after discovery. They can lead to the finding of information not explicitly mentioned in the dataset, or CitNetExplorer23 to create maps publication and where to engage in such as influential authors in a scientific field. Re-using methods in studies of scholarly metrics of science through citation networks discussions by exploring mentions on can open new search opportunities and help library patrons — researchers, students and uni- and enhance them with information social platforms. This context also versity administrators — to become acquainted with these methods. from scholarly metrics just like Open provides authors of scholarly works Knowledge Maps do. with the full view of the scholarly Reveal collaboration patterns (e.g., debate around
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