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A Guide to the Dimensions Data Approach

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A Guide to the Dimensions Data Approach Dimensions Report A Guide to the Dimensions Data Approach A collaborative approach to creating a modern infrastructure for data describing research: where we are and where we want to take it Christian Bode, Christian Herzog, Daniel Hook & Robert McGrath APRIL 2019 About Dimensions Dimensions® is a modern and innovative, linked research data infrastructure and tool, re- imagining discovery and access to research: grants, publications, citations, clinical trials, patents and policy documents in one place. The development of Dimensions has been triggered by the feedback from clients and partners of the Digital Science portfolio companies. As a result, Dimensions has been developed through a dynamic collaboration across Digital Science and six of its portfolio businesses (ReadCube, Altmetric, Figshare, Symplectic, DS Consultancy and ÜberResearch). With each company focused on a different pain point within the research cycle and serving various stakeholders in the research ecosystem, these teams shared their true passion for innovation, and contribute their unique experiences, opinions, and values into Dimensions. Visit www.dimensions.ai About Digital Science Digital Science® is a technology company serving the needs of scientific and research communities at key points along the full cycle of research. We invest in, nurture and support innovative businesses and technologies that make all parts of the research process more open, efficient and effective. We believe that together, we can change research for good. Visit www.digital-science.com Acknowledgements We are grateful to all contributors and would like to thank our development team for their time and effort in extracting the data to support this report. This report has been published by Digital Science, which is owned by the Holtzbrinck Publishing Group.. For inquries in respect of Dimensions, please contact [email protected], otherwise please write to Digital Science at [email protected] or 625 Massachusetts Avenue, Cambridge, MA, 02139 USA. Copyright © 2018 Digital Science & Research Solutions Inc. DOI: 10.6084/m9.figshare.5783094 Contents 1. A modern linked research data landscape 2 2. Linking it all together and enriching it for the user 3 Full text index - enabling deep discovery 4 Machine learning based research topic classification - Fields of Research and other classification systems 4 Research categories in Dimensions - Australian and New Zealand Standard Research Classification (ANZSRC) 4 Other classification systems 5 Disambiguating institution names - based on GRID 6 Person disambiguation across publications, grants, patents and clinical trials - a challenging task 7 Citations, acknowledgements and adding context 7 3. Broadening the view beyond publications - bringing content together from as many places as possible 8 How does Dimensions compare to other databases like Google Scholar, Pubmed, Scopus or Web of Science? 8 Citation counts in different systems and databases - there is no single truth! 9 The current content scope and quality is just the starting point 10 4. Grants - a real glimpse into the future 11 Key statistics on the Dimensions grant data 12 5. Publications, books and citations 14 Dimensions and publications / citations - a database, not a judgement call 14 Quality related filters: whitelists and blacklists as tools for the user 15 Aggregating the Dimensions publication and citation data 15 Beyond academic attention - Altmetrics data in Dimensions 16 Open Access, Open Citation Data and Dimensions 17 Key statistics on the Dimensions publication and citation data 17 6. Clinical trials - research results en route to clinical application 19 Key statistics on the Dimensions clinical trial data 19 7. Patents - research resulting in practical and commercial applications 21 Key statistics on the Dimensions patent data 21 8. Policy documents - research resulting in policy and guidance documents 23 Key statistics on the Dimensions policy document data 23 Dimensions Report 1 A modern linked research data landscape The broader Dimensions was created in response to two significant constraints for Digital Science and its development partners. The first constraint was that existing Dimensions team: solutions sought to understand the research landscape solely through the lens 100+ development of publication and citation data. The second constraint was the way that existing partners and solutions exposed what data they did have. Much of the publications research graph had been locked away in proprietary applications, which constrained how Digital Science the information could be used, including through a lack of workable APIs. Where proprietary data existed, there were significant data holes, making the data less useful for core use cases. Making publication To address these constraints and to try to stimulate innovation to support research, we worked closely with more than 100 development partners and citation data (research organisations and funders) to realise an integrated database covering freely available the entire research process from funding to research, from publishing of results through attention, both scholarly and beyond, to commercial application and policy making - consistently linked in multiple dimensions. Empowering the At the heart of Dimensions, we wanted to do something transformative for research and that was always going to have multiple components. A key part research community of that vision was that Dimensions makes available, without charge, publication citation data via the Dimensions application (visit https://app.dimensions.ai) and via APIs - the metrics in Dimensions are available via the open Dimensions Metrics API and the Dimensions Badges (visit https://badge.dimensions.ai) - in both cases for non-commercial purposes. Does it support Another aspect of supporting the academic community was empowering the community. The current vogue in research evaluation promotes the use your use case? of metrics to cope with the vast quantities of material being evaluated. It is clear that a more open data source compatible with more open publications, more open evaluation frameworks and more open metrics are needed. Dimensions aims to be a system that helps the academic community to own the formulation and development of metrics that tell the best stories and give the best context to a piece of research. This document provides an overview of the Dimensions content. Feel free to reach out to the Dimensions team if you want to discuss further whether the content scope and coverage of Dimensions can help in your specific situation and use case. We will improve One of the most important aspects of Dimensions is that we are going to it together! develop it further with the research community - any feedback is welcome. Please contact us at [email protected]. 2 Dimensions Report Quick facts on Dimensions - the total record count and more Content type Number of items indexed Publications 100 million Grants 4.6 million Patents 38 million Clinical Trials 455,000 Policy Documents 422,000 Records with Altmetric attention 10 million Grand total 153 million Linking it all together and enriching it for the user Linked and integrated data from multiple sources are core to Dimensions. The links between grants, This has been a key feature in discussing the product scope and direction with development partners, who agree that the integrated view enables novel publications, clinical insights. The following sections provide a quick overview of the key approaches trials, patents and policy which are visible to the user. documents are key We are realising these linkages with a data driven, machine learning and AI-based approach, automatically extracting the information to create the connections. The content and enrichment pipeline is as automated as possible, allowing us to provide Dimensions with publication / citation data to researchers for free, and to research institutions at realistic cost levels. While an automated approach allows us to offer a more open, free approach it also Automated process, results in some data issues, which we will continue to have to work on and improve. If you see anything that doesn’t seem correct in our data case please efficient and effective, reach out to us. We are always looking to improve the processing pipeline and but we need your help subsequently the data and services that Dimensions provides - please email us to constantly improve at [email protected]. the quality An example of a publication record in Dimensions with links to all other content sources - allowing the user already in the freely available version to explore these relations: Example “Persistent Systemic Inflammation is Associated with Poor Clinical Outcomes in COPD: A Novel Phenotype” (DOI 10.1371/journal. pone.0037483) Publication references 44 Associated data sets 15 Supporting Grants 2 Publication citations 401 Patent citations 5 Linked Clinical trials 2 Policy document citations 1 Altmetric Attention Score 18 Dimensions Report 3 Full text index - enabling deep discovery Full text indexing - Dimensions provides researchers with a free discovery service. Our approach to indexing the full text makes publications and books much more real discovery instead discoverable. Full text search is already available for over 69 million publication of missing relevant records in Dimensions. For example, a search for CRISPR in just title and abstracts brings back about 15,000 results, while the Dimensions search using information the full-text index results
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