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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 About Dimensions Dimensions is a modern and innovative linked research data infrastructure and tool reimagining 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 di ?erent 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 scienti ?c 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 e ?cient and e ?ective 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 e ?ort 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 info dimensions ai otherwise please write to Digital Science at info digital-science com or Massachusetts Avenue Cambridge MA USA Copyright ? Digital Science Research Solutions Inc DOI m ?gshare Contents A modern linked research data landscape Linking it all together and enriching it for the user Full text index - enabling deep discovery Machine learning based research topic classi ?cation - Fields of Research and other classi ?cation systems Research categories in Dimensions - Australian and New Zealand Standard Research Classi ?cation ANZSRC Other classi ?cation systems Disambiguating institution names - based on GRID Person disambiguation across publications grants patents and clinical trials - a challenging task Citations acknowledgements and adding context Broadening the view beyond publications - bringing content together from as many places as possible How does Dimensions compare to other databases like Google Scholar Pubmed Scopus or Web of Science Citation counts in di ?erent systems and databases - there is no single truth The current content scope and quality is just the starting point Grants - a real glimpse into the future Key statistics on the Dimensions grant data Publications books and citations Dimensions and publications citations - a database not a judgement call Quality related ?lters whitelists and blacklists as tools for the user Aggregating the Dimensions publication and citation data