ORCID for funders: Who’s who - and what are they doing? - ORCID IDs as identifiers for researchers and flexible article based classifications to understand the collective researcher portfolio

التفاصيل البيبلوغرافية
العنوان: ORCID for funders: Who’s who - and what are they doing? - ORCID IDs as identifiers for researchers and flexible article based classifications to understand the collective researcher portfolio
المؤلفون: Christian Herzog, Giles Radford
المصدر: F1000Research. 4:122
بيانات النشر: F1000 Research Ltd, 2015.
سنة النشر: 2015
مصطلحات موضوعية: Persistent identifier, Service (systems architecture), General Immunology and Microbiology, business.industry, General Medicine, Who's Who, General Biochemistry, Genetics and Molecular Biology, Metadata, Identifier, World Wide Web, Workflow, Publishing, Portfolio, Medicine, General Pharmacology, Toxicology and Pharmaceutics, business, Neuroscience
الوصف: For science funders, ORCID provides a persistent identifier that distinguishes one researcher from the others, and can facilitate workflows in grant submission, career tracking, and research impact(s). It makes life easier for the researcher – they can update their information in ORCID and make his/her past publications available to a funder as an ongoing service by just allowing this access as a one-time agreement. With these newly launched persistent tokens, researchers can grant a funder the right to update their grant record on ORCID once awarded – the metadata goes on an automatic roundtrip – effortless for the researcher, but the researcher stays in control, and can remove this right at any stage. Having and sharing data is one aspect – but being able to understand true researcher activity is another – and even more challenging is to understand research activity in the aggregate. What are hundreds or thousands of researchers doing? Often a standard search will only answer or provide insights into a slice of the data. Research classification systems - like the Fields of Research (FOR) - provide sufficient aggregation, but these normally require manual tagging and curation of all the documents in a dataset. However, by using machine learning to automate tagging, it becomes possible to answer the ‘what’ question easily. This ‘article-based classification’ is realized using Natural Language Processing (NLP) technology. With Dimensions, a portfolio analysis tool for research funders these capabilities are combined for research funders: allowing the researcher to provide controlled access to their ORCID profile and a solution environment for flexible article based classification, providing immediate access to analytical information on the researcher and institutional level – answering the questions ‘who is who’ and ‘what are they doing’?
تدمد: 2046-1402
الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_________::eaf8f0b3ae30f8110dcb0f40c75f81bcTest
https://doi.org/10.12688/f1000research.6504.1Test
حقوق: OPEN
رقم الانضمام: edsair.doi...........eaf8f0b3ae30f8110dcb0f40c75f81bc
قاعدة البيانات: OpenAIRE