{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,5,14]],"date-time":"2025-05-14T09:49:12Z","timestamp":1747216152414,"version":"3.40.5"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"type":"print","value":"9781643684284"},{"type":"electronic","value":"9781643684291"}],"license":[{"start":{"date-parts":[[2023,9,12]],"date-time":"2023-09-12T00:00:00Z","timestamp":1694476800000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,9,12]]},"abstract":"<jats:p>Metadata is essential for handling medical data according to FAIR principles. Standards are well-established for many types of electrophysiological methods but are still lacking for microneurographic recordings of peripheral sensory nerve fibers in humans. Developing a new concept to enhance laboratory workflows is a complex process. We propose a standard for structuring and storing microneurography metadata based on odML and odML-tables. Further, we present an extension to the odML-tables GUI that enables user-friendly search functionality of the database. With our open-source repository, we encourage other microneurography labs to incorporate odML-based metadata into their experimental routines.<\/jats:p>","DOI":"10.3233\/shti230687","type":"book-chapter","created":{"date-parts":[[2023,9,12]],"date-time":"2023-09-12T07:05:09Z","timestamp":1694502309000},"source":"Crossref","is-referenced-by-count":0,"title":["odML-Tables as a Metadata Standard in Microneurography"],"prefix":"10.3233","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7770-4389","authenticated-orcid":false,"given":"Alina","family":"Troglio","sequence":"first","affiliation":[{"name":"Research Group Neuroscience, IZKF, Department of Physiology, RWTH Aachen University, Aachen, Germany"}]},{"given":"Aidan","family":"Nickerson","sequence":"additional","affiliation":[{"name":"School of Physiology, Pharmacology and Neuroscience Bristol Anaesthesia, Critical Care and Pain Research, University of Bristol, UK"},{"name":"Eli Lilly and Company, Bracknell, UK"}]},{"given":"Fabian","family":"Schlebusch","sequence":"additional","affiliation":[{"name":"Research Group Neuroscience, IZKF, Department of Physiology, RWTH Aachen University, Aachen, Germany"}]},{"given":"Rainer","family":"R\u00f6hrig","sequence":"additional","affiliation":[{"name":"Institute of Medical Informatics, Medical Faculty, RWTH Aachen University, Aachen, Germany"}]},{"given":"James","family":"Dunham","sequence":"additional","affiliation":[{"name":"School of Physiology, Pharmacology and Neuroscience Bristol Anaesthesia, Critical Care and Pain Research, University of Bristol, UK"}]},{"given":"Barbara","family":"Namer","sequence":"additional","affiliation":[{"name":"Research Group Neuroscience, IZKF, Department of Physiology, RWTH Aachen University, Aachen, Germany"}]},{"given":"Ekaterina","family":"Kutafina","sequence":"additional","affiliation":[{"name":"Institute of Medical Informatics, Medical Faculty, RWTH Aachen University, Aachen, Germany"}]}],"member":"7437","container-title":["Studies in Health Technology and Informatics","German Medical Data Sciences 2023 \u2013 Science. Close to People."],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/SHTI230687","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,9,12]],"date-time":"2023-09-12T07:05:12Z","timestamp":1694502312000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/SHTI230687"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,9,12]]},"ISBN":["9781643684284","9781643684291"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/shti230687","relation":{},"ISSN":["0926-9630","1879-8365"],"issn-type":[{"type":"print","value":"0926-9630"},{"type":"electronic","value":"1879-8365"}],"subject":[],"published":{"date-parts":[[2023,9,12]]}}}