Ulrich Sax, C. Henke, Christian Dräger, T. Bender, Alessandra Kuntz, Martin Golebiewski, Hannes Ulrich, Matthias Löbe
{"title":"来源核心数据集:生物医学研究中数据来源的最小信息模型","authors":"Ulrich Sax, C. Henke, Christian Dräger, T. Bender, Alessandra Kuntz, Martin Golebiewski, Hannes Ulrich, Matthias Löbe","doi":"10.52825/cordi.v1i.347","DOIUrl":null,"url":null,"abstract":"The exchange, dissemination, and reuse of biological specimens and data have become essentialfor life sciences research. This requires standards that enable cross-organizational documentation, traceability, and tracking of data and its corresponding metadata. Thus, data provenance, or the lineage of data, is an important aspect of data management in any information system integrating data from different sources [1]. It provides crucial information about the origin, transformation, and accountability of data, which is essential for ensuring trustworthiness, transparency, and quality of healthcare data [2]. For biological material and derived data, a novel ISO standard was recently introduced that specifies a general concept for a provenance information model for biological material and data and requirements for provenance data interoperability and serialization [3,4]. However, a specific standard for health data provenance is currently missing. In recent years, there has been a growing need for developing a minimal core data set for representing provenance information in health information systems. This paper presents a Provenance Core Data Set (PCDS), a generalized data model that aims to provide a set of attributes for describing data provenance in health information systems and beyond. ","PeriodicalId":359879,"journal":{"name":"Proceedings of the Conference on Research Data Infrastructure","volume":"4 3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Provenance Core Data Set A Minimal Information Model for Data Provenance in Biomedical Research\",\"authors\":\"Ulrich Sax, C. Henke, Christian Dräger, T. Bender, Alessandra Kuntz, Martin Golebiewski, Hannes Ulrich, Matthias Löbe\",\"doi\":\"10.52825/cordi.v1i.347\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The exchange, dissemination, and reuse of biological specimens and data have become essentialfor life sciences research. This requires standards that enable cross-organizational documentation, traceability, and tracking of data and its corresponding metadata. Thus, data provenance, or the lineage of data, is an important aspect of data management in any information system integrating data from different sources [1]. It provides crucial information about the origin, transformation, and accountability of data, which is essential for ensuring trustworthiness, transparency, and quality of healthcare data [2]. For biological material and derived data, a novel ISO standard was recently introduced that specifies a general concept for a provenance information model for biological material and data and requirements for provenance data interoperability and serialization [3,4]. However, a specific standard for health data provenance is currently missing. In recent years, there has been a growing need for developing a minimal core data set for representing provenance information in health information systems. This paper presents a Provenance Core Data Set (PCDS), a generalized data model that aims to provide a set of attributes for describing data provenance in health information systems and beyond. \",\"PeriodicalId\":359879,\"journal\":{\"name\":\"Proceedings of the Conference on Research Data Infrastructure\",\"volume\":\"4 3 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-09-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the Conference on Research Data Infrastructure\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.52825/cordi.v1i.347\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Conference on Research Data Infrastructure","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.52825/cordi.v1i.347","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Provenance Core Data Set A Minimal Information Model for Data Provenance in Biomedical Research
The exchange, dissemination, and reuse of biological specimens and data have become essentialfor life sciences research. This requires standards that enable cross-organizational documentation, traceability, and tracking of data and its corresponding metadata. Thus, data provenance, or the lineage of data, is an important aspect of data management in any information system integrating data from different sources [1]. It provides crucial information about the origin, transformation, and accountability of data, which is essential for ensuring trustworthiness, transparency, and quality of healthcare data [2]. For biological material and derived data, a novel ISO standard was recently introduced that specifies a general concept for a provenance information model for biological material and data and requirements for provenance data interoperability and serialization [3,4]. However, a specific standard for health data provenance is currently missing. In recent years, there has been a growing need for developing a minimal core data set for representing provenance information in health information systems. This paper presents a Provenance Core Data Set (PCDS), a generalized data model that aims to provide a set of attributes for describing data provenance in health information systems and beyond.