Sara Mannheimer, Jason A. Clark, Kyle Hagerman, Jakob Schultz, James Espeland
{"title":"Dataset Search: A lightweight, community-built tool to support research data discovery","authors":"Sara Mannheimer, Jason A. Clark, Kyle Hagerman, Jakob Schultz, James Espeland","doi":"10.7191/JESLIB.2021.1189","DOIUrl":null,"url":null,"abstract":"Objective: Promoting discovery of research data helps archived data realize its potential to advance knowledge. Montana State University (MSU) Dataset Search aims to support discovery and reporting for research datasets created by researchers at institutions.\n\nMethods and Results: The Dataset Search application consists of five core features: a streamlined browse and search interface, a data model based on dataset discovery, a harvesting process for finding and vetting datasets stored in external repositories, an administrative interface for managing the creation, ingest, and maintenance of dataset records, and a dataset visualization interface to demonstrate how data is produced and used by MSU researchers.\n\nConclusion: The Dataset Search application is designed to be easily customized and implemented by other institutions. Indexes like Dataset Search can improve search and discovery for content archived in data repositories, therefore amplifying the impact and benefits of archived data.","PeriodicalId":90214,"journal":{"name":"Journal of escience librarianship","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2021-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of escience librarianship","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.7191/JESLIB.2021.1189","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
Objective: Promoting discovery of research data helps archived data realize its potential to advance knowledge. Montana State University (MSU) Dataset Search aims to support discovery and reporting for research datasets created by researchers at institutions.
Methods and Results: The Dataset Search application consists of five core features: a streamlined browse and search interface, a data model based on dataset discovery, a harvesting process for finding and vetting datasets stored in external repositories, an administrative interface for managing the creation, ingest, and maintenance of dataset records, and a dataset visualization interface to demonstrate how data is produced and used by MSU researchers.
Conclusion: The Dataset Search application is designed to be easily customized and implemented by other institutions. Indexes like Dataset Search can improve search and discovery for content archived in data repositories, therefore amplifying the impact and benefits of archived data.