{"id":45056,"date":"2021-07-07T12:28:09","date_gmt":"2021-07-07T16:28:09","guid":{"rendered":"https:\/\/umaine.edu\/research\/?p=45056"},"modified":"2021-07-13T16:11:13","modified_gmt":"2021-07-13T20:11:13","slug":"how-research-data-management-benefits-everyone-through-open-access","status":"publish","type":"post","link":"https:\/\/umaine.edu\/research\/2021\/07\/07\/how-research-data-management-benefits-everyone-through-open-access\/","title":{"rendered":"How Research Data Management benefits everyone through open access"},"content":{"rendered":"<p>Research Data Management (RDM) is a systematic and planned approach to the entire life cycle of scholarly data: from the collection, creation, and\/or observation to documentation, storage, and sharing. All researchers engage in RDM in some capacity, but the better a project\u2019s research data is managed, the better the impact the project will have beyond its duration of work.<\/p>\n<p>Making research data accessible to the public and other scholars increases the integrity of the research and contributes to building a greater body of knowledge, a noble cause for every scholar. \u201cPublic access is a natural continuation of an academic institution\u2019s research mission,\u201d says Shane Moeykens, director of Advanced Research Computing, Security, and Information Management (ARCSIM) at UMaine. \u201cPart of that continuum is making sure it&#8217;s not just writing a report about the information, but making the information itself available to the broader community.\u201d<\/p>\n<p>Open access to research data increases the visibility of a researcher\u2019s work, advances the field of discipline, and ultimately enhances public trust. In some cases making research data open to access is required. The National Science Foundation\u2019s <a href=\"https:\/\/www.nsf.gov\/pubs\/policydocs\/pappg20_1\/nsf20_1.pdf\">Proposal &amp; Award Policies &amp; Procedures Guide (PAPPG)<\/a>, for example, clearly states that \u201cinvestigators are expected to share with other researchers, at no more than incremental cost and within a reasonable time, the primary data, samples, physical collections and other supporting materials created or gathered in the course of work under NSF grants.\u201d This means that researchers with NSF funding must make project materials available to others.<\/p>\n<p>Research data extends beyond measurements and publications and should be thought of as everything utilized in a project. Lab notebooks, archival photos taken during a library visit, survey results, audio recordings, samples, and film clips are just some of the possibilities of what can be considered research data.<\/p>\n<p>The most common ways to make research outputs available are through data repositories. UMaine has two tools available: <a href=\"https:\/\/digitalcommons.library.umaine.edu\/\">DigitalCommons<\/a> managed by Fogler Library and <a href=\"https:\/\/acg.maine.edu\/maine-dataverse-network\/\">Dataverse<\/a> facilitated by the Advanced Computing Group and the University of Maine System IT organization. DigitalCommons primarily aggregates publications and other research and creative products of a project. Its ease of use and aggregation saves time for researchers looking to find the history of research done on a certain topic. Dataverse contains the research data itself, and it is particularly useful for large projects with multiple contributors to place all their work in one place. Any researcher at UMaine can <a href=\"https:\/\/libguides.library.umaine.edu\/datamanagement\/umaine\">seek advice<\/a> from the Office of Research Administration, the Fogler Library, and the Advanced Computing Group to make a plan for managing their research data when applying for funding. Ami Gaspar, an outreach specialist for the Advanced Computing Group, also runs useful <a href=\"https:\/\/www.youtube.com\/watch?v=EHymsWG_BGM\">seminars on research data management<\/a> for researchers at any career level.<\/p>\n<p>\u201cWe often think that if we publish in books or journals, we must give our intellectual property away to those publishers,\u201d says Jen Bonnet, social science and humanities reference librarian at Fogler Library. \u201cAuthors and publishers now have more options for what they can do with their research outputs. A journal article is one output, data would be another output. Increasingly, publishers will let you make your article and the data associated with that article available in your open access institutional repository, within a certain timeframe.\u201d If open access to research data is required by a grant funding the project the negotiation can be easier between the researcher and publisher. Some grants could also require placing research data in national or international repositories. \u201cThat doesn\u2019t mean we\u2019re not going to work locally with Dataverse and other institutional alternatives,\u201d says Moeykens. \u201cIt\u2019s really a spectrum of activity.\u201d<\/p>\n<p>While research projects will vary in what they contain and require, the overarching goal is to lower the bar and make it easier for people to gain access to the project\u2019s information in its raw form. \u201cFaculty strive to be in compliance today with the federal requirements, but is it as easy as it could be?\u201d Moeykens explains. \u201cThere\u2019s always more that can be done. Over time, there could be new portals developed, and new institutional practices around existing tools.\u201d<\/p>\n<p>Derivative research products are becoming increasingly part of federally funded projects, where the research contributes back to the public by creating a user-friendly tool that makes its data digestible. <a href=\"https:\/\/www.shellgis.com\/\">ShellGIS<\/a> is an outstanding example of a derivative decision support tool, directly extending federally sponsored data and work to the general public in a way that benefits the public. The tool was developed under Damian Brady, associate professor at the Darling Marine Center for the Sustainable Ecological Aquaculture Network (SEANET), with Meggan Dwyer as the research coordinator for the project.<\/p>\n<p>Even if a project does not result in a derivative tool, other things matter in making research data accessible. Version control and descriptive naming conventions throughout a project\u2019s duration help track changes in a project. \u201cThere\u2019s so much interdisciplinary and collaborative work happening on campus that being able to have an audience that\u2019s outside your field understand at least what each of your files contains is a true kindness,\u201d says Bonnet. \u201cBest practices suggest that researchers be as descriptive as possible, and if possible, have a guiding document so that people going through their data files can make sense of what\u2019s there, why it\u2019s there, and how it connects.\u201d For the general public, it\u2019s important to avoid jargon in keywords and descriptions.<\/p>\n<p>File formats are also important for the long run, as proprietary formats may no longer be supported. For instance, formatting the data file as a CSV instead of an Excel file ensures access to a wider audience. PDFs can also be formatted as XML or HTML so that readers will not require software to read them. More on best practices for research data management can be found on Fogler Library\u2019s extensive <a href=\"https:\/\/libguides.library.umaine.edu\/datamanagement\/bestpractice\">online resource<\/a>.<\/p>\n<p>Contact: <a href=\"mailto:research@maine.edu\">research@maine.edu<\/a><\/p>\n<p>Written by Clarisa Diaz<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Research Data Management (RDM) is a systematic and planned approach to the entire life cycle of scholarly data: from the collection, creation, and\/or observation to documentation, storage, and sharing. All researchers engage in RDM in some capacity, but the better a project\u2019s research data is managed, the better the impact the project will have beyond 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Data Management (RDM) is a systematic and planned approach to the entire life cycle of scholarly data: from the collection, creation, and\/or observation to documentation, storage, and sharing. All researchers engage in RDM in some capacity, but the better a project\u2019s research data is managed, the better the impact the project will have beyond its duration of work. Making research data accessible to the public and other scholars increases the integrity of the research and contributes to building a greater body of knowledge, a noble cause for every scholar. \u201cPublic access is a natural continuation of an academic institution\u2019s&hellip;<\/p>\n","category_list_v2":"<a href=\"https:\/\/umaine.edu\/research\/category\/program-highlight\/\" rel=\"category tag\">Program Highlight<\/a>, <a href=\"https:\/\/umaine.edu\/research\/category\/research-news\/\" rel=\"category tag\">Research News<\/a>","author_info_v2":{"name":"","url":"https:\/\/umaine.edu\/research\/author\/"},"comments_num_v2":"0 comments","taxonomy_info":{"category":[{"value":573,"label":"Program Highlight"},{"value":65,"label":"Research News"}],"post_tag":[{"value":634,"label":"ARCSIM"},{"value":632,"label":"data management"},{"value":633,"label":"Fogler Library"},{"value":631,"label":"open access"}]},"featured_image_src_large":["https:\/\/umaine.edu\/research\/wp-content\/uploads\/sites\/281\/2021\/07\/data_web.jpg",1024,576,false],"author_info":{"display_name":"","author_link":"https:\/\/umaine.edu\/research\/author\/"},"comment_info":0,"category_info":[{"term_id":573,"name":"Program Highlight","slug":"program-highlight","term_group":0,"term_taxonomy_id":573,"taxonomy":"category","description":"","parent":0,"count":41,"filter":"raw","cat_ID":573,"category_count":41,"category_description":"","cat_name":"Program Highlight","category_nicename":"program-highlight","category_parent":0},{"term_id":65,"name":"Research News","slug":"research-news","term_group":0,"term_taxonomy_id":65,"taxonomy":"category","description":"","parent":0,"count":226,"filter":"raw","cat_ID":65,"category_count":226,"category_description":"","cat_name":"Research News","category_nicename":"research-news","category_parent":0}],"tag_info":[{"term_id":634,"name":"ARCSIM","slug":"arcsim","term_group":0,"term_taxonomy_id":634,"taxonomy":"post_tag","description":"","parent":0,"count":3,"filter":"raw"},{"term_id":632,"name":"data management","slug":"data-management","term_group":0,"term_taxonomy_id":632,"taxonomy":"post_tag","description":"","parent":0,"count":1,"filter":"raw"},{"term_id":633,"name":"Fogler Library","slug":"fogler-library","term_group":0,"term_taxonomy_id":633,"taxonomy":"post_tag","description":"","parent":0,"count":1,"filter":"raw"},{"term_id":631,"name":"open access","slug":"open-access","term_group":0,"term_taxonomy_id":631,"taxonomy":"post_tag","description":"","parent":0,"count":1,"filter":"raw"}],"_links":{"self":[{"href":"https:\/\/umaine.edu\/research\/wp-json\/wp\/v2\/posts\/45056","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/umaine.edu\/research\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/umaine.edu\/research\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/umaine.edu\/research\/wp-json\/wp\/v2\/users\/478"}],"replies":[{"embeddable":true,"href":"https:\/\/umaine.edu\/research\/wp-json\/wp\/v2\/comments?post=45056"}],"version-history":[{"count":4,"href":"https:\/\/umaine.edu\/research\/wp-json\/wp\/v2\/posts\/45056\/revisions"}],"predecessor-version":[{"id":45084,"href":"https:\/\/umaine.edu\/research\/wp-json\/wp\/v2\/posts\/45056\/revisions\/45084"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/umaine.edu\/research\/wp-json\/wp\/v2\/media\/45057"}],"wp:attachment":[{"href":"https:\/\/umaine.edu\/research\/wp-json\/wp\/v2\/media?parent=45056"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/umaine.edu\/research\/wp-json\/wp\/v2\/categories?post=45056"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/umaine.edu\/research\/wp-json\/wp\/v2\/tags?post=45056"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}