Görzig, H., Engel, F., Brocks, H., Vogel, T. & Hemmje, M. (2015, August). Towards Data Management Planning Support for Research Data. Paper presented at the ASE International Conference on Data Science, Stanford, United States of America. ; This paper outlines challenges and requirements for developing tools and services supporting automated generation, management, evolution, and execution of Data Management Plans (DMPs) by reviewing Research Data Management (RDM) processes represented by Knowledge-based and Process-oriented Innovation Management (German: Wissenbasiertes Prozess-orientiertes Innovationsmanagement, WPIM). Based on this representation Data Management Rules (DMRs) will be derived to support the Integrated Rule-Oriented Data System (iRODS). In this way, compliance with the Open Archive Information System (OAIS) and packaging the relevant context information related to a data object is supported in a serialization using the Open Archives Initiative Object Reuse and Exchange (OAI-ORE) format specification. ; This study is part of the RAGE project. The RAGE project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 644187. This publication reflects only the author's view. The European Commission is not responsible for any use that may be made of the information it contains.
In anticipation of the then forthcoming Tri-Agency Research Data Management Policy, a consortium of professionals from Canadian university libraries surveyed researchers on their research data management (RDM) practices, attitudes, and interest in data management services. Data collected from three surveys targeting researchers in science and engineering, humanities and social sciences, and health sciences and medicine were compiled to create a national dataset. The present study is the first large-scale survey investigating researcher RDM practices in Canada, and one of the few recent multi-institutional and multidisciplinary surveys on this topic. This article presents the results of the survey to assess researcher readiness to meet RDM policy requirements, namely the preparation of data management plans (DMPs) and data deposit in a digital repository. The survey results also highlight common trends across the country while revealing differences in practices and attitudes between disciplines. Based on our survey results, most researchers would have to change their RDM behaviors to meet Tri-Agency RDM policy requirements. The data we gathered provides insights that can help institutions prioritize service development and infrastructure that will meet researcher needs. ; En prévision de la future Politique des trois organismes sur la gestion des données de recherche, un consortium de professionnels des bibliothèques universitaires canadiennes a interrogé des chercheurs sur leurs pratiques et leurs attitudes en matière de gestion des données de recherche (GDR) et sur leur intérêt pour les services de gestion des données. Des données recueillies de trois sondages ciblant les chercheurs en sciences et en génie, en sciences humaines et sociales ainsi qu'en sciences de la santé et en médecine ont été compilées pour créer un ensemble de données national. Cette étude est la première enquête à grande échelle sur les pratiques de GDR des chercheurs au Canada et est l'une des rares enquêtes récentes ...
Der Beitrag ordnet das Handlungsfeld Forschungsdatenmanagement zunächst in den Kontext sich wandelnder Anforderungen an wissenschaftliche Bibliotheken sowie wissenschaftspolitischer Strategien und Forderungen auf nationaler und europäischer Ebene ein. Im Anschluss liegt der Schwerpunkt auf einem möglichen Leistungsportfolio einer wissenschaftlichen Bibliothek, das Forschenden Unterstützung bei dem Management und der Publikation ihrer Forschungsdaten bietet. Die denkbaren Serviceleistungen reichen dabei von der Beratung bis hin zum Aufbau eigener Forschungsdateninfrastrukturen, die den Nachweis, die Bewertung, das Sichtbarmachen und die Überprüfung von Forschungsdaten ermöglichen. ; The field of action "research data management" is placed within the context of changing requirements to research libraries as well as of strategies and requirements named by science policy on national and European level. The focus lies on a potential service portfolio of a research library, which offers researchers support with regard to the management and publication of research data. Potential services might range from advisory services to the development of research data infrastructures which facilitate the record, evaluation, visibility and review of research data.
This course gives a brief recap on RDM and then covers managing personal and sensitive data in the context of the new GDPR legislation, why it is a Good Thing to share your data, and how to do this most effectively in terms of describing your data, deciding where to share it, and using licences to control how your data is used by others. You will even get to write your own Data Management Plan (DMP): these help you manage your data throughout a project and after it has ended and are increasingly required as part of a grant or fellowship application. You will also learn about the range of support services available to you within the University for managing your data.
Data Management Plans (DMP) play an important role for planning and conducting research activities and more and more researchers are facing requirements by their institution or funding agency for writing such a plan. Thereby, they are often misunderstood as an administrative task. Instead, DMPs are a powerful tool for efficient and secure collaboration and for the creation of research outputs of better quality and higher impact. A DMP will also help you to develop strategies for sharing and publishing your research data as openly as possible (and protecting them, when necessary). In this session, we will introduce the typical components of a DMP and discuss how the plan can be used actively throughout a research project. It will be targeted towards PhD students, but it will also be relevant for anyone working with research data. ; Co-funded by the Erasmus+ Programme of the European Union
Presentation for the Health Libraries Association of British Columbia. Take a moment to think about your researchers and the kinds of data they access and/or create. Where is this data stored and how is it organized? If they were asked to share data with another researcher would they be able to make sense of that work? If they needed to locate the data files from 5 years ago, how easy would it be to find and use datasets? What privacy and security controls have they implemented to ensure that they are appropriately safeguarding their data? Is their data governed by legislative requirements? If so, are they required to comply with additional policies and standards when using these datasets? If you are unsure about the answer to any of these questions you have come to the right place. This workshop will cover the basics of data management plans, metadata and data documentation, data privacy and security, and data sharing. It is designed to support researchers engaging in clinical research to start thinking about the steps they can take to better manage their research data. Kaitlyn Gutteridge is the Research Data Privacy and Security Officer for the ARC team. In addition, Kaitlyn serves as a member of the Compute Canada Security Council. She holds a Master of Science degree from the London School of Hygiene and Tropical Medicine where she focused her epidemiology training on multilevel modeling of chronic disease development. She previously held positions supervising the implementation of large-scale research initiatives at Simon Fraser University and the Centre for Hip Health and Mobility. Most recently, she served as the Privacy and Governance Lead at Population Data BC. In her position at Population Data BC, Kaitlyn served as the organization's Privacy Officer and managed the negotiation, development, and execution of information sharing agreements and associated policies & procedures. Eugene Barsky is Research Data Librarian at the UBC Library. His recent peer-recognition included American Society for Engineering Education and Special Library Association awards. He published more than 20 peer-reviewed papers and presented at more than 40 conferences. Eugene is chairing the national Portage Data Discovery Expert Group, participates in building the Canadian Federated Research Data Repository (FRDR), and collaborates with Research Data Canada (RDC). Eugene is an adjunct faculty member at the iSchool at UBC, teaching courses in science librarianship and research data management, and is an active member of the Pacific Northwest data curators group. ; Library, UBC ; Other UBC ; Unreviewed ; Faculty ; Other
This is a non-credit, free course which provides guidelines for good practice in research data management. The course is particularly appropriate for postgraduate students and early career researchers who work with data and would like to learn more about managing their research data. The course content is mainly geared for three disciplines: geosciences, social and political sciences and clinical psychology, however, many of the issues covered apply equally to all research disciplines. This course is an Open Educational Resource that may be freely used by anyone. It is available through an open license for re-using, rebranding, repurposing.
Research data must be discoverable to be re-used. Data discovery represents the descriptive and technical processing of data and metadata, as well as the tools and infrastructure aimed at improving access and reuse of research data on the web. A Canadian data discovery service would make it easier to find and reuse research data held in institutional and disciplinary repositories. We would like to see a service that provides a coherent, single point of access to authoritative, searchable, browsable, and machine actionable descriptions (metadata) for datasets and implements clear means for accessing them, thus increasing the likelihood of discovery and reuse of research data in Canada. In this paper, we highlight current opportunities and issues related to developing such a service in Canada. Based on a review of international and national research data repositories and data discovery services, we offer a set of guiding principles, best practices, and recommendations for data discovery: Common metadata: the descriptive information that accompanies research data should meet minimum standards to enable discovery and support data reuse. This requires a commitment to a core set of metadata components across domains. Metadata tools should accommodate multiple, overlapping metadata namespaces, i.e., descriptive terms assigned, managed, and grouped into collections of classes and attributes. We also recommend building separate, flexible metadata harvesters for indexing specialized repositories, so that domain-specific metadata and granularity can be retained in its original format. Persistent Identification: the use of global identifiers for researchers and research data. We recommend exploring a national ORCID agreement so that universities and government agencies in Canada can integrate researcher identifiers into institutional and other research management and publishing software. We also recommend registering DOIs corresponding to datasets in participating repositories with DataCite Canada. These DOIs will greatly enhance dataset discoverability via DataCite's metadata partners (e.g. ORCID, VIVO, etc). Open Access and Programmatic Interfaces: the use of an application program interface (API) allowing one piece of software to make use of the functionality or data available to another through a set of routines, protocols, and tools. Metadata and data should be programmatically accessible for reuse and development purposes through the provision of APIs among participating repositories and data discovery platforms. Common licensing: policies and licenses should govern access to data and metadata and, whenever possible, should be minimally restrictive. We recommend the use of Creative Commons licenses for research data as they effectively communicate information about the copyright holders' intentions and clarify usage permissions. Licensing can apply to data and metadata, although we strongly recommend that metadata be provided as openly as possible, with minimal to no restrictions on reuse in order to facilitate discovery. Collaboration: a joint commitment to shared recognition and cooperation among actors, organizations, data producers, and researchers, sometimes described as "coexistence in the scholarly ecosystem." We emphasize that collaboration will drive improvements for data discovery in Canada. A well coordinated national project will ensure that all attempts to improve discovery and access to data will be informed and facilitated by stakeholder expectations, participation, and collaboration. Keeping stakeholders engaged and providing clear communication channels are key for the success of a national data discovery service. This paper is presented with a common goal to make research data as widely discoverable and accessible as possible, thus enhancing opportunities for data reproducibility and reuse. Enhancing data discovery is one approach to facilitating greater interoperability and discovery of scholarly outputs. Building national infrastructure to support research data discovery will greatly enhance opportunities for further integration across the scholarly ecosystem, including support for metadata, global identifiers, and open APIs. ; Library, UBC ; Non UBC ; Unreviewed ; Faculty ; Researcher
It presents research data access and management initiatives in Argentina. The Database National Systems initiative by the Ministry of Science, Technology and Productive Innovation (MINCyT) includes the National System of Biological Data, the National System of Sea Data, the National System of Digital Repositories, and the National System of Climate Data. Research data access and management legislation was promoted by MINCyT and it is now being discussed by Argentinean Congress. The National Council of Scientific and Technological Research is developing the Interactive Platform for Social Sciences Research to create an appropriate environment for data sharing, to allow interdisciplinary approaches and to contribute to the understating of complex problems. National University of Rosario is conducting a study to learn researchers´ needs regarding repository services for data management and access. ; Fil: Bongiovani, Paola Carolina. Universidad Nacional de Rosario; Argentina
This report presents the findings of a needs assessment survey that was carried out with research managers in four Palestinian Higher Education Institutions (PS HEIs) between December 2016 and February 2017. The four participating institutions include: The Islamic University of Gaza (IUG) Al-Quds Open University (QOU) Birzeit University (BZU) Palestine Technical University-Kadoori (KAD) The survey data will be used to: Identify the size, formats and scopes of research volumes and digital holdings for which each partner PS HEI assumes preservation responsibility. Review the current RDM practices and activities adopted at the institutional level. Review the current situation in PS HEIs as regards IRs, open access publishing and institutional support for RDM. Determine the current shortcomings and future priorities in RDM from the institution's perspective. In general, this survey targeted the administration and management staff who were responsible for, or directly involved, in RDM in the four partner PS HEIs. Since partner PS Universities might have different organizational structures and administrative departments, the selection process of participants from each university could not be the same. Project coordinators at partner PS Universities were asked to choose eligible persons based on the university's structure and pertinent administrative positions. They were urged to select participants from department/units/centres that were in charge of RDM activities such as scientific research, University library, IT unit, etc. ; Project number: 573700-EPP-1-2016-1-PS-EPPKA2-CBHE-JP. Co-funded by the Erasmus+ Programme of the European Union.
The overall goal of WP2 in FarFish is to "advance knowledge and collate data related to biological characteristics of the main fish stocks in the selected fisheries, and to evaluate the appropriateness, relevance and applicability of stock assessment models currently in use for these fisheries", as per the DoA. Task 2.2 and deliverable 2.2 contributes towards these goals by creating a "Data Management Plan", as per the Horizon 2020 Open Research Data Pilot. The deliverable contains 14 forms detailing the content of all datasets used within FarFish, how it will be preserved, and steps taken to make data publically available after the project end. ; This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement no. 727891.
The overall goal of WP2 in FarFish is to "advance knowledge and collate data related to biological characteristics of the main fish stocks in the selected fisheries, and to evaluate the appropriateness, relevance and applicability of stock assessment models currently in use for these fisheries", as per the DoA. Task 2.2 and deliverable 2.2 contributes towards these goals by creating a "Data Management Plan", as per the Horizon 2020 Open Research Data Pilot. The deliverable contains 14 forms detailing the content of all datasets used within FarFish, how it will be preserved, and steps taken to make data publically available after the project end. ; This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement no. 727891.
The overall goal of WP2 in the FarFish project is to "advance knowledge and collate data related to biological characteristics of the main fish stocks in the selected fisheries, and to evaluate the appropriateness, relevance and applicability of stock assessment models currently in use for these fisheries", as presented in the project description (DoA). Task 2.2 and deliverable 2.2 contributes towards these goals by creating a "Data Management Plan" (DMP), in accordance with the Horizon 2020 Open Research Data Pilot. The DMP was initially developed in the first months of the project and was first published in month six (November 2017) of the project. The DMP has been regularly updated during the lifetime of the project and this is the fifth, and final (revised), version. The DMP contains 47 forms detailing the content of all datasets used within FarFish, how it will be preserved, and steps taken to make data publically available after the project end. ; This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement no. 727891.
The presentation was given as part of the networking meeting Research Data Management Reloaded: Open Data and the Future of Research Data Management in the Social Sciences and Humanities that targeted research data management officers of universities, academic libraries and research institutes in German-speaking countries. The meeting involved a review of Open Data requirements and related infrastructures, e.g. in terms of best practice guidelines or data repositories, as well as of resources to assist researchers in processing Open Data, such as the FOSTER Plus Online Toolkit or the CESSDA Data Management Expert Guide.The meeting was part of the FOSTER Plus Project (Facilitate Open Science Training For European Research), funded by the EU (grant numbers 612425 and 741839). It took place on April 24th and 25th, 2019, at GESIS – Leibniz-Institute for the Social Sciences in Cologne, Germany. The course's language was German. It was supported by CESSDA Training, being a follow-up event of the CESSDA's Train- the-Trainers workshop in Ljubljana in April 2018. The major focus of this content driven session was on resources to do good research data management as well as to train and consult (young) researchers in doing so. In this context, Sebastian Netscher introduced the CESSDA Data Management Expert Guide as core sources to learn about research data management. The workshop consisted of several presentations: Introduction "Open Science und FAIR Data" http://doi.org/10.5281/zenodo.3925299 Das FOSTER Toolkit http://doi.org/10.5281/zenodo.3925327 CESSDA Data Management Expert Guide, Forschungsdatenmanagement Training Tool https://doi.org/10.5281/zenodo.3964385 Was bietet das GESIS Datenarchiv an? http://doi.org/10.5281/zenodo.3925380 Gemeinsam statt einsam, Beispiele für ein vernetztes Forschungsdatenmanagement http://doi.org/10.5281/zenodo.3925390 Hessische Forschungsdateninfrastruktur HeFDI- FDM als Landesinitiative http://doi.org/10.5281/zenodo.3925395 Verbund Forschungsdaten Bildung http://doi.org/10.5281/zenodo.3925399 CESSDA ERIC, Ein paneuropäisches Netzwerk sozialwissenschaftlicher Datenarchive http://doi.org/10.5281/zenodo.3925409
