Research Data Management

Background: Public engagement in health and biomedical research is being influenced by the paradigm of citizen science. However, conventional health and biomedical research relies on sophisticated research data management tools and methods. Considering these, what contribution can citizen science make in this field of re-search? How can it follow research protocols and produce reliable results? Objective: The aim of this article is to analyze research data management practices in existing biomedical citizen science studies, so as to provide insights for members of the public and of the research community considering this approach to research. Methods: A scoping review was conducted on this topic to determine data management characteristics of health and bio medical citizen science research. From this review and related web searching, we chose five on-line platforms and a specific research project associated with each, to understand their research data management approaches and enablers. Results: Health and biomedical citizen science platforms and projects are diverse in terms of types of work with data and data management activities that in themselves may have scientific merit. However, consistent approaches in the use of research data management models or practices seem lacking, or at least are not prevalent in the review. Conclusions: There is potential for important data collection and analysis activities to be opaque or irreproduc-ible in health and biomedical citizen science initiatives without the implementation of a research data management model that is transparent and accessible to team members and to external audiences. This situation might be improved with participatory development of standards that can be applied to diverse projects and platforms, across the research data life cycle.

What is the best way of managing access to sensitive data? This is not a straightforward question, as it involves the interaction of legal, technical, statistical and, above all, human components to produce a solution. This paper introduces a modelling tool designed to simplify and structure such decision-making.
The Five Safes model is a popular framework for designing, describing and evaluating access systems for data, used by data providers, data users, and regulators. The model integrates analysis of opportunities, constraints, costs and benefits of different approaches, taking account of the level of data anonymisation, the likely users, the scope for training, the environment through which data are accessed, and the statistical outputs derived from data use.
Up to now this model has largely been described indirectly in other papers which have used it as a framing device. This paper focuses specifically on the framework, discusses usage, and demonstrates where it sits with other data and risk management tools. The aim is to provide a practical guide to the effective planning and management of access to research data.

Research Data Management (RDM) promises to make research outputs more transparent, findable, and reproducible. Strategies to streamline data management across disciplines are of key importance. This paper presents results of an institutional survey (N = 258) at a medium-sized Austrian university with a STEM focus, supplemented with interviews (N = 18), to give an overview of the state-of-play of RDM practices across faculties and disciplinary contexts. RDM services are on the rise but remain somewhat behind leading countries like the Netherlands and UK, showing only the beginnings of a culture attuned to RDM. There is considerable variation between faculties and institutes with respect to data amounts, complexity of data sets, data collection and analysis, and data archiving. Data sharing practices within fields tend to be inconsistent. RDM is predominantly regarded as an administrative task, to the detriment of considerations of good research practice. Problems with RDM fall in two categories: Generic problems transcend specific research interests, infrastructures, and departments while discipline-specific problems need a more targeted approach. The paper extends the state-of-the-art on RDM practices by combining in-depth qualitative material with quantified, detailed data about RDM practices and needs. The findings should be of interest to any comparable research institution with a similar agenda.

A characteristic of recent decades of scholarly work in the social sciences has been the increased amounts of empirical research. Access and availability of data are prerequisites for further research, replication work, and scientific development. As international peer-reviewed journals have gradually become the central forum for research debate, moves towards data sharing are dependent upon the policies of journals regarding data availability. This article examines contemporary data availability policies in political science and investigates the extent to which journals adopt such policies and their content. It also identifies a few factors associated with the existence of such policies

In this commentary, I propose a framework for thinking about data quality in the context of scientific research. I start by analyzing conceptualizations of quality as a property of information, evidence and data and reviewing research in the philosophy of information, the philosophy of science and the philosophy of biomedicine. I identify a push for purpose dependency as one of the main results of this review. On this basis, I present a contextual approach to data quality in scientific research, whereby the quality of a dataset is dependent on the context of use of the dataset as much as the dataset itself. I exemplify the approach by discussing current critiques and debates of scientific quality, thus showcasing how data quality can be approached contextually.

In the context of open science, good research data management (RDM), including data sharing and data reuse, has become a major goal of research policy. However, studies and monitors reveal that open science practices are not yet widely mainstream. Rewards and incentives have been suggested as a solution, to facilitate and accelerate the development of open and transparent RDM. Based on relevant literature, our paper provides a critical analysis of three main issues: what should be rewarded and incentivized, who should be rewarded, and what kind of rewards and incentives should be used? Concluding the analysis, we ask if it is really necessary and appropriate to consider RDM as an individual (behavioral) issue, as the main challenges are elsewhere, not personal, but technological, institutional and inancial. CCS CONCEPTS • Information systems → Data management systems; ; • General and reference → General literature.

This article gives an overview of the findings from the first phase of the Jisc Journal Research Data Policy Registry pilot (JRDPR), which is currently under way. The project continues from the initial study, ‘Journal of Research Data policy bank’ (JoRD), carried out by Nottingham University’s Centre for Research Communication from 2012 to 2014. The project undertook an analysis of 250 journal research data policies to assess the feasibility of developing a policy registry to assist researchers and support staff to comply with research data publication requirements. The evidence shows that the current research data policy ecosystem is in critical need of standardization and harmonization if such services are to be built and implemented. To this end, the article proposes the next steps for the project with the objective of ultimately moving towards a modern research infrastructure based on machine-readable policies that support a more open scholarly communications environment.

Austin CC; Brown S; Fong N; Humphrey C; *Leahey A; Webster P (2015).
IASSIST Quarterly. Data sharing is increasingly recognized as integral to scientific research and publishing. This requires informed and thoughtful preparation from initial research planning to collection of data/metadata, interoperability, deposit in data repositories, and curation. Research Data Canada (RDC) is a collaborative, non-government organization that promotes access to and preservation of Canadian research data. The RDC Standards and Interoperability Committee (RDC-SINC) surveyed 32 Canadian and International online data platforms for storage, data transfer, curation activities, preservation, access, and sharing features. We developed a checklist to compare criteria and features between platforms. The survey revealed a heterogeneity of features and services across platforms, non-standardized use of terms, uneven compliance with relevant standards, and a paucity of certified data repositories. Recommendations for online digital infrastructure development to meet evolving researcher and end-user needs centre around persistent identification and citation of datasets, data reliability, version control, metadata, data sharing, privacy controls, long-term preservation of data, and certification of data repositories. We identified a need in Canada for investment in an integrated, comprehensive national digital infrastructure for research data.

The emergence of social media, including social networking technologies, has had a profound impact on almost all human activities. Social media's application in research is the most recent occurrence, as the technologies have gained prominence among researchers who regard social media as an avenue for not only strengthening their own networks, but also sharing their research. This article focuses on one of the social networking services for researchers, namely ResearchGate (RG), to assess the research visibility and impact of universities in South Africa. It also examines the correlation between the universities' ResearchGate-based metrics and Web of Science (WoS) citation statistics on the one hand, and the Webometrics Ranking of World Universities' (WRWU) ranking on the other. Results reveal that researchers in the top-ranking South African universities have quickly moved to embrace social media; there is a high correlation between RG and WoS in terms of their coverage of papers produced by universities in South Africa; there is also a high correlation between RG and WoS in terms of impact; and ranking of universities in RG, WoS and WRWU is similarly highly correlated. Further discussions, conclusions and recommendations are provided in the paper.

Incremental is one of eight projects in the JISC Managing Research Data programme funded to identify institutional requirements for digital research data management and pilot relevant infrastructure. Our findings concur with those of other Managing Research Data projects, as well as with several previous studies.

Research data as an integral part of the scholarly record is increasingly attracting attention of all stakeholder groups. Higher education institutions, funding agencies, policy makers as well as the public at large see benefits in accelerating science through opening access to research data. More specifically, this aims at better re-usability and verification of research findings. The latter is particularly of great interest for higher education and other research institutions, as they embody scholarly scrutiny and trust. Once established as an university of a new type that should unify research and teaching, Humboldt-Universität has recently created a new job position to develop an institutional concept for research data management. In this paper we present the initial situation along with preliminary survey findings and draw the consequences for multidisciplinary higher education institutions by taking the example of Humboldt-Universität zu Berlin (HU).

The Open Science (OS) agenda has potentially massive cultural, organizational and infrastructural consequences. Ambitions for OS-driven policies have proliferated, within which researchers are expected to publish their scientific data. Significant research has been devoted to studying the issues associated with managing Open Research Data. Digital curation, as it is typically known, seeks to assess data management issues to ensure its long-term value and encourage secondary use. Hitherto, relatively little interest has been shown in examining the immense gap that exists between the OS grand vision and researchers' actual data practices. Our specific contribution is to examine research data practices before systematic attempts at curation are made. We suggest that interdisciplinary ethnographically-driven contexts offer a perspicuous opportunity to understand the Data Curation and Research Data Management issues that can problematize uptake. These relate to obvious discrepancies between Open Research Data policies and subject-specific research practices and needs. Not least, it opens up questions about how data is constituted in different disciplinary and interdisciplinary contexts. We present a detailed empirical account of interdisciplinary ethnographically-driven research contexts in order to clarify critical aspects of the OS agenda and how to realize its benefits, highlighting three gaps: between policy and practice, in knowledge, and in tool use and development.

Die Humboldt-Universität zu Berlin hat im Spätsommer 2012 damit begonnen, ein institutionelles Konzept zum Forschungsdatenmanagement zu erarbeiten. In diesem Rahmen wurde im 1. Quartal 2013 eine breit angelegte Umfrage durchgeführt, die den aktuellen Stand im Umgang mit Forschungsdaten und die Anforderungen an zentrale Serviceleistungen ermitteln sollte. Der vorliegende Bericht stellt die Umfrage und ihre Ergebnisse dar. Es sollen zudem die Hintergründe der verwendeten Fragen erklärt und damit die Interpretation der Ergebnisse erleichtert werden.

This article considers digital curation in doctoral study and the role of the doctoral supervisor and institution in facilitating students' acquisition of digital curation skills, including some of the potentially problematic expectations of the supervisory relationship with regards to digital curation. Research took the form of an analysis of the current digital curation training landscape, focussing on doctoral study and supervision. This was followed by a survey (n=116) investigating attitudes towards importance, expertise, and responsibilities regarding digital curation. This research confirms that digital curation is considered to be very important within doctoral study but that doctoral supervisors and particularly students consider themselves to be largely unskilled at curation tasks. It provides a detailed picture of curation activity within doctoral study and identifies the areas of most concern. A detailed analysis demonstrates that most of the responsibility for curation is thought to lie with students and that institutions are perceived to have very low responsibility, whilst individuals tend to over-assign responsibility to themselves. Finally, the research identifies the most common types of support system for curation and suggests ways in which students, supervisors, institutions, and others can effectively and efficiently address problematic areas and improve digital curation within doctoral study. The International Journal of Digital Curation is an international journal committed to scholarly excellence and dedicated to the advancement of digital curation across a wide range of sectors. The IJDC is published by the University of Edinburgh on behalf of the Digital Curation Centre. ISSN: 1746-8256. URL: http://www.ijdc.net/ Copyright rests with the authors. This work is released under a Creative Commons Attribution (UK) Licence, version 2.0. For details please see

Management and curation of digital data has been becoming ever more important in a higher education and research environment characterised by large and complex data, demand for more interdisciplinary and collaborative work, extended funder requirements and use of e-infrastructures to facilitate new research methods and paradigms. This paper presents the approach, technical infrastructure, findings, challenges and outlook (including future development within the successor project, MiSS) of the 'MaDAM: Pilot data management infrastructure for biomedical researchers at University of Manchester' project funded under the infrastructure strand of the JISC Managing Research Data (JISCMRD) programme. MaDAM developed a pilot research data management solution at the University of Manchester based on biomedical researchers' requirements, which includes technical and governance components with the flexibility to meet future needs across multiple research groups and disciplines.

To develop robust research support services across the entire research life cycle, individuals and units from across the university, including the library, must collaborate across internal silos. Effective social interoperability—the creation and maintenance of working relationships between individuals and organizational units—in higher education requires a thorough knowledge of campus partners.
The OCLC Research report Social Interoperability in Research Support explores the social and structural norms that shape cross-campus collaboration and offers a conceptual model of key university stakeholders in research support. Information about their goals, interests, expertise, and crucially, the importance of cross-campus relationships in their work was synthesized from interviews conducted with practitioners from a wide range of campus stakeholders in research support. The report describes the network of campus units involved in both the provision and consumption of major categories of research support services and concludes with recommendations for establishing and maintaining successful cross-campus relationships.

The purpose of this study was to assess Research Data Management (RDM) capabilities at the University of Ghana (UG). The study focused on four key capability elements: policy framework, technological infrastructure, skills and knowledge, and support services. It explored the extent to which RDM is embedded in research practices at UG and provides insight into the preparedness of UG to develop RDM. A qualitative case study method was adopted for the study and data was gathered using semi-structured interviews and document analysis. The instrument for the assessment was informed by the Collaborative Assessment for Research Data Infrastructure and Objectives (CARDIO) Matrix tool and respondents were drawn from the Library, IT department, Research Office and senior researchers. The results of the study show that RDM at UG is currently underdeveloped but with immense potential for growth. Though there is no formal RDM infrastructure in place, RDM is considered an essential research integrity issue. Capabilities were generally found to be limited, uncoordinated and not officially instituted. The study recommends that a clear and comprehensive policy framework for RDM should be developed to articulate RDM aspirations and express management’s commitment. It also recommends that research support staff should be supported to build their capacity for RDM promotion and support.

"Abstract (english):
Nearly all academic institutions are presently facing the challenge of ever-growing amounts of digital research data. A comprehensive survey on current research data holdings and researchers needs in supporting their path to good research data management was run at Humboldt-Universität zu Berlin in the first quarter of 2013. In this paper we present the initial situation, evaluate the status quo and reflect about the next strategic steps.

Abstract (german):
Wie nahezu jede wissenschaftliche Einrichtung steht auch die Humboldt-Universität zu Berlin heute vor der Herausforderung mit den zunehmend in digitaler Form vorliegenden Forschungsdaten umzugehen. Basierend auf den Ergebnissen einer im Jahr 2013 durchgeführten Umfrage zum Umgang mit digitalen Forschungsdaten werden die Ausgangssituation charakterisiert, der Status Quo eingeordnet und strategische Überlegungen für das Forschungsdatenmanagement vorgestellt.""

This book is a guide to clarify the legal protection applying to research data under Dutch and European Union law, intended for researchers who need to know what they can do with other people’s data.

The opportunities opened up by ICT and the Internet are making access to research results and data broader and more open. It is increasingly possible to add to the text of a publication by enriching it with other materials, including the relevant research data. By making that data accessible, it becomes easier to verify research results and to reproduce and reuse them.

But when reusing raw research data, it is important to know the legal status of the material. Sometimes, the consent of the 'author' (i.e. the 'maker') of the data is required; however, some actions involving data can be carried out without consent.
The guide aims to clarify the legal protection applying to research data for researchers who need to know what they can do with other people’s data. That information will also allow researchers to determine whether they also need to protect their own research data.

The report provides an overview of the current situation on the basis of the most important legislation and case law. It consists of three sections, dealing successively with intellectual property (copyright, database right, and protection of non-original writings), privacy, and liability.

The guide is a translation of a dutch report, available at http://www.surffoundation.nl/nl/publicaties/Pages/Juridischestatusvanruwedata.aspx.

Dieser Beitrag skizziert vor dem Hintergrund der Diskussionen um den Aufbau einer nationalen Forschungsdateninfrastruktur (NFDI) in Deutschland die Arbeitsweise und Merkmale des Rats für Sozial- und Wirtschaftsdaten (RatSWD). ImMittelpunkt stehen die zwei zentralen Merkmale des RatSWD als unabhängiges Beratungsgremium von Datenproduzenten und wissenschaftlichen Datennutzenden einerseits und als organisatorischer Rahmen für ein dezentrales Netzwerk aus derzeit 31 akkreditierten Forschungsdatenzentren (FDZ) andererseits. Der RatSWD bildet damit den Rahmen für eine nutzergetriebene, nach außen sprechfähige und leistungsfähige, koordinierte Forschungsdateninfrastruktur in den Sozial-, Verhaltens- und Wirtschaftswissenschaften. Die Forschungsdateninfrastruktur der Sozial-, Verhaltens- und Wirtschaftswissenschaften ist als bundesweites, verteiltes und wachsendes Netzwerk arbeitsteilig angelegt. Das Netzwerk koordiniert disziplinübergreifend die Archivierung und Bereitstellung einer Vielfalt von Forschungsdaten, befördert  institutionellen Wissensaustausch und erarbeitet gemeinsame Standards. Der RatSWD widmet sich der Öffnung von weiteren Datenschätzen aus Verwaltung, Forschung und Wirtschaft für die unabhängige Wissenschaft und entwickelt übergeordnete Standards zu Themen wie Datenschutz, Forschungsethik und nachhaltiger Förderpolitik. Den empirisch Forschenden stehen dadurch eine Interessenvertretung nach außen sowie ein stetig wachsendes Angebot an qualitativ hochwertigen Datensätzen zur Verfügung.

"What do researchers need from archives? What do archives
need from researchers? These questions cover two types
of researchers that encounter data archives: those who
create the data (data creators) and those who re-use it
(data re-users). These groups have different needs and
archives mediate between them.
The role of an archive for creators and re-users is to
support them in producing quality data, metadata and
documentation and to facilitate wide and multipurpose
data dissemination. By supporting multipurpose reuse, to
the fullest extent possible, archives help realize the value
of public investment in academic research.
This paper discusses the optimization of research
data management training and support for research
data creators, and data dissemination and long-term
preservation for social science data archives. It outlines
the GESIS plan to create a research data management and
archive training centre for the European research area, to
cater to both data supply and data demand.
The training centre will look to ensure excellence in the
creation and long-term preservation of reusable data in
the European Research area, contribute to promoting
and to the adoption of standards in research data
management, and promote data availability and reuse.
Finally, the centre will provide and coordinate training on
technologies and tools used by data professionals."

This paper attempts to present a brief overview of several Research Data Management (RDM)issues and a detailed literature review regarding the RDM aspects adopted in libraries globally. Furthermore, it will describe several tendencies concerning the management of repository tools for research data, as well as the challenges in implementing the RDM. The proper planned training and skill development for all stakeholders by mentors to train both staff and users are some of the issues that need to be considered to enhance the RDM process. An effortwill be also made to present the suitable policies and workflows along with the adoption of best practices in RDM, so as to boost the research process in an organisation. This study will showcase the implementation of RDM processes in the Higher Educational Institute of India,referring particularly to the Central Library @ NIT Rourkela inOdisha, Indiawith a proposed framework.Finally,this study will also proposean area of opportunities that ca...

RESUMEN: El nuevo modelo de ciencia abierta requiere de una infraestructura adecuada para preservar y compartir los datos de investigación. Ello ha implicado un desafío tanto para los investigadores como para las universidades y centros. Como respuesta se han creado más de dos mil repositorios de datos en el mundo, un cuarto por parte de estas instituciones, con diferentes softwares especializados. El presente trabajo tiene como objetivo proponer atributos de calidad web para evaluar la interfaz de este tipo de sitios. Para ello se realizó una revisión sistematizada de literatura con directrices internacionales, requisitos técnicos y recomendaciones de expertos, detectando coincidencias. Como resultado se ofrece un protocolo de análisis especialmente formulado para repositorios de datos de investigación, con parámetros e indicadores sobre la interfaz de usuario, localización, acceso y reutilización, conservación, difusión, evaluación y compromiso institucional. A modo de conclusión se observa la necesidad de atender los aspectos específicos de este tipo de datos, relevando el papel de las bibliotecas universitarias para gestionarlos. PALABRAS CLAVE: Repositorios; Datos de investigación; Calidad web; Repositorio de datos; Ciencia abierta; Bibliotecas universitarias
ABSTRACT: The new Open Science model requires an adequate infrastructure to preserve and share research data. This has involved a challenge for both researchers and universities and centers. In response, more than two thousand data repositories have been created in the world, a quarter by these institutions, with different specialized software. This paper aims to propose web quality attributes to evaluate the interface of this type of sites. For this, a systematic review of literature with international guidelines, technical requirements and expert recommendations was carried out, detecting coincidences. As a result, an analysis protocol specially formulated for repositories of research data is offered, with parameters and indicators on the user interface, location, access and reuse, conservation, dissemination, evaluation and institutional commitment. In conclusion, the need to address the specific aspects of this type of data is noted, highlighting the role of university libraries in managing them.

The effectiveness and impact of social science research is under constant review. From the sharing, reuse and archiving of social science research data to the outcomes, reach and impact of research, social science professionals are under increasing pressure to realise the maximum potential of their data collections and their research findings. The UK Data Service is playing a key role in supporting researchers in this process and is using detailed and well-received case studies to provide them with guidance on the best practice for sharing and reusing data and also identifying and capturing the impact of research. The impact of research is now routinely considered when examining the 'success' of funded projects, but the reality of identifying and capturing impact can be a challenge. Publishing data in its own right is now recognised as being impactful to funders, yet exposing this narrative through 'showcasing' is under exploited. Such narratives can incentivise others to share data and also improve the quality of the data and documentation. This paper seeks to explore the role that case studies of research can play in this regard. The paper also examines the role that depositor and user case studies can play in enhancing the reuse of a showcased data collection. To achieve this, a variety of illustrative depositor and impact case studies are discussed, highlighting the role that these can have on research projects.

In large systems, data management is only possible through the use of replication techniques. In order to improve availability and ensure fast and efficient access, we propose in this paper a dynamic replication algorithm which takes into account also the placement of data in a hierarchical data grid. Experimental results show the effectiveness of our approach in terms of response time and availability of data in the system.

The Infrastructure for Integration in Structural Sciences (I2S2) Project is funded under the Research Data Management Infrastructure strand of the JISC's Managing Research Data Programme, with a duration of 18 months (Oct 2009 to March 2011.

Open-access data associated with research efforts depend upon managing, packaging, and pre- serving data for sharing with collaborators and the public. The U.S. Long-Term Ecological Research (LTER) Network, established in 1980, provides an early example of embedded data management supporting long-term, place-based research and contributes to our understanding of the enactment of open data access within scientific research arenas. Here, we examine collective data activities enabled by embedding data management within the Shortgrass Steppe (SGS) research site. Study of the SGS LTER, a member of the U.S. LTER Network for more than three decades, provided a unique opportunity to investigate data management practices and challenges during the life cycle of a long-term project. It illustrates how a continuous, uninterrupted focus on data management positioned in dynamic interaction with researchers at a site as well as with an active network-wide data management committee can stimulate the growth of both data expertise and data infrastructure. We report on an ethnographic study by a collaborative team of researchers, all having been involved with the LTER network and well-positioned for investigating data management challenges faced during the periods of activation, maturation, and decommissioning of a project at a research site. Termination of the SGS site’s membership in the U.S. LTER Network prompted rethinking about long-term data management. During the decommissioning phase, we document how views on temporality and data management strategies shift from planning for a longitudinal, ongoing site to wrapping up a long-term project. Striving to ensure “long live the data” at the end, novel data arrangements, such as development of a digital legacy project collection, contribute to data stewardship. Lastly, from this study of a long-term research site, we offer five recommendations about data management and describe strategies pertinent to planning for data management and open access for other research projects.

Im gemeinsamen Austausch der vom BMBF geförderten Projekte eeFDM Jena, FDMentor, FOKUS, PODMAN und UniLLAB wurde deutlich, dass die gewonnenen Erfahrungen im Forschungsdatenmanagement-Kompetenzausbau trotz differierender Ansätze und adressierter Personengruppen (Studierende, Graduierte, Hochschulbeschäftigte) in wesentlichen Punkten übereinstimmen.

Es herrschte Einigkeit darüber, dass FDM-Kompetenzausbau ein fester Bestandteil der Angebote von Hochschulen sein muss und disziplinübergreifend bereits in die grundständigen Studiengänge gehört. Kompetenzerwerb im Forschungsdatenmanagement basiert auf grundlegender Kenntnis von Daten und ihren Eigenschaften: Was im fachspezifischen Anwendungskontext Daten sein können, und was ein Management von Daten umfassen kann, muss reflektiert und vermittelt werden. Forschungsdatenmanagement ist hierbei als notwendige Voraussetzung eines sicheren Umgangs mit Daten zu verstehen, als pragmatisch fokussierte Umsetzung von Data Literacy, welche im digitalen Zeitalter eine Schlüsselkompetenz darstellt.

Mit Maßnahmen zur Implementierung von FDM-Kompetenzvermittlung reagieren die Hochschulen auf einen Kulturwandel, der als weitreichende Folgeerscheinung der Digitalisierung zu verstehen ist. Als komplexes Thema betrifft die Vermittlung von FDM-Kompetenzen die Hochschule als gesamte Einrichtung. Für die Verankerung von FDM als Thema in der Lehre ist die Zusammenarbeit von Wissenschaft, Infrastruktureinrichtungen sowie Verwaltung notwendig, die ihre jeweilige Expertise und Arbeitsroutine einbringen. Innerhalb der verschiedenen Disziplinen und Fachkulturen herrschen unterschiedliche Sichtweisen auf das Thema vor, die es gleichermaßen zu berücksichtigen gilt. Zur Umsetzung eines solchen Prozesses reicht es nicht aus, dass die Einrichtungen der Hochschule nebeneinander agieren. Sinnvoll sind regelmäßiger Austausch und Kommunikation sowie eine dezidierte Anlaufstelle für Fragen des FDM, welche innerhalb der Hochschule Umsetzung, Beratung und Begleitung deutlich erleichtert. Dazu muss innerhalb der Hochschule für die beschriebene Zusammenarbeit ein klar erkennbares Profil entwickelt werden, das nur mit langfristig gedachten Aufgaben und dauerhaft beschäftigtem Personal umzusetzen ist.


Empfohlene Zitation: Einwächter, Sophie G., Esther Krähwinkel, und Frederik Ostsieker. 2020. „Lessons Learned: Thesen Zur FDM-Kompetenzausbildung: Erkenntnisse Aus Dem Vernetzungstreffen Der Vom BMBF geförderten Projekte EeFDM Jena, FDMentor, FOKUS, PODMAN und UniLLAB Am 30. Und 31. Januar 2019 in Marburg“. Bausteine Forschungsdatenmanagement, Nr. 1 (April), 8-15. https://doi.org/10.17192/bfdm.2020.1.8101.

At the University of Pretoria (UP), Pretoria, South Africa, a team consisting of members of the IT and Library departments has evaluated several research data repository platforms in depth. A list of criteria was developed based on other lists of criteria, a South African research data repository workshop and several internal and external discussions and surveys. Two commercial and four open source research data repositories were short listed for evaluation. By end February 2017 we should know which repository the University will be prepared to fund and implement. The University is also keen to investigate the possibility of forming a consortium with other South African Universities in order to obtain the best research data platform at a good price.

In this paper we provide a case study of the creation of the DCAL Research Data Archive at University College London. In doing so, we assess the various challenges associated with archiving large-scale legacy multimedia research data, given the lack of literature on archiving such datasets. We address issues such as the anonymisation of video research data, the ethical challenges of managing legacy data and historic consent, ownership considerations, the handling of large-size multimedia data, as well as the complexity of multi-project data from a number of researchers and legacy data from eleven years of research. (Accepted 17 Aug 2017.)

With the advent of new technologies integrated with research data management tools has led to a great revolution in the automation and digitization in libraries to provide innovative
services that cater to the modern “smart” users’ needs. At the same time,
adoption of various policy frameworks for managing the data
and workflow systems
along with other Knowledge Organisation Systems (KOS) such as
Metadata, taxonomies, ontologies
that enable the interoperability of research data that enable information retrieval pose challenges to the information professionals. The expectations of the library patrons are increasing day-by-day, as the required information need to be made available on their fingertips within the short span of time. Within this framework, Research Data Management (RDM) plays a crucial role in the information management and dissemination of research data. The paper will first present a brief overview of RDM, detailed literature review regarding the RDM aspects adopted in libraries of the world. It will also describe several tendencies concerning management of repository tools for managing research data and also the showcase the associated challenges in implementing the RDM. This will also depict the proper planned training and skill development for all stakeholders by mentors to train both staff and users are some of the issues that need to be considered to enhance the RDM process. An attempt will be tried to depict and present the suitable policies with a policy framework and workflows with adoption of best practices in RDM will boost the research process in an organisation.

Url: http://dspace.nitrkl.ac.in/dspace/handle/2080/2514