scholarly journals A survey of the research data management in Austria

2015 ◽  
Author(s):  
Barbara Sánchez Solís

In early 2015, the scientific and artistic-scientific personnel at all 21 universities and three non-university research institutions in Austria received the call to participate in an Austria-wide survey relating to research data. The survey was conducted within the project entitled e-Infrastructures Austria and facilitated the collection of the practical handling of digital data. The findings from this survey form the basis for a consecutive optimization of the infrastructures and services available in this field, in accordance with needs that have been expressed.Solid research data management is the foundation of cooperative and open research and thus of its comprehensibility and verifiability. The subject is equally relevant and current for researchers, funding bodies and senior posts of scientific institutions.The poster visualizes the main findings of this ambitious survey. For the first time, the status quo of domestic data management is displayed in a representative manner crossing all disciplines. This can be used by individual institutions to derive organizational, structural or strategic measures for the development of infrastructures. On the other hand, it allows a co-ordinated, Austria-wide approach for identifying common areas of responsibility and for establishing central services.

Neuroforum ◽  
2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Michael Hanke ◽  
Franco Pestilli ◽  
Adina S. Wagner ◽  
Christopher J. Markiewicz ◽  
Jean-Baptiste Poline ◽  
...  

Abstract Decentralized research data management (dRDM) systems handle digital research objects across participating nodes without critically relying on central services. We present four perspectives in defense of dRDM, illustrating that, in contrast to centralized or federated research data management solutions, a dRDM system based on heterogeneous but interoperable components can offer a sustainable, resilient, inclusive, and adaptive infrastructure for scientific stakeholders: An individual scientist or laboratory, a research institute, a domain data archive or cloud computing platform, and a collaborative multisite consortium. All perspectives share the use of a common, self-contained, portable data structure as an abstraction from current technology and service choices. In conjunction, the four perspectives review how varying requirements of independent scientific stakeholders can be addressed by a scalable, uniform dRDM solution and present a working system as an exemplary implementation.


2016 ◽  
Vol Volume 112 (Number 7/8) ◽  
Author(s):  
Margaret M. Koopman ◽  
Karin de Jager ◽  
◽  

Abstract Digital data archiving and research data management have become increasingly important for institutions in South Africa, particularly after the announcement by the National Research Foundation, one of the principal South African academic research funders, recommending these actions for the research that they fund. A case study undertaken during the latter half of 2014, among the biological sciences researchers at a South African university, explored the state of data management and archiving at this institution and the readiness of researchers to engage with sharing their digital research data through repositories. It was found that while some researchers were already engaged with digital data archiving in repositories, neither researchers nor the university had implemented systematic research data management.


Data ◽  
2019 ◽  
Vol 4 (2) ◽  
pp. 83 ◽  
Author(s):  
Timm Fitschen ◽  
Alexander Schlemmer ◽  
Daniel Hornung ◽  
Henrik tom Wörden ◽  
Ulrich Parlitz ◽  
...  

We present CaosDB, a Research Data Management System (RDMS) designed to ensure seamless integration of inhomogeneous data sources and repositories of legacy data in a FAIR way. Its primary purpose is the management of data from biomedical sciences, both from simulations and experiments during the complete research data lifecycle. An RDMS for this domain faces particular challenges: research data arise in huge amounts, from a wide variety of sources, and traverse a highly branched path of further processing. To be accepted by its users, an RDMS must be built around workflows of the scientists and practices and thus support changes in workflow and data structure. Nevertheless, it should encourage and support the development and observation of standards and furthermore facilitate the automation of data acquisition and processing with specialized software. The storage data model of an RDMS must reflect these complexities with appropriate semantics and ontologies while offering simple methods for finding, retrieving, and understanding relevant data. We show how CaosDB responds to these challenges and give an overview of its data model, the CaosDB Server and its easy-to-learn CaosDB Query Language. We briefly discuss the status of the implementation, how we currently use CaosDB, and how we plan to use and extend it.


2017 ◽  
Vol 35 (2) ◽  
pp. 271-289 ◽  
Author(s):  
Arsev Umur Aydinoglu ◽  
Guleda Dogan ◽  
Zehra Taskin

Purpose The massive increase in research data being produced nowadays has highlighted the importance of research data management (RDM) to science. Research data not only have to be cost effective but also reliable, discoverable, accessible, and reusable. In this regard, the purpose of this paper is to investigate the perceptions and practices of Turkish researchers on the subject of RDM. Design/methodology/approach An online survey was distributed to the academicians in 25 universities in Turkey, and 532 responses were gathered. Findings Results indicate that although Turkish researchers are aware of the benefits of data management, are willing to share their research data with certain groups, and have decent preservation habits, they express that they lack the technical skills and knowledge needed for RDM. In addition, no institutionalized support (staff, training, software, and hardware) is provided to researchers. Research limitations/implications A well-structured data strategy or policy that includes resource allocation (awareness, training, software/hardware) and is supported by Turkish research agencies is required for better data management practices among researchers in Turkey. Originality/value This is the first study that investigates the data practices of Turkish academics who produce around 30,000 scientific articles annually that are indexed by Web of Science. It contributes to the growing literature on RDM.


2015 ◽  
Author(s):  
Karlheinz Pappenberger

See video of the presentation.On 17th July 2015 the Ministry of Science, Research and the Arts for Baden-Wuerttemberg, Germany, invited national experts to the presentation of the final report of the ‘bwFDM communities’ project. This 18 month project was launched at the beginning of 2014 to evaluate the needs of services and the support that libraries and IT service centres should offer researchers in the area of research data management. Full-time key project staff had been established at all 9 universities in the state of Baden-Wuerttemberg to conduct semi-structured personal interviews of all research groups working with research data (in a broad sense including all areas of science, social science and humanities) and to document them in the form of user stories. 627 interviews have been conducted and more than 2,500 user stories could be extracted, showing the wide range of needs and wishes articulated by researchers. On this basis issues of importance and requirements had be identified, categorised in 18 different groups and finalised into an analysis of the status quo and recommendations for concrete action plans. The results cover the areas ‘general requirements and policy framework’, ‘data collection and data sharing’, ‘technical framework and virtual research environments’, ‘preservation’,  ‘IT infrastructure and IT support’, ‘licencing’ and ‘Open Science’.The presentation will give an overview of the project results and will highlight the roles libraries and IT service centres are expected to play from the researcher´s point of view.As the final report to the Ministry contributes to a comprehensive research data management strategy for the State of Baden-Wuerttemberg, the presentation will also point out the status of the federal strategy in RDM.


Author(s):  
Frank Oliver Glöckner ◽  
Michael Diepenbroek

Background: The NFDI process in Germany The digital revolution is fundamentally transforming research data and methods. Mastering this transformation poses major challenges for stakeholders in the domains of science and policy. The process of digitalisation creates immense opportunities, but it must be structured proactively. To this end, the establishment of effective governance mechanisms for research data management (RDM) is of fundamental importance and will be one key driver for successful research and innovation in the future. In 2016 the German Council for Information Infrastructures (RfII) recommended the establishment of a “Nationale Forschungsdateninfrastruktur” (National Research Data Infrastructure, or NFDI), which will serve as the backbone for research data management in Germany. The NFDI should be implemented as a dynamic national collaborative network that grows over time and is composed of various specialised nodes (consortia). The talk will provide a short overview of the status and objectives of the NFDI. It will commence with a description of the goals of the NFDI4BioDiversity consortium which was established for the targeted support of the biodiversity community with data management. The NFDI4BioDiversity Consortium: Biodiversity, Ecology & Environmental Data Biodiversity is more than just the diversity of living species. It includes genetic diversity, functional diversity, interactions and the diversity of whole ecosystems. Mankind continuous to dramatically impact the earth’s ecosystem: species dying-out genetic diversity as well as whole ecosystems are endangered or already lost. Next to the loss of charismatic species and conspicuous change in ecosystems, we are experiencing a quiet loss of common species which together has captured high level policy attention. This has impacts on vital ecosystem services that provide the foundation of human well-being. A general understanding of the status, trends and drivers of the biodiversity on earth is urgently needed to devise conservation responses. Besides the fact that data are often scattered across repositories or not accessible at all, the main challenge for integrative studies is the heterogeneity of measurements and observation types, combined with a substantial lack of documentation. This leads to inconsistencies and incompatibilities in data structures, interfaces and semantics and thus hinders the re-usability of data to answer scientifically and socially relevant questions. Synthesis as well as hypothesis generation will only proceed when data are compliant with the FAIR (Findable, Accessible, Interoperable and Re-usable) data principles. Over the last five years these key challenges have been addressed by the DFG funded German Federation for Biological Data (GFBio) project. GFBio encompasses technical, organizational, financial, and community aspects to raise awareness for research data management in biodiversity research and environmental sciences. To foster sustainability across this federated infrastructure the not-for-profit association “Gesellschaft für biologische Daten e.V. (GFBio e.V.)” has been set up in 2016 as an independent legal entity. NFDI4BioDiversity builds on the experience and established user community of GFBio and takes advantage of GFBio e.V. GFBio already comprises data centers for nucleotide and environmental data as well as the seven well-established data centers of Germany´s largest natural science research facilities, museums and world’s most diverse microbiological resource collection. The network is now extended to include the network of botanical gardens and the largest collections of crop plants and their wild relatives. All collections together host more than 75% of all museum objects (150 millions) in Germany and >80% of all described microbial species. They represent the biggest and internationally-relevant data repositories. NFDI4BioDiversity will extend its community engagement at the science-society-policy interface by including farm animal biology, crop sciences, biodiversity monitoring and citizen science, as well as systems biology encompassing world-leading tools and collections for FAIR data management. Partners of the German Network for Bioinformatics Infrastructure (de.NBI) provide large scale data analysis and storage capacities in the cloud, as well as extensive continuous training and education experiences. Dedicated personnel will be responsible for the mutual exchange of data and experiences with NFDI4Life-Umbrella,NFDI4Earth, NFDI4Chem, NFDI4Health and beyond. As digitalization and liberation of data proceeds, NFDI4BioDiversity will foster community standards, quality management and documentation as well as the harmonization and synthesis of heterogeneous data. It will pro-actively engage the user community to build a coordinated data management platform for all types of biodiversity data as a dedicated added value service for all users of NFDI.


2015 ◽  
Author(s):  
Paolo Budroni ◽  
Barbara Sánchez Solís

See video of the presentation.At the start of 2015, scientific and artistic-scientific personnel of all 21 universities and three non-university research institutions in Austria were given the call to participate in an Austria-wide survey focusing on research data. The survey was conducted within the framework of the e-Infrastructures Austria (www.e-infrastructures.at) project funded by the Austrian Federal Ministry of Science, Research and Economics (BMWFW) and facilitates the evaluation of the actual, practical handling of digital data.The participants were asked about the following topics: data types and formats, data archiving, backup and loss, ethical and legal aspects, accessibility and reuse as well as infrastructure and services. The findings form the basis for a consecutive optimization of the e-infrastructure and services available in this area in accordance with the needs they have expressed.Solid research data management is the foundation for cooperative, open research and thus for their comprehensibility and verifiability. The issue is equally relevant and up-to-date for researchers, funding bodies and senior posts of scientific institutions, which is currently being demonstrated by the pilot for research data from the European Commission.The lecture provides insight into the planning, implementation and evaluation of this ambitious undertaking and presents the main results that will have an impact at national level. For the first time, the status quo of domestic data management is being presented in a manner that represents all disciplines. Organizational, structural and strategic measures for the development of e-infrastructures for individual institutions can then be derived using this data. In addition, it is possible through the co-ordinated, Austria-wide approach to identify common areas of responsibility and to establish central services.


Author(s):  
Yuhong Cui

Research Data is acknowledged as constituting elements of the big data landscape and currency of science. With the rise of the open science movement and data sharing policies, research data management has been an emerging practice among domain-specific science and library and information science, while academic libraries have become deeply involved in the development of principles and best practices for managing data for long-term use. Research data management practices in China have a much shorter history and face more challenges. This paper is to explore the development of research data management in China across different disciplines. A conceptual framework of Research Data Management for Development (RDM4D) is proposed to demonstrate the status of data sharing policies, data repositories and libraries actions within three dimensions of societies, technology and humanity in China. Our goal is to bridge the gap between China and other countries and explore which are the proper actions for Chinese academic libraries.


Author(s):  
Fabian Cremer ◽  
Silvia Daniel ◽  
Marina Lemaire ◽  
Katrin Moeller ◽  
Matthias Razum ◽  
...  

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