scholarly journals Research Data Management at 9 Universities in Baden-Wuerttemberg, Germany. The Results from the Final Report of the bwFDM Communities Project

2015 ◽  
Author(s):  
Karlheinz Pappenberger
Keyword(s):  
Data Management ◽  
Research Data ◽  
The State ◽  
Final Report ◽  
Full Time ◽  
It Service ◽  
Research Data Management ◽  
User Stories ◽  
Wide Range ◽  
The Status

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.

scholarly journals bwFDM Communities – a Research Data Management Initiative in the County of Baden-Wuerttemberg, Germany

2014 ◽  
Author(s):  
Karlheinz Pappenberger
Keyword(s):  
Data Management ◽  
Science Research ◽  
Research Data ◽  
Point Of View ◽  
Data Repository ◽  
Full Time ◽  
It Service ◽  
Research Data Management ◽  
Concrete Action ◽  
The University

>> See video of presentation (33 min.)On 29th July 2014 the Ministry of Science, Research and the Arts of Baden-Wuerttemberg, Germany, has launched an e-science initiative to build up a powerful, efficient and innovative information infrastructure for all universities, research institutions and universities of applied science of the county of southwest Germany. With the overall budget of 3.7 million euro action plans within the five areas licensing, digitalization, research data management, open access and virtual research environments shall be worked out within the next years.Within this framework an 18-month project has been launched at the beginning of 2014 to evaluate the needs of services and support libraries and IT service centres should offer for researchers in the area of research data management. In this “bwFDM communities” named project full time key accounters have been established at all 9 universities of the county (Freiburg, Heidelberg, Hohenheim, Karlsruhe, Konstanz, Mannheim, Stuttgart, Tuebingen and Ulm; among them national and international highly ranked universities). The task of the key accounters is to identity concrete needs and requirements of all research groups working with research data (in a broad sense including all areas of science, social science and humanities) at each of the nine universities as well as possible solutions by conducting semi-structured personal interviews and documenting them in the form of user stories. As a result issues of importance and requirements will be identified, categorized and finalized to recommendations for concrete action plans.The presentation will give an overview of the first results of the project, thereby also highlighting the roles libraries and IT service centres are expected to play from the researcher´s point of view. Furthermore the presentation will point out the response of the University of Konstanz Library to the rising awareness of the importance of research data within the University Executive, showing the special efforts the University of Konstanz Library undertakes to support researchers in their research data management so far and to build up more and more expertise in the area of research data management. One step had been the set-up of a disciplinary data repository in the field of ornithology (Movebank data repository).

scholarly journals NFDI4Chem - Towards a National Research Data Infrastructure for Chemistry in Germany

2020 ◽  
Vol 6 ◽  
Author(s):  
Christoph Steinbeck ◽  
Oliver Koepler ◽  
Felix Bach ◽  
Sonja Herres-Pawlis ◽  
Nicole Jung ◽  
...  
Keyword(s):  
Data Management ◽  
Data Science ◽  
Open Data ◽  
Research Data ◽  
Data Standards ◽  
Data Repositories ◽  
Data Infrastructure ◽  
Research Data Management ◽  
Wide Range ◽  
Chemistry Community

The vision of NFDI4Chem is the digitalisation of all key steps in chemical research to support scientists in their efforts to collect, store, process, analyse, disclose and re-use research data. Measures to promote Open Science and Research Data Management (RDM) in agreement with the FAIR data principles are fundamental aims of NFDI4Chem to serve the chemistry community with a holistic concept for access to research data. To this end, the overarching objective is the development and maintenance of a national research data infrastructure for the research domain of chemistry in Germany, and to enable innovative and easy to use services and novel scientific approaches based on re-use of research data. NFDI4Chem intends to represent all disciplines of chemistry in academia. We aim to collaborate closely with thematically related consortia. In the initial phase, NFDI4Chem focuses on data related to molecules and reactions including data for their experimental and theoretical characterisation. This overarching goal is achieved by working towards a number of key objectives: Key Objective 1: Establish a virtual environment of federated repositories for storing, disclosing, searching and re-using research data across distributed data sources. Connect existing data repositories and, based on a requirements analysis, establish domain-specific research data repositories for the national research community, and link them to international repositories. Key Objective 2: Initiate international community processes to establish minimum information (MI) standards for data and machine-readable metadata as well as open data standards in key areas of chemistry. Identify and recommend open data standards in key areas of chemistry, in order to support the FAIR principles for research data. Finally, develop standards, if there is a lack. Key Objective 3: Foster cultural and digital change towards Smart Laboratory Environments by promoting the use of digital tools in all stages of research and promote subsequent Research Data Management (RDM) at all levels of academia, beginning in undergraduate studies curricula. Key Objective 4: Engage with the chemistry community in Germany through a wide range of measures to create awareness for and foster the adoption of FAIR data management. Initiate processes to integrate RDM and data science into curricula. Offer a wide range of training opportunities for researchers. Key Objective 5: Explore synergies with other consortia and promote cross-cutting development within the NFDI. Key Objective 6: Provide a legally reliable framework of policies and guidelines for FAIR and open RDM.

scholarly journals CaosDB—Research Data Management for Complex, Changing, and Automated Research Workflows

Data ◽  
2019 ◽  
Vol 4 (2) ◽  
pp. 83 ◽  
Author(s):  
Timm Fitschen ◽  
Alexander Schlemmer ◽  
Daniel Hornung ◽  
Henrik tom Wörden ◽  
Ulrich Parlitz ◽  
...  
Keyword(s):  
Data Management ◽  
Data Model ◽  
Query Language ◽  
Research Data ◽  
Data Management System ◽  
Biomedical Sciences ◽  
Seamless Integration ◽  
Research Data Management ◽  
The Status ◽  
Data Acquisition And Processing

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.

Towards a Specialized Environmental Data Portal: Challenges and Opportunities

2020 ◽  
Author(s):  
Ionut Iosifescu-Enescu ◽  
Gian-Kasper Plattner ◽  
Dominik Haas-Artho ◽  
David Hanimann ◽  
Konrad Steffen
Keyword(s):  
Data Management ◽  
Scientific Information ◽  
Central Element ◽  
Research Data ◽  
Environmental Data ◽  
Research Data Management ◽  
Environmental Domain ◽  
Federal Institute ◽  
Wide Range ◽  
Data Portal

<p>EnviDat – www.envidat.ch – is the institutional Environmental Data portal of the Swiss Federal Institute for Forest, Snow and Landscape Research WSL. Launched in 2012 as a small project to explore possible solutions for a generic WSL-wide data portal, it has since evolved into a strategic initiative at the institutional level tackling issues in the broad areas of Open Research Data and Research Data Management. EnviDat demonstrates our commitment to accessible research data in order to advance environmental science.</p><p>EnviDat actively implements the FAIR (Findability, Accessibility, Interoperability and Reusability) principles. Core EnviDat research data management services include the registration, integration and hosting of quality-controlled, publication-ready data from a wide range of terrestrial environmental systems, in order to provide unified access to WSL’s environmental monitoring and research data. The registration of research data in EnviDat results in the formal publication with permanent identifiers (EnviDat own PIDs as well as DOIs) and the assignment of appropriate citation information.</p><p>Innovative EnviDat features that contribute to the global system of modern documentation and exchange of scientific information include: (i) a DataCRediT mechanism designed for specifying data authorship (Collection, Validation, Curation, Software, Publication, Supervision), (ii) the ability to enhance published research data with additional resources, such as model codes and software, (iii) in-depth documentation of data provenance, e.g., through a dataset description as well as related publications and datasets, (iv) unambiguous and persistent identifiers for authors (ORCIDs) and, in the medium-term, (v) a decentralized “peer-review” data publication process for safeguarding the quality of available datasets in EnviDat.</p><p>More recently, the EnviDat development has been moving beyond the set of core features expected from a research data management portal with a built-in publishing repository. This evolution is driven by the diverse set of researchers’ requirements for a specialized environmental data portal that formally cuts across the five WSL research themes forest, landscape, biodiversity, natural hazards, and snow and ice, and that concerns all research units and central IT services.</p><p>Examples of such recent requirements for EnviDat include: (i) immediate access to data collected by automatic measurements stations, (ii) metadata and data visualization on charts and maps, with geoservices for large geodatasets, and (iii) progress towards linked open data (LOD) with curated vocabularies and semantics for the environmental domain.</p><p>There are many challenges associated with the developments mentioned above. However, they also represent opportunities for further improving the exchange of scientific information in the environmental domain. Especially geospatial technologies have the potential to become a central element for any specialized environmental data portal, triggering the convergence between publishing repositories and geoportals. Ultimately, these new requirements demonstrate the raised expectations that institutions and researchers have towards the future capabilities of research data portals and repositories in the environmental domain. With EnviDat, we are ready to take up these challenges over the years to come.</p>

scholarly journals The Data Management Skills Support Initiative: Synthesising Postgraduate Training in Research Data Management

2012 ◽  
Vol 7 (2) ◽  
pp. 101-109 ◽  
Author(s):  
Laura Molloy ◽  
Kellie Snow
Keyword(s):  
Data Management ◽  
Management Training ◽  
Skills Training ◽  
Research Data ◽  
Management Skills ◽  
Research Information ◽  
Research Data Management ◽  
Researcher Development ◽  
Development Framework ◽  
Wide Range

This paper will describe the efforts and findings of the JISC Data Management Skills Support Initiative (‘DaMSSI’). DaMSSI was co-funded by the JISC Managing Research Data programme and the Research Information Network (RIN), in partnership with the Digital Curation Centre, to review, synthesise and augment the training offerings of the JISC Research Data Management Training Materials (‘RDMTrain’) projects.DaMSSI tested the effectiveness of the Society of College, National and University Libraries’ Seven Pillars of Information Literacy model (SCONUL, 2011), and Vitae’s Researcher Development Framework (‘Vitae RDF’) for consistently describing research data management (‘RDM’) skills and skills development paths in UK HEI postgraduate courses.With the collaboration of the RDMTrain projects, we mapped individual course modules to these two models and identified basic generic data management skills alongside discipline-specific requirements. A synthesis of the training outputs of the projects was then carried out, which further investigated the generic versus discipline-specific considerations and other successful approaches to training that had been identified as a result of the projects’ work. In addition we produced a series of career profiles to help illustrate the fact that data management is an essential component – in obvious and not-so-obvious ways – of a wide range of professions.We found that both models had potential for consistently and coherently describing data management skills training and embedding this within broader institutional postgraduate curricula. However, we feel that additional discipline-specific references to data management skills could also be beneficial for effective use of these models. Our synthesis work identified that the majority of core skills were generic across disciplines at the postgraduate level, with the discipline-specific approach showing its value in engaging the audience and providing context for the generic principles.Findings were fed back to SCONUL and Vitae to help in the refinement of their respective models, and we are working with a number of other projects, such as the DCC and the EC-funded Digital Curator Vocational Education Europe (DigCurV2) initiative, to investigate ways to take forward the training profiling work we have begun.

scholarly journals A survey of the research data management in Austria

2015 ◽  
Author(s):  
Barbara Sánchez Solís
Keyword(s):  
Data Management ◽  
Research Data ◽  
Digital Data ◽  
Research Data Management ◽  
Survey Form ◽  
Strategic Measures ◽  
The Status ◽  
The Subject ◽  
Central Services ◽  
First Time

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.

scholarly journals NFDI4BioDiversity: Biodiversity, ecology and environmental data

2019 ◽  
Vol 3 ◽  
Author(s):  
Frank Oliver Glöckner ◽  
Michael Diepenbroek
Keyword(s):  
Genetic Diversity ◽  
Data Management ◽  
Data Centers ◽  
Research Data ◽  
Biological Data ◽  
Environmental Data ◽  
User Community ◽  
Management Platform ◽  
Research Data Management ◽  
The Status

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.

scholarly journals NRDC Data Visualization Web Suite

10.29007/rkqh ◽  
2020 ◽  
Author(s):  
Andrew Muñoz ◽  
Frederick Harris ◽  
Sergiu Dascalu
Keyword(s):  
Data Management ◽  
Data Visualization ◽  
Data Center ◽  
Web Application ◽  
Web Applications ◽  
Research Data ◽  
The State ◽  
Environmental Data ◽  
High Rate ◽  
Research Data Management

The Nevada Research Data Center (NRDC) is a research data management center that collects sensor-based data from various locations throughout the state of Nevada. The measurements collected are specifically environmental data, which are used in cross-disciplinary research across different facilities. Since data is being collected at a high rate, it is necessary to be able to visualize the data quickly and efficiently. This paper discusses in detail a web application that can be used by researchers to make visualizations that can help in data comparisons. While there exist other web applications that allows researchers to visualize the data, this project expands on that idea by allowing researchers the ability to not only visualize the data but also make comparisons and predictions.

scholarly journals Research Data Management in Austria – A manageable task for Austrian research institutions?

2015 ◽  
Author(s):  
Paolo Budroni ◽  
Barbara Sánchez Solís
Keyword(s):  
Data Management ◽  
National Level ◽  
Science Research ◽  
Legal Aspects ◽  
Research Data ◽  
Research Institutions ◽  
Data Types ◽  
Data Archiving ◽  
Research Data Management ◽  
The Status

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.

Research Data Management

2016 ◽  
pp. 184-195
Author(s):  
Yuhong Cui
Keyword(s):  
Data Management ◽  
Data Sharing ◽  
Academic Libraries ◽  
Management Practices ◽  
Information Science ◽  
Open Science ◽  
Research Data ◽  
Three Dimensions ◽  
Research Data Management ◽  
The Status

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.

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