scholarly journals The on-premise data sharing infrastructure e!DAL: Foster FAIR data for faster data acquisition

GigaScience ◽  
2020 ◽  
Vol 9 (10) ◽  
Author(s):  
Daniel Arend ◽  
Patrick König ◽  
Astrid Junker ◽  
Uwe Scholz ◽  
Matthias Lange
Keyword(s):  
Data Management ◽  
Data Storage ◽  
Best Practice ◽  
Research Process ◽  
Research Data ◽  
Primary Data ◽  
Data Repository ◽  
Plant Genomics ◽  
Quality Of Data

Abstract Background The FAIR data principle as a commitment to support long-term research data management is widely accepted in the scientific community. Although the ELIXIR Core Data Resources and other established infrastructures provide comprehensive and long-term stable services and platforms for FAIR data management, a large quantity of research data is still hidden or at risk of getting lost. Currently, high-throughput plant genomics and phenomics technologies are producing research data in abundance, the storage of which is not covered by established core databases. This concerns the data volume, e.g., time series of images or high-resolution hyper-spectral data; the quality of data formatting and annotation, e.g., with regard to structure and annotation specifications of core databases; uncovered data domains; or organizational constraints prohibiting primary data storage outside institional boundaries. Results To share these potentially dark data in a FAIR way and master these challenges the ELIXIR Germany/de.NBI service Plant Genomic and Phenomics Research Data Repository (PGP) implements a “bring the infrastructure to the data” approach, which allows research data to be kept in place and wrapped in a FAIR-aware software infrastructure. This article presents new features of the e!DAL infrastructure software and the PGP repository as a best practice on how to easily set up FAIR-compliant and intuitive research data services. Furthermore, the integration of the ELIXIR Authentication and Authorization Infrastructure (AAI) and data discovery services are introduced as means to lower technical barriers and to increase the visibility of research data. Conclusion The e!DAL software matured to a powerful and FAIR-compliant infrastructure, while keeping the focus on flexible setup and integration into existing infrastructures and into the daily research process.

Research Data Sharing and Reuse Through Open Data

2021 ◽  
pp. 284-306
Author(s):  
Abel Christopher M'kulama ◽  
Akakandelwa Akakandelwa
Keyword(s):  
Data Management ◽  
Data Sharing ◽  
Data Storage ◽  
Mixed Methods Research ◽  
Open Data ◽  
Research Process ◽  
Research Data ◽  
Research Data Management ◽  
Inadequate Knowledge ◽  
Self Administered Questionnaire

Research data management is considered a critical step in the research process among researchers. Researchers are required to submit RDM plans with details about data storage, data sharing, and reuse procedures when submitting research proposals for grants. This chapter presents findings of an investigation into the perceptions and practices of ZARI researchers towards research data management. Mixed methods research using a self-administered questionnaire was adopted for data collection. Fifty-one researchers were sampled and recruited for participation into the study. The study established that the majority of the researchers were not depositing their research data in central repositories; data was kept on individual's devices and was therefore not readily available for sharing. The major challenges being faced by researchers included lack of a policy, lack of a repository, and inadequate knowledge in RDM. The study concludes that research data at ZARI was not being professionally managed. The study recommends for formulation of policies, establishment of repository and staff training.

scholarly journals RESEARCH DATA MANAGEMENT SYSTEM DESIGN (CASE ICT RESEARCH AND HUMAN RESOURCES DEVELOPMENT AGENCY MCIT)

2017 ◽  
Vol 7 (2) ◽  
pp. 143
Author(s):  
Onny Rafizan
Keyword(s):  
Data Management ◽  
Data Storage ◽  
Research Data ◽  
Data Management System ◽  
Primary Data ◽  
Management Information ◽  
User Requirement ◽  
Research Activities ◽  
Data Credibility ◽  
Research Institute

<p class="JGI-AbstractIsi"><span lang="EN">Management of research data is important for every research institute. The absence of activity for centralized data management and data storage within the research institute has the potential to make the research data disappear or not reusable. Data management information system is needed by research institute in order to manage data centrally by paying attention to the business process of research and requirement to the process of storage and sharing of research data. Primary data collection by means of interviews to the technical sources with expertise and direct experience are related to the management of research data, as well as validation of data credibility are tiered to higher research positions (madya and main) and to structural officials who facilitate research activities to obtain business modeling and user requirement. The result of this study is the design of data management information systems in accordance with the conditions of the R &amp; D organizations to facilitate the activities of storage and sharing access the research data.</span></p>

Evaluasi Implementasi Kebijakan Sistem Repositori Ilmiah Nasional (Rin)

2021 ◽  
Vol 5 (2) ◽  
pp. 80
Author(s):  
Vivi Elvina Panjaitan
Keyword(s):  
Qualitative Research ◽  
Research Data ◽  
Data Management System ◽  
Primary Data ◽  
Target Groups ◽  
Research Data Management ◽  
Share Data ◽  
Technical Guidance

ABSTRACTNumbers of management, storage, and preservation of research data problems had been the rationales why national scientific repository (RIN) system was implemented. To measure its success, the present study evaluated, analyzed problems, and provided recommendations using descriptive exploratory qualitative research methods with interviews as the primary data. In terms of the effectiveness, the results showed that the RIN system objectives provided a nationally integrated interoperability research data management system, ensuring long-term archiving and access had been achieved whereas the awareness of researchers to share data and sustainability plans had not been achieved. Based on its efficiency, PDDI LIPI had pursued many activities and strategies. In accordance with its adequacy, the existence of RIN system was able to answer the existing research data problems while the problem of continuity of input of research data and the sustainability of research had not been achieved. In regard to its equalization, RIN system was intended to all professions that carried out research, in which the socialization activities and technical guidance to researchers in relevant institutions were conducted. In coping with its responsiveness, all target groups still could not experience it because the follow-up activity of the target groups after knowing RIN system was still minimum. Hence, it was advised that the target group from both internal LIPI, external LIPI, and PDDI LIPI acted as the implementors. The present study concluded that the implementation of RIN system had not been optimally implemented and still needed improvements. ABSTRAKPermasalahan pengelolaan, penyimpanan, pelestarian data penelitian mendorong dilakukannya implementasi kebijakan sistem RIN. Untuk mengukur keberhasilannya, penulis mengevaluasi, menganalisis permasalahan dan memberikan rekomendasi dengan menggunakan metode penelitan kualitatif deskriptif melalui data primer yaitu wawancara dan data sekunder. Dari efektivitasnya diperoleh hasil bahwa tujuan sistem RIN menyediakan sistem interoperabilitas pengelolaan data penelitian terintegrasi secara nasional, menjamin pengarsipan dan pengaksesan jangka panjang telah tercapai sedangkan kesadaran peneliti untuk berbagi data dan rencana keberlanjutan belum tercapai. Berdasarkan efisiensinya, PDDI LIPI telah mengupayakan banyak kegiatan dan strategi. Berdasarkan kecukupannya, keberadaan sistem RIN mampu menjawab permasalahan data penelitian yang dihadapi sedangkan permasalahan kontinuitas penginputan data penelitian, keberlanjutan penelitian belum tercapai. Berdasarkan pemerataannya, sistem RIN ditujukan kepada seluruh profesi yang melaksanakan penelitian, bukan sekelompok golongan namun kegiatan sosialisasi dan bimbingan teknis lebih banyak kepada peneliti di instansi yang memiliki badan penelitian pengembangan serta perguruan tinggi. Berdasarkan responsivitasnya, belum dapat dirasakan oleh seluruh target sasaran dikarenakan tindaklanjut dari para target sasaran setelah mengenal sistem RIN masih rendah. Maka perlu rekomendasi kepada target sasaran baik dari internal LIPI, eksternal LIPI maupun PDDI LIPI sebagai implementor. Oleh karena itu dapat disimpulkan bahwa implementasi kebijakan sistem RIN belum berjalan dengan optimal dan masih perlu ditingkatkan.

scholarly journals GAMS – An infrastructure for the long-term preservation and publication of research data from the Humanities

2018 ◽  
Vol 71 (1) ◽  
pp. 207-216 ◽  
Author(s):  
Johannes Hubert Stigler ◽  
Elisabeth Steiner
Keyword(s):  
System Architecture ◽  
Academic Research ◽  
Research Data ◽  
Data Repository ◽  
Data Repositories ◽  
Domain Specific ◽  
Preservation Policy ◽  
Long Term Preservation ◽  
Data Centres

Research data repositories and data centres are becoming more and more important as infrastructures in academic research. The article introduces the Humanities’ research data repository GAMS, starting with the system architecture to preservation policy and content policy. Challenges of data centres and repositories and the general and domain-specific approaches and solutions are outlined. Special emphasis lies on the sustainability and long-term perspective of such infrastructures, not only on the technical but above all on the organisational and financial level.

scholarly journals How long can we build it? Ensuring usability of a scientific code base

2021 ◽  
Vol 16 (1) ◽  
pp. 11
Author(s):  
Klaus Rechert ◽  
Jurek Oberhauser ◽  
Rafael Gieschke
Keyword(s):  
Data Management ◽  
Source Code ◽  
Research Data ◽  
Scientific Contribution ◽  
Scientific Publications ◽  
Research Data Management ◽  
Code Base

Software and in particular source code became an important component of scientific publications and henceforth is now subject of research data management.  Maintaining source code such that it remains a usable and a valuable scientific contribution is and remains a huge task. Not all code contributions can be actively maintained forever. Eventually, there will be a significant backlog of legacy source-code. In this article we analyse the requirements for applying the concept of long-term reusability to source code. We use simple case study to identify gaps and provide a technical infrastructure based on emulator to support automated builds of historic software in form of source code.  

scholarly journals FAIR Data Austria - Aligning the Implementation of FAIR Tools and Services

2021 ◽  
Vol 74 (2) ◽  
Author(s):  
Susanne Blumesberger ◽  
Nikos Gänsdorfer ◽  
Raman Ganguly ◽  
Eva Gergely ◽  
Alexander Gruber ◽  
...  
Keyword(s):  
Data Management ◽  
Support Services ◽  
Research Data ◽  
Research Results ◽  
Management Plans ◽  
Project Objectives ◽  
Training And Support

This article gives an overview of the FAIR Data Austria project objectives and current results. In collaboration with our project partners, we work on the development and establishment of tools for managing the lifecycle of research data, including machine-actionable Data Management Plans (maDMPs), repositories for long-term archiving of research results, RDM training and support services, models, and profiles for Data Stewards and FAIR Office Austria.

Designing an information architecture for data management technologies: Introducing the DIAMANT model

2019 ◽  
Vol 52 (2) ◽  
pp. 592-600
Author(s):  
Katarina Blask ◽  
André Förster
Keyword(s):  
Data Management ◽  
Reference Model ◽  
Implementation Process ◽  
Research Process ◽  
Research Data ◽  
Information Architecture ◽  
Central Research ◽  
Research Data Management ◽  
Comprehensive Framework ◽  
The Ideal

Although research institutions take on increased responsibility for providing infrastructures and services around the proper handling of research data, there is no comprehensive framework addressing the ideal conditions of this implementation process. To overcome this gap, we present the DIAMANT model, a reference model aimed at providing an orientation framework for the implementation of research data management guided by the research process itself. It builds upon a central research data management information unit controlling the information flow between all other organizational units involved in research data management. Due to the possibility of outsourcing organizational units, the implementation process is maximally flexible and efficient.

scholarly journals Research Data Services at ETH-Bibliothek

IFLA Journal ◽  
2016 ◽  
Vol 42 (4) ◽  
pp. 284-291 ◽  
Author(s):  
Ana Sesartic ◽  
Matthias Töwe
Keyword(s):  
Life Cycle ◽  
Data Management ◽  
Service Providers ◽  
Scientific Practice ◽  
Research Data ◽  
Data Services ◽  
Mutual Learning ◽  
Data Life Cycle ◽  
Long Term Preservation

The management of research data throughout its life-cycle is both a key prerequisite for effective data sharing and efficient long-term preservation of data. This article summarizes the data services and the overall approach to data management as currently practised at ETH-Bibliothek, the main library of ETH Zürich, the largest technical university in Switzerland. The services offered by service providers within ETH Zürich cover the entirety of the data life-cycle. The library provides support regarding conceptual questions, offers training and services concerning data publication and long-term preservation. As research data management continues to play a steadily more prominent part in both the requirements of researchers and funders as well as curricula and good scientific practice, ETH-Bibliothek is establishing close collaborations with researchers, in order to promote a mutual learning process and tackle new challenges.

scholarly journals Research Data Management Initiatives at University of Edinburgh

2011 ◽  
Vol 6 (2) ◽  
pp. 232-244 ◽  
Author(s):  
Robin Rice ◽  
Jeff Haywood
Keyword(s):  
Data Management ◽  
Data Storage ◽  
Academic Staff ◽  
Research Data ◽  
Lessons Learned ◽  
The Public ◽  
Research Data Management ◽  
Online Tools ◽  
University Of Edinburgh ◽  
Future Direction

During the last decade, national and international attention has been increasingly focused on issues of research data management and access to publicly funded research data. The pressure brought to bear on researchers to improve their data management and data sharing practice has come from research funders seeking to add value to expensive research and solve cross-disciplinary grand challenges; publishers seeking to be responsive to calls for transparency and reproducibility of the scientific record; and the public seeking to gain and re-use knowledge for their own purposes using new online tools. Meanwhile higher education institutions have been rather reluctant to assert their role in either incentivising or supporting their academic staff in meeting these more demanding requirements for research practice, partly due to lack of knowledge as to how to provide suitable assistance or facilities for data storage and curation/preservation. This paper discusses the activities and drivers behind one institution’s recent attempts to address this gap, with reflection on lessons learned and future direction.

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).

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