Data management planning and repository demands for qualitative research

KWALON ◽  
2016 ◽  
Vol 21 (1) ◽  
Author(s):  
René van Horik
Keyword(s):  
Data Management ◽  
Research Data ◽  
Digital Data ◽  
Data Repository ◽  
Data Sets ◽  
Data Repositories ◽  
Management Planning ◽  
Research Activities ◽  
Trusted Data ◽  
New Research

Summary Nowadays, research without a role for digital data and data analysis tools is barely possible. As a result, we see an increasing interest in research data management, as this enables the replication of research outcomes and the reuse of research data for new research activities. Data management planning outlines how to handle data, both during research and after the research is completed. Trusted data repositories are places were research data are archived and made available for the long term. This article covers the state of the art concerning data management and data repository demands with a focus on qualitative data sets.

scholarly journals Integration of an Active Research Data System with a Data Repository to Streamline the Research Data Lifecyle: Pure-NOMAD Case Study

2018 ◽  
Vol 12 (2) ◽  
pp. 210-219
Author(s):  
Simone Ivan Conte ◽  
Federica Fina ◽  
Michalis Psalios ◽  
Shyam Ryal ◽  
Tomas Lebl ◽  
...  
Keyword(s):  
Data Management ◽  
Active Phase ◽  
Research Data ◽  
Data Management System ◽  
Data Repository ◽  
Data Repositories ◽  
Human Errors ◽  
Important Challenge ◽  
Active Data ◽  
Active Research

Research funders have introduced requirements that expect researchers to properly manage and publicly share their research data, and expect institutions to put in place services to support researchers in meeting these requirements. So far the general focus of these services and systems has been on addressing the final stages of the research data lifecycle (archive, share and re-use), rather than stages related to the active phase of the cycle (collect/create and analyse). As a result, full integration of active data management systems with data repositories is not yet the norm, making the streamlined transition of data from an active to a published and archived status an important challenge. In this paper we present the integration between an active data management system developed in-house (NOMAD) and Elsevier’s Pure data repository used at our institution, with the aim of offering a simple workflow to facilitate and promote the data deposit process. The integration results in a new data management and publication workflow that helps researchers to save time, minimize human errors related to manually handling files, and further promote data deposit together with collaboration across the institution.

scholarly journals Development of a Pilot Data Management Infrastructure for Biomedical Researchers at University of Manchester – Approach, Findings, Challenges and Outlook of the MaDAM Project

2012 ◽  
Vol 7 (2) ◽  
pp. 110-122 ◽  
Author(s):  
Meik Poschen ◽  
June Finch ◽  
Rob Procter ◽  
Mhorag Goff ◽  
Mary McDerby ◽  
...  
Keyword(s):  
Data Management ◽  
Collaborative Work ◽  
Research Data ◽  
Digital Data ◽  
Complex Data ◽  
Research Groups ◽  
Pilot Data ◽  
New Research ◽  
The University ◽  
University Of Manchester

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.

scholarly journals Progress with implementing the new research data management system at HartRAO

2018 ◽  
Vol 186 ◽  
pp. 12002
Author(s):  
Glenda Coetzer ◽  
Roelf Botha ◽  
Lorette Jacobs
Keyword(s):  
Data Management ◽  
Radio Astronomy ◽  
Management System ◽  
Research Data ◽  
Data Management System ◽  
Research Data Management ◽  
Research Activities ◽  
Fundamental Astronomy ◽  
New Research ◽  
Service Standards

The Hartebeesthoek Radio Astronomy Observatory (HartRAO) participates in global radio astronomy and fundamental astronomy (space geodesy) research activities. Data and data products produced by HartRAO’s expanding range of on-site and off-site instrumentation must be archived and stored at HartRAO and made accessible to the scientific community. The data management and storage systems currently being used for managing fundamental astronomy data are not capable of handling the large volumes of data and have become obsolete. This necessitated the design and implementation of a next-generation Geodetic Research Data Management System (GRDMS), which complies with internationally accepted data service standards. We present the top-level conceptual model of the GRDMS and progress to date with developments of various sub-systems, data structuring and organisation within the sub-systems.

scholarly journals Knowledge management of research data: an initial analysis of Institute of Radiation Protection and Dosimetry

2021 ◽  
Vol 8 (3A) ◽  
Author(s):  
Fernando Barcellos Razuck
Keyword(s):  
Radiation Protection ◽  
Scientific Research ◽  
Technical Information ◽  
Research Process ◽  
Research Data ◽  
Digital Data ◽  
Data Repository ◽  
Data Repositories ◽  
Initial Stage ◽  
By Products

It can be said that scientific community produces research data, as well as uses research data to validate its work. Thus, research data cease to be research products to become informational resources. In this context, digital data repositories play an extremely important role in the scientific research process, since they can be used to share, access, reuse and validate data. In this sense, the informational recognition of research data, in recent years, transformed the view that characterized them as simple by-products of research processes, to the point that researchers, academic institutions and research development agencies begin to understand that these data contribute as a source of informational resources for scientific research and science teaching. Based on this, the objective of this work is to make a preliminary survey of the type of research data generated at the Institute of Radiation Protection and Dosimetry (IRD). For this, an analysis was made of the papers published by the permanent professors of the Post-graduation Program in Radiation Protection and Dosimetry in the last year (2019). It was then generated a table relating the Concentration Areas versus some technical information, regarding the generation of research data. In this sense, the analysis of the data of the IRD consists of a initial stage to assist the creation of the Institute's Digital data repository, which aims to provide the research data in order to be used in other researches. 

scholarly journals Research data management and services: Resources for different data practitioners

2021 ◽  
Vol 45 (3-4) ◽  
Author(s):  
Gilbert Mushi
Keyword(s):  
Data Management ◽  
Developed Countries ◽  
Management Plan ◽  
Research Data ◽  
Data Repository ◽  
Data Repositories ◽  
Research Libraries ◽  
Research Data Management ◽  
Metadata Standards ◽  
Training Resources

The emergence of data-driven research and demands for the establishment of Research Data Management (RDM) has created interest in academic institutions and research organizations globally. Some of the libraries especially in developed countries have started offering RDM services to their communities. Although lagging behind, some academic libraries in developing countries are at the stage of planning or implementing the service. However, the level of RDM awareness is very low among researchers, librarians and other data practitioners. The objective of this paper is to present available open resources for different data practitioners particularly researchers and librarians. It includes training resources for both researchers and librarians, Data Management Plan (DMP) tool for researchers; data repositories available for researchers to freely archive and share their research data to the local and international communities.   A case study with a survey was conducted at the University of Dodoma to identify relevant RDM services so that librarians could assist researchers to make their data accessible to the local and international community. The study findings revealed a low level of RDM awareness among researchers and librarians. Over 50% of the respondent indicated their perceived knowledge as poor in the following RDM knowledge areas; DMP, data repository, long term digital preservation, funders RDM mandates, metadata standards describing data and general awareness of RDM. Therefore, this paper presents available open resources for different data practitioners to improve RDM knowledge and boost the confidence of academic and research libraries in establishing the service.

MATERIAL HANDLING MACHINES AND SYSTEMS – UMI-TWINN PROJECT CONTRIBUTION

2019 ◽  
Vol 12 (1) ◽  
pp. 7-20
Author(s):  
Péter Telek ◽  
Béla Illés ◽  
Christian Landschützer ◽  
Fabian Schenk ◽  
Flavien Massi
Keyword(s):  
Material Handling ◽  
Digital Data ◽  
Flow Process ◽  
Research Directions ◽  
Scientific Excellence ◽  
Research Activities ◽  
New Research ◽  
Eu Project ◽  
The University

Nowadays, the Industry 4.0 concept affects every area of the industrial, economic, social and personal sectors. The most significant changings are the automation and the digitalization. This is also true for the material handling processes, where the handling systems use more and more automated machines; planning, operation and optimization of different logistic processes are based on many digital data collected from the material flow process. However, new methods and devices require new solutions which define new research directions. In this paper we describe the state of the art of the material handling researches and draw the role of the UMi-TWINN partner institutes in these fields. As a result of this H2020 EU project, scientific excellence of the University of Miskolc can be increased and new research activities will be started.

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.

Improvements for research data repositories: The case of text spam

2021 ◽  
pp. 016555152199863
Author(s):  
Ismael Vázquez ◽  
María Novo-Lourés ◽  
Reyes Pavón ◽  
Rosalía Laza ◽  
José Ramón Méndez ◽  
...  
Keyword(s):  
Web Application ◽  
Research Data ◽  
Data Sets ◽  
Data Repositories ◽  
Software Applications ◽  
Public Data ◽  
Protection Mechanisms ◽  
Experimental Protocols ◽  
Learning Research ◽  
Processing Steps

Current research has evolved in such a way scientists must not only adequately describe the algorithms they introduce and the results of their application, but also ensure the possibility of reproducing the results and comparing them with those obtained through other approximations. In this context, public data sets (sometimes shared through repositories) are one of the most important elements for the development of experimental protocols and test benches. This study has analysed a significant number of CS/ML ( Computer Science/ Machine Learning) research data repositories and data sets and detected some limitations that hamper their utility. Particularly, we identify and discuss the following demanding functionalities for repositories: (1) building customised data sets for specific research tasks, (2) facilitating the comparison of different techniques using dissimilar pre-processing methods, (3) ensuring the availability of software applications to reproduce the pre-processing steps without using the repository functionalities and (4) providing protection mechanisms for licencing issues and user rights. To show the introduced functionality, we created STRep (Spam Text Repository) web application which implements our recommendations adapted to the field of spam text repositories. In addition, we launched an instance of STRep in the URL https://rdata.4spam.group to facilitate understanding of this study.

scholarly journals A Mine of Information: Can Sports Analytics Provide Wisdom From Your Data?

2017 ◽  
Vol 12 (7) ◽  
pp. 851-855 ◽  
Author(s):  
Louis Passfield ◽  
James G. Hopker
Keyword(s):  
Web Sites ◽  
Large Data ◽  
Objective Evaluation ◽  
Large Data Sets ◽  
Data Sets ◽  
Competitive Strategies ◽  
Data Repositories ◽  
Sports Analytics ◽  
Sport And Exercise ◽  
New Research

This paper explores the notion that the availability and analysis of large data sets have the capacity to improve practice and change the nature of science in the sport and exercise setting. The increasing use of data and information technology in sport is giving rise to this change. Web sites hold large data repositories, and the development of wearable technology, mobile phone applications, and related instruments for monitoring physical activity, training, and competition provide large data sets of extensive and detailed measurements. Innovative approaches conceived to more fully exploit these large data sets could provide a basis for more objective evaluation of coaching strategies and new approaches to how science is conducted. An emerging discipline, sports analytics, could help overcome some of the challenges involved in obtaining knowledge and wisdom from these large data sets. Examples of where large data sets have been analyzed, to evaluate the career development of elite cyclists and to characterize and optimize the training load of well-trained runners, are discussed. Careful verification of large data sets is time consuming and imperative before useful conclusions can be drawn. Consequently, it is recommended that prospective studies be preferred over retrospective analyses of data. It is concluded that rigorous analysis of large data sets could enhance our knowledge in the sport and exercise sciences, inform competitive strategies, and allow innovative new research and findings.

scholarly journals Archiving South African digital research data: How ready are we?

2016 ◽  
Vol Volume 112 (Number 7/8) ◽  
Author(s):  
Margaret M. Koopman ◽  
Karin de Jager ◽  
◽  
Keyword(s):  
Data Management ◽  
South African ◽  
Academic Research ◽  
Research Data ◽  
Digital Data ◽  
Systematic Research ◽  
Data Archiving ◽  
Research Data Management ◽  
The University ◽  
Digital Research

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.

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