Archives des mots-clés : research data management

Enhancing the Research Data Management of Computer-Based Educational Assessments in Switzerland

Posté le par

Authors : Catharina Wasner, Ingo Barkow, Fabian Odoni

Since 2006 the education authorities in Switzerland have been obliged by the Constitution to harmonize important benchmarks in the educational system throughout Switzerland. With the development of national educational objectives in four disciplines an important basis for the implementation of this constitutional mandate was created.

In 2013 the Swiss National Core Skills Assessment Program (in German: ÜGK – Überprüfung der Grundkompetenzen) was initiated to investigate the skills of students, starting with three of four domains: mathematics, language of teaching and first foreign language in grades 2, 6 and 9. ÜGK uses a computer-based test and a sample size of 25.000 students per year.

A huge challenge for computer-based educational assessment is the research data management process. Data from several different systems and tools existing in different formats has to be merged to obtain data products researchers can utilize.

The long term preservation has to be adapted as well. In this paper, we describe our current processes and data sources as well as our ideas for enhancing the data management.

URL : Enhancing the Research Data Management of Computer-Based Educational Assessments in Switzerland

DOI : http://doi.org/10.5334/dsj-2018-018

Developing research data management services and support for researchers

Posté le par

Authors : Laure Perrier, Leslie Barnes

This mixed method study determined the essential tools and services required for research data management to aid academic researchers in fulfilling emerging funding agency and journal requirements. Focus groups were conducted and a rating exercise was designed to rank potential services.

Faculty conducting research at the University of Toronto were recruited; 28 researchers participated in four focus groups from June– August 2016. Two investigators independently coded the transcripts from the focus groups and identified four themes: 1) seamless infrastructure, 2) data security, 3) developing skills and knowledge, and 4) anxiety about releasing data.

Researchers require assistance with the secure storage of data and favour tools that are easy to use. Increasing knowledge of best practices in research data management is necessary and can be supported by the library using multiple strategies.

These findings help our library identify and prioritize tools and services in order to allocate resources in support of research data management on campus.

URL : Developing research data management services and support for researchers

DOI : https://doi.org/10.21083/partnership.v13i1.4115

Modelling the Research Data Lifecycle

Posté le par

Author: Stacy T Kowalczyk

This paper develops and tests a lifecycle model for the preservation of research data by investigating the research practices of scientists. This research is based on a mixed-method approach.

An initial study was conducted using case study analytical techniques; insights from these case studies were combined with grounded theory in order to develop a novel model of the Digital Research Data Lifecycle.

A broad-based quantitative survey was then constructed to test and extend the components of the model. The major contribution of these research initiatives are the creation of the Digital Research Data Lifecycle, a data lifecycle that provides a generalized model of the research process to better describe and explain both the antecedents and barriers to preservation.

The antecedents and barriers to preservation are data management, contextual metadata, file formats, and preservation technologies. The availability of data management support and preservation technologies, the ability to create and manage contextual metadata, and the choices of file formats all significantly effect the preservability of research data.

URL : Modelling the Research Data Lifecycle

DOI : https://doi.org/10.2218/ijdc.v12i2.429

A Data-Driven Approach to Appraisal and Selection at a Domain Data Repository

Posté le par

Authors : Amy M Pienta, Dharma Akmon, Justin Noble, Lynette Hoelter, Susan Jekielek

Social scientists are producing an ever-expanding volume of data, leading to questions about appraisal and selection of content given finite resources to process data for reuse. We analyze users’ search activity in an established social science data repository to better understand demand for data and more effectively guide collection development.

By applying a data-driven approach, we aim to ensure curation resources are applied to make the most valuable data findable, understandable, accessible, and usable. We analyze data from a domain repository for the social sciences that includes over 500,000 annual searches in 2014 and 2015 to better understand trends in user search behavior.

Using a newly created search-to-study ratio technique, we identified gaps in the domain data repository’s holdings and leveraged this analysis to inform our collection and curation practices and policies.

The evaluative technique we propose in this paper will serve as a baseline for future studies looking at trends in user demand over time at the domain data repository being studied with broader implications for other data repositories.

URL : A Data-Driven Approach to Appraisal and Selection at a Domain Data Repository

DOI : https://doi.org/10.2218/ijdc.v12i2.500

A Research Graph dataset for connecting research data repositories using RD-Switchboard

Posté le par

Authors : Amir Aryani, Marta Poblet, Kathryn Unsworth, Jingbo Wang, Ben Evans, Anusuriya Devaraju, Brigitte Hausstein, Claus-Peter Klas, Benjamin Zapilko, Samuele Kaplun

This paper describes the open access graph dataset that shows the connections between Dryad, CERN, ANDS and other international data repositories to publications and grants across multiple research data infrastructures.

The graph dataset was created using the Research Graph data model and the Research Data Switchboard (RD-Switchboard), a collaborative project by the Research Data Alliance DDRI Working Group (DDRI WG) with the aim to discover and connect the related research datasets based on publication co-authorship or jointly funded grants.

The graph dataset allows researchers to trace and follow the paths to understanding a body of work. By mapping the links between research datasets and related resources, the graph dataset improves both their discovery and visibility, while avoiding duplicate efforts in data creation.

Ultimately, the linked datasets may spur novel ideas, facilitate reproducibility and re-use in new applications, stimulate combinatorial creativity, and foster collaborations across institutions.

URL : A Research Graph dataset for connecting research data repositories using RD-Switchboard

Alternative location : https://www.nature.com/articles/sdata201899

Curating Humanities Research Data: Managing Workflows for Adjusting a Repository Framework

Posté le par

Author : Hagen Peukert

Handling heterogeneous data, subject to minimal costs, can be perceived as a classic management problem. The approach at hand applies established managerial theorizing to the field of data curation.

It is argued, however, that data curation cannot merely be treated as a standard case of applying management theory in a traditional sense. Rather, the practice of curating humanities research data, the specifications and adjustments of the model suggested here reveal an intertwined process, in which knowledge of both strategic management and solid information technology have to be considered.

Thus, suggestions on the strategic positioning of research data, which can be used as an analytical tool to understand the proposed workflow mechanisms, and the definition of workflow modules, which can be flexibly used in designing new standard workflows to configure research data repositories, are put forward.

URL : Curating Humanities Research Data: Managing Workflows for Adjusting a Repository Framework

DOI : https://doi.org/10.2218/ijdc.v12i2.571

Are the FAIR Data Principles Fair?

Posté le par

Authors : Alastair Dunning, Madeleine de Smaele, Jasmin Böhmer

This practice paper describes an ongoing research project to test the effectiveness and relevance of the FAIR Data Principles. Simultaneously, it will analyse how easy it is for data archives to adhere to the principles. The research took place from November 2016 to January 2017, and will be underpinned with feedback from the repositories.

The FAIR Data Principles feature 15 facets corresponding to the four letters of FAIR – Findable, Accessible, Interoperable, Reusable. These principles have already gained traction within the research world.

The European Commission has recently expanded its demand for research to produce open data. The relevant guidelines1are explicitly written in the context of the FAIR Data Principles. Given an increasing number of researchers will have exposure to the guidelines, understanding their viability and suggesting where there may be room for modification and adjustment is of vital importance.

This practice paper is connected to a dataset (Dunning et al.,2017) containing the original overview of the sample group statistics and graphs, in an Excel spreadsheet. Over the course of two months, the web-interfaces, help-pages and metadata-records of over 40 data repositories have been examined, to score the individual data repository against the FAIR principles and facets.

The traffic-light rating system enables colour-coding according to compliance and vagueness. The statistical analysis provides overall, categorised, on the principles focussing, and on the facet focussing results.

The analysis includes the statistical and descriptive evaluation, followed by elaborations on Elements of the FAIR Data Principles, the subject specific or repository specific differences, and subsequently what repositories can do to improve their information architecture.

URL : Are the FAIR Data Principles Fair?

DOI: https://doi.org/10.2218/ijdc.v12i2.567