Étiquette : research data

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How Important is Data Curation? Gaps and Opportunities for Academic Libraries

Authors: Lisa R Johnston, Jacob Carlson, Cynthia Hudson-Vitale, Heidi Imker, Wendy Kozlowski, Robert Olendorf, Claire Stewart

INTRODUCTION

Data curation may be an emerging service for academic libraries, but researchers actively “curate” their data in a number of ways—even if terminology may not always align. Building on past userneeds assessments performed via survey and focus groups, the authors sought direct input from researchers on the importance and utilization of specific data curation activities.

METHODS

Between October 21, 2016, and November 18, 2016, the study team held focus groups with 91 participants at six different academic institutions to determine which data curation activities were most important to researchers, which activities were currently underway for their data, and how satisfied they were with the results.

RESULTS

Researchers are actively engaged in a variety of data curation activities, and while they considered most data curation activities to be highly important, a majority of the sample reported dissatisfaction with the current state of data curation at their institution.

DISCUSSION

Our findings demonstrate specific gaps and opportunities for academic libraries to focus their data curation services to more effectively meet researcher needs.

CONCLUSION

Research libraries stand to benefit their users by emphasizing, investing in, and/or heavily promoting the highly valued services that may not currently be in use by many researchers.

URL : How Important is Data Curation? Gaps and Opportunities for Academic Libraries

DOI : http://doi.org/10.7710/2162-3309.2198

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

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

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Are the FAIR Data Principles Fair?

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

 

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

Authors : Simone Ivan Conte, Federica Fina, Michalis Psalios, Shyam Ryal, Tomas Lebl, Anna Clements

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.

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

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Practices of research data curation in institutional repositories: A qualitative view from repository staff

Authors : Dong Joon Lee, Besiki Stvilia

The importance of managing research data has been emphasized by the government, funding agencies, and scholarly communities. Increased access to research data increases the impact and efficiency of scientific activities and funding.

Thus, many research institutions have established or plan to establish research data curation services as part of their Institutional Repositories (IRs). However, in order to design effective research data curation services in IRs, and to build active research data providers and user communities around those IRs, it is essential to study current data curation practices and provide rich descriptions of the sociotechnical factors and relationships shaping those practices.

Based on 13 interviews with 15 IR staff members from 13 large research universities in the United States, this paper provides a rich, qualitative description of research data curation and use practices in IRs.

In particular, the paper identifies data curation and use activities in IRs, as well as their structures, roles played, skills needed, contradictions and problems present, solutions sought, and workarounds applied.

The paper can inform the development of best practice guides, infrastructure and service templates, as well as education in research data curation in Library and Information Science (LIS) schools.

URL : Practices of research data curation in institutional repositories: A qualitative view from repository staff

DOI : https://doi.org/10.1371/journal.pone.0173987

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Setting up a National Research Data Curation Service for Qatar: Challenges and Opportunities

Authors : Arif Shaon, Armin Straube, Krishna Roy Chowdhury

Over the past decade, Qatar has been making considerable progress towards developing a sustainable research culture for the nation. The main driver behind Qatar’s progress in research and innovation is Qatar Foundation for Education, Science, and Community Development (QF), a private, non-profit organization that aims to utilise research as a catalyst for expanding, diversifying and improving the country’s economy, health and environment.

While this has resulted in a significant growth in the number of research publications produced by Qatari researchers in recent years, a nationally co-ordinated approach is needed to address some of the emerging but increasingly important aspects of research data curation, such as management and publication of research data as important outputs, and their long-term digital preservation.

Qatar National Library (QNL), launched in November 2012 under the umbrella of QF, aims to establish itself as a centre of excellence in Qatar for research data management, curation and publishing to address the research data-related needs of Qatari researchers and academics.

This paper describes QNL’s approach towards establishing a national research data curation service for Qatar, highlighting the associated opportunities and key challenges.

URL : Setting up a National Research Data Curation Service for Qatar: Challenges and Opportunities

Alternative location : http://www.ijdc.net/article/view/515

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The State of Assessing Data Stewardship Maturity – An Overview

Author : Ge Peng

Data stewardship encompasses all activities that preserve and improve the information content, accessibility, and usability of data and metadata. Recent regulations, mandates, policies, and guidelines set forth by the U.S. government, federal other, and funding agencies, scientific societies and scholarly publishers, have levied stewardship requirements on digital scientific data.

This elevated level of requirements has increased the need for a formal approach to stewardship activities that supports compliance verification and reporting. Meeting or verifying compliance with stewardship requirements requires assessing the current state, identifying gaps, and, if necessary, defining a roadmap for improvement.

This, however, touches on standards and best practices in multiple knowledge domains. Therefore, data stewardship practitioners, especially these at data repositories or data service centers or associated with data stewardship programs, can benefit from knowledge of existing maturity assessment models.

This article provides an overview of the current state of assessing stewardship maturity for federally funded digital scientific data. A brief description of existing maturity assessment models and related application(s) is provided.

This helps stewardship practitioners to readily obtain basic information about these models. It allows them to evaluate each model’s suitability for their unique verification and improvement needs.

URL : The State of Assessing Data Stewardship Maturity – An Overview

DOI : http://doi.org/10.5334/dsj-2018-007