scholarly journals The Informatics Transform: Re-Engineering Libraries for the Data Decade

2012 ◽  
Vol 7 (1) ◽  
pp. 126-138 ◽  
Author(s):  
Liz Lyon
Keyword(s):  
Data Management ◽  
Support Services ◽  
Research Data ◽  
Institutional Research ◽  
Roles And Responsibilities ◽  
Research Data Management ◽  
Data Support

In this paper, Liz Lyon explores how libraries can re-shape to better reflect the requirements and challenges of today’s data-centric research landscape. The Informatics Transform presents five assertions as potential pathways to change, which will help libraries to re-position, re-profile, and re-structure to better address research data management challenges. The paper deconstructs the institutional research lifecycle and describes a portfolio of ten data support services which libraries can deliver to support the research lifecycle phases. Institutional roles and responsibilities for research data management are also unpacked, building on the framework from the earlier Dealing with Data Report. Finally, the paper examines critical capacity and capability challenges and proposes some innovative steps to addressing the significant skills gaps.

scholarly journals From Project to Strategic Vision: Taking the Lead in Research Data Management Support at the University of Sydney Library

2014 ◽  
Vol 9 (1) ◽  
pp. 253-262 ◽  
Author(s):  
Belinda Norman ◽  
Kate Valentine Stanton
Keyword(s):  
Data Management ◽  
Research Data ◽  
Management Support ◽  
Policy And Practice ◽  
Roles And Responsibilities ◽  
Strategic Vision ◽  
Research Data Management ◽  
The Commons ◽  
The University ◽  
Project Partner

This paper explores three stories, each occurring a year apart, illustrating an evolution toward a strategic vision for Library leadership in supporting research data management at the University of Sydney. The three stories describe activities undertaken throughout the Seeding the Commons project and beyond, as the establishment of ongoing roles and responsibilities transition the Library from project partner to strategic leader in the delivery of research data management support. Each story exposes key ingredients that characterise research data management support: researcher engagement; partnerships; and the complementary roles of policy and practice.

scholarly journals Kutatási adatkezelést támogató szolgáltatás a Szegedi Tudományegyetemen

2021 ◽  
Author(s):  
Rozália Zeller ◽  
Szabolcs Hoczopán ◽  
Gyula Nagy
Keyword(s):  
Data Management ◽  
Research Community ◽  
Research Data ◽  
Data Repository ◽  
Institutional Research ◽  
Research Data Management ◽  
International Trends ◽  
Professional Assistance ◽  
Management Recommendations ◽  
The University

Following the national and international trends in mid-2020 the Klebelsberg Kuno Library of the University of Szeged has also started to deal with the issue of research data management. After thorough self-training the library staff studied the Hungarian and international best practices of managing research data. We tried to assess the needs of the institutional research data management habits and the opinion of the researchers of SZTE with a comprehensive questionnaire. We compiled a comprehensive questionnaire to assess the needs of our researchers, learn what they’re thinking about RDM and what kind of practices regarding RDM already exist in the research community. By evaluating the questionnaire we have determined the areas in which the library could provide professional assistance where there was a real need among researchers. Keeping in mind the needs of the research community of University of Szeged we have decided to develop the following services: copyright consulting, RDM trainings for PhD students, theoretical and methodological assistance for RDM, write institutional FAIR data management recommendations. The last four services have been successfully implemented. We also wrote a feasibility study to assess the possibilities of developing our own institutional data repository.

scholarly journals Skilling Up to Do Data: Whose Role, Whose Responsibility, Whose Career?

2009 ◽  
Vol 4 (2) ◽  
pp. 158-170 ◽  
Author(s):  
Graham Pryor ◽  
Martin Donnelly
Keyword(s):  
Data Management ◽  
Training Needs ◽  
Research Data ◽  
Roles And Responsibilities ◽  
Research Data Management ◽  
Management Forum ◽  
Career Opportunities ◽  
Informed Opinion

What are the roles necessary to effective data management and what kinds of expertise are needed by the researchers and data specialists who are filling those roles?  These questions were posed at a workshop of data creators and curators whose delegates challenged the DCC and RIN to identify the training needs and career opportunities for the broad cohort that finds itself working in data management – sometimes by design but more often by accident.  This paper revisits previous investigations into the roles and responsibilities required by a “data workforce”, presents a representative spectrum of informed opinion from the DCC Research Data Management Forum, and makes some recommendations for raising capability, capacity and status.

Generic concepts for organising data management in research projects

2021 ◽  
Author(s):  
Ivonne Anders ◽  
Swati Gehlot ◽  
Andrea Lammert ◽  
Karsten Peters-von Gehlen
Keyword(s):  
Project Management ◽  
Data Management ◽  
Best Practice ◽  
Research Data ◽  
Data Organization ◽  
Research Projects ◽  
General Application ◽  
Roles And Responsibilities ◽  
Research Data Management ◽  
Project Size

<p>Since few years Research Data Management is becoming an increasingly important part of scientific projects regardless of the number of topics or subjects, researchers or institutions involved. The bigger the project, the more are the data organization and data management requirements in order to assure the best outcome of the project. Despite this, projects rarely have clear structures or responsibilities for data management. The importance of clearly defining data management and also budgeting for it is often underestimated and/or neglected. A rather scarce number of reports and documentations explaining the research data management in certain projects and detailing best practice examples can be found in the current literature.  Additionally, these are often mixed up with topics of the general project management. Furthermore, these examples are very focused on the certain issues of the described projects and thus, a transferability (or general application) of provided methods is very difficult.</p><p>This contribution presents generic concepts of research data management with an effort to separate them from general project management tasks. Project size, details among the diversity of topics and the involved researcher, play an important role in shaping data management and determining which methods of data management can add value to the outcome of a project. We especially focus on different organisation types, including roles and responsibilities for data management in projects of different sizes. Additionally, we show how and when also education should be included, but also how important agreements in a project are.</p>

scholarly journals Is Democracy the Right System? Collaborative Approaches to Building an Engaged RDM Community

2017 ◽  
Author(s):  
Marta Teperek ◽  
Rosie Higman ◽  
Danny Kingsley
Keyword(s):  
Data Management ◽  
Community Engagement ◽  
Support Services ◽  
Cost Benefit Analysis ◽  
End Users ◽  
Research Data ◽  
Management Support ◽  
Initial Development ◽  
Positive Effects ◽  
Research Data Management

AbstractWhen developing new products, tools or services, one always need to think about the end users to ensure a wide-spread adoption. While this applies equally to services developed at higher education institutions, sometimes these services are driven by policies and not by needs of end users. This policy-driven approach can prove challenging for building effective community engagement. The initial development of Research Data Management support services at the University of Cambridge was policy-driven and subsequently failed in the first instance to engage the community of researchers for whom these services were created.In this practice paper we will describe the initial approach undertaken at Cambridge when developing RDM services, the results of this approach and lessons learnt. We will then provide an overview of alternative, democratic strategies employed and their positive effects on community engagement. We will summarise by performing a cost-benefit analysis of the two approaches. This paper might be a useful case study for any institutions aiming to develop central support services for researchers, with conclusions applicable to the wide sector, and extending beyond Research Data Management services.

scholarly journals Getting a Grip on Research Data Management

2021 ◽  
Author(s):  
Barb Znamirowski
Keyword(s):  
Data Management ◽  
Management Strategy ◽  
Research Data ◽  
Management Policy ◽  
Institutional Research ◽  
Research Data Management ◽  
Key Points ◽  
Agency Policy

In March 2021 the Tri-Agency released its Research Data Management Policy, including its three pillar requirements. This article reviews some key points from the Alliance RDM (Portage Network) workshop "Putting the Tri-Agency Policy into Practice: Workshopping Your Institutional Research Data Management Strategy."

scholarly journals Automating Research Data Management Using Machine-Actionable Data Management Plans

2022 ◽  
Vol 13 (2) ◽  
pp. 1-22
Author(s):  
Tomasz Miksa ◽  
Simon Oblasser ◽  
Andreas Rauber
Keyword(s):  
Data Management ◽  
Research Data ◽  
Use Cases ◽  
Full Potential ◽  
Institutional Research ◽  
Reference Architecture ◽  
Management Planning ◽  
Research Data Management ◽  
Management Plans ◽  
New Generation

Many research funders mandate researchers to create and maintain data management plans (DMPs) for research projects that describe how research data is managed to ensure its reusability. A DMP, being a static textual document, is difficult to act upon and can quickly become obsolete and impractical to maintain. A new generation of machine-actionable DMPs (maDMPs) was therefore proposed by the Research Data Alliance to enable automated integration of information and updates. maDMPs open up a variety of use cases enabling interoperability of research systems and automation of data management tasks. In this article, we describe a system for machine-actionable data management planning in an institutional context. We identify common use cases within research that can be automated to benefit from machine-actionability of DMPs. We propose a reference architecture of an maDMP support system that can be embedded into an institutional research data management infrastructure. The system semi-automates creation and maintenance of DMPs, and thus eases the burden for the stakeholders responsible for various DMP elements. We evaluate the proposed system in a case study conducted at the largest technical university in Austria and quantify to what extent the DMP templates provided by the European Commission and a national funding body can be pre-filled. The proof-of-concept implementation shows that maDMP workflows can be semi-automated, thus workload on involved parties can be reduced and quality of information increased. The results are especially relevant to decision makers and infrastructure operators who want to design information systems in a systematic way that can utilize the full potential of maDMPs.

scholarly journals ‘Essentials 4 Data Support’

IFLA Journal ◽  
2016 ◽  
Vol 42 (4) ◽  
pp. 278-283
Author(s):  
Ellen Verbakel ◽  
Marjan Grootveld
Keyword(s):  
Data Management ◽  
Research Data ◽  
Support Staff ◽  
Online Information ◽  
Face To Face ◽  
Research Data Management ◽  
Data Support ◽  
Professional Network

This article describes a research data management course for support staff such as librarians and IT staff. The authors, who coach the participants, introduce the three course formats and describe the training in more detail. In the last years over 170 persons have participated in this training. It combines a wealth of online information with face-to-face meetings. The aim of the course is to support the participants in strengthening various skills and acquiring knowledge so they feel confident to support, advise and train researchers. Interaction among the students is embedded in the structure of the training, because we regard it as a valuable instrument to develop a professional network. Recently the course has taken on a new challenge: in addition to the regular courses a couple of in house trainings have been delivered on request. The paper ends with a description of the key group assignments for such compact trainings.

Team-based data management instruction at small liberal arts colleges

IFLA Journal ◽  
2017 ◽  
Vol 43 (1) ◽  
pp. 105-118 ◽  
Author(s):  
Ryan Clement ◽  
Amy Blau ◽  
Parvaneh Abbaspour ◽  
Eli Gandour-Rood
Keyword(s):  
Data Management ◽  
Liberal Arts ◽  
Liberal Arts Colleges ◽  
Research Data ◽  
Institutional Research ◽  
Management Skills ◽  
Learning Modules ◽  
Research Data Management ◽  
Small Liberal Arts Colleges ◽  
Management Services

This paper describes a collaborative approach taken by librarians at five small, regional liberal arts colleges to developing/enhancing research data management services on their campuses. The five colleges collectively belong to a consortium known as the Northwest Five Consortium. Over 10 months, librarians from the five schools collaborated to plan a data management and curation workshop with the goals of developing relationships with researchers working with data, developing their own research data management skills and services, and building a model for future training and outreach around institutional research data management services. This workshop brought together research teams including faculty, students, and librarians, and incorporated active learning modules as well as in-depth pre-workshop discussion. This article will discuss the context and background for this workshop, the model itself, and the outcomes and possibilities for future developments.

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