scholarly journals Practical considerations for a library’s research data management services: the case of the National Institutes of Health Library

2021 ◽  
Vol 109 (3) ◽  
Author(s):  
Soojung Kim ◽  
Sue Yeon Syn
Keyword(s):  
Data Management ◽  
Research Data ◽  
National Institutes Of Health ◽  
User Characteristics ◽  
Data Services ◽  
Research Data Management ◽  
Semistructured Interviews ◽  
Computer Library ◽  
Data Lifecycle

Objective: This study investigates research data management (RDM) services using a crosstab framework with the National Institutes of Health (NIH) Library as a case study to provide practical considerations for libraries seeking to improve their RDM services.Methods: We conducted semistructured interviews with four librarians who provide data services at the NIH Library regarding library user characteristics, RDM services provided, RDM infrastructure, and collaboration experiences. Through the analysis of interview transcripts, we identified and analyzed the NIH Library’s RDM services according to Online Computer Library Center (OCLC)'s three categories of RDM services and the six stages of the data lifecycle.Results: The findings show that the two models’ crosstab framework can provide an overview of an institution’s current RDM services and identify service gaps. The NIH Library tends to take more responsibility in providing education and expertise services while relying more on information technology departments for curation services. The library provides significant support for data creation, analysis, and sharing stages to meet biomedical researchers’ needs, suggesting areas for potential expansion of RDM services in the less supported stages of data description, storage, and preservation. Based on these findings, we recommend three key considerations for libraries: identify gaps in current services, identify services that can be supported via partnerships, and get regular feedback from users.Conclusion: These findings provide a deeper understanding of RDM support on the basis of RDM service categories and the data lifecycle and promote discussion of issues to be considered for future improvements in RDM services.

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.  

Research Data Management Services in Tertiary Institutions in Zimbabwe

2021 ◽  
pp. 419-437
Author(s):  
Josiline Phiri Chigwada
Keyword(s):  
Data Management ◽  
Research Data ◽  
Management Policy ◽  
Online Questionnaire ◽  
Tertiary Institutions ◽  
Data Services ◽  
Security Issues ◽  
Research Data Management ◽  
Survey Monkey ◽  
Management Services

The chapter seeks to analyze how librarians in Zimbabwe are responding to increasing librarian roles in the provision of research data services. The study sought to ascertain librarians' awareness and preparedness to offer research data management services at their institutions and determine support required by librarians to effectively deliver research data services. Participants were invited to respond to the survey, and survey monkey was used to administer the online questionnaire. The collected data was analyzed using content analysis, and it was thematically presented. Findings revealed that librarians in Zimbabwe are aware of their role in research data management, but the majority are not prepared to offer research data management services due to a lack of the required skills and resources. Challenges that were noted include lack of research data management policy at institutional levels and information technology issues such as obsolescence and security issues.

scholarly journals Building a research data management service for the London school of hygiene & tropical medicine

2015 ◽  
Vol 49 (4) ◽  
pp. 424-439 ◽  
Author(s):  
Gareth Knight
Keyword(s):  
Data Management ◽  
Research Data ◽  
Tropical Medicine ◽  
Limited Resources ◽  
London School ◽  
Management Service ◽  
Content Type ◽  
Research Data Management ◽  
Time Investment

Purpose – The purpose of this paper is to present a case study of work performed at the London School of Hygiene and Tropical Medicine to set-up a Research Data Management Service and tailor it to the needs of health researchers. Design/methodology/approach – The paper describes the motivations for establishing the RDM Service and outlines the three objectives that were set to improve data management practice within the institution. Each of the objectives are explored in turn, stating how they were addressed. Findings – A university with limited resources can operate a RDM Service that pro-actively supports researchers wishing to manage research data by monitoring evolving support needs, identifying common trends and developing resources that will reduce the time investment needed. The institution-wide survey identified a need for guidance on developing data documentation and archiving research data following project completion. Analysis of ongoing support requests identifies a need for guidance on data management plans and complying with journal sharing requirements. Research limitations/implications – The paper provides a case study of a single institution. The results may not be generally applicable to universities that support other disciplines. Practical implications – The case study may be helpful in helping other universities to establish an RDM Service using limited resources. Originality/value – The paper outlines how the evolving data management needs of public health researchers can be identified and a strategy that can be adopted by an RDM Service to efficiently address these requirements.

scholarly journals Developing Data Curation Protocols for Digital Projects at Vanderbilt: Une Micro-Histoire

2018 ◽  
Vol 12 (2) ◽  
pp. 246-254 ◽  
Author(s):  
Veronica A Ikeshoji-Orlati ◽  
Clifford B Anderson
Keyword(s):  
Data Management ◽  
Charles Baudelaire ◽  
Research Data ◽  
Future Directions ◽  
Object Description ◽  
Research Data Management ◽  
Ongoing Development ◽  
Holistic Research ◽  
Management Services

This paper examines the intersection of legacy digital humanities projects and the ongoing development of research data management services at Vanderbilt University’s Jean and Alexander Heard Library. Future directions for data management and curation protocols are explored through the lens of a case study: the (re)curation of data from an early 2000s e-edition of Raymond Poggenburg’s Charles Baudelaire: Une Micro-histoire. The vagaries of applying the Library of Congress Metadata Object Description Schema (MODS) to the data and metadata of theMicro-histoirewill be addressed. In addition, the balance between curating data and metadata for preservation vs. curating it for (re)use by future researchers is considered in order to suggest future avenues for holistic research data management services at Vanderbilt.

scholarly journals Research Data Management Practices: Synergies and Discords between Researchers and Institutions

2018 ◽  
Vol 13 (1) ◽  
pp. 73-90
Author(s):  
Sally Vanden-Hehir ◽  
Helena Cousijn ◽  
Hesham Attalla
Keyword(s):  
Data Management ◽  
Management Practices ◽  
Qualitative Interviews ◽  
Research Data ◽  
Research Data Management ◽  
Early Stages ◽  
Lifecycle Model ◽  
Data Lifecycle

The aim of this study was to explore the synergies and discords in attitudes towards research data management (RDM) drivers and barriers for both researchers and institutions. Previous work has studied RDM from a single perspective, but not compared researchers’ and institutions’ perspectives. We carried out qualitative interviews with researchers as well as institutional representatives to identify drivers and barriers, and to explore synergies and discords of both towards RDM. We mapped these to a data lifecycle model and found that the contradictions occur at early stages in the lifecycle of data and the synergies occur at the later stages. This means that for future successful RDM, the points of discord at the start of the data lifecycle must be overcome. Finally, we conclude by proposing key recommendations that could help institutions when addressing both researcher and institutional RDM needs.

scholarly journals A model for initiating research data management services at academic libraries

2019 ◽  
Vol 107 (3) ◽  
Author(s):  
Kevin B. Read ◽  
Jessica Koos ◽  
Rebekah S. Miller ◽  
Cathryn F. Miller ◽  
Gesina A. Phillips ◽  
...  
Keyword(s):  
Data Management ◽  
Research Data ◽  
Data Series ◽  
Pilot Program ◽  
Data Services ◽  
Research Data Management ◽  
Hands On ◽  
Medical Libraries ◽  
Training Resources ◽  
Educational Modules

Background: Librarians developed a pilot program to provide training, resources, strategies, and support for medical libraries seeking to establish research data management (RDM) services. Participants were required to complete eight educational modules to provide the necessary background in RDM. Each participating institution was then required to use two of the following three elements: (1) a template and strategies for data interviews, (2) a teaching tool kit to teach an introductory RDM class, or (3) strategies for hosting a data class series.Case Presentation: Six libraries participated in the pilot, with between two and eight librarians participating from each institution. Librarians from each institution completed the online training modules. Each institution conducted between six and fifteen data interviews, which helped build connections with researchers, and taught between one and five introductory RDM classes. All classes received very positive evaluations from attendees. Two libraries conducted a data series, with one bringing in instructors from outside the library.Conclusion: The pilot program proved successful in helping participating librarians learn about and engage with their research communities, jump-start their teaching of RDM, and develop institutional partnerships around RDM services. The practical, hands-on approach of this pilot proved to be successful in helping libraries with different environments establish RDM services. The success of this pilot provides a proven path forward for libraries that are developing data services at their own institutions.

scholarly journals Doctoral Students' Educational Needs in Research Data Management: Perceived Importance and Current Competencies

2021 ◽  
Vol 16 (1) ◽  
pp. 36
Author(s):  
Jukka Rantasaari
Keyword(s):  
Data Management ◽  
Doctoral Students ◽  
Educational Needs ◽  
Research Data ◽  
Structured Interviews ◽  
High Quality Research ◽  
Management Planning ◽  
Data Preservation ◽  
Research Data Management ◽  
Data Lifecycle

Sound research data management (RDM) competencies are elementary tools used by researchers to ensure integrated, reliable, and re-usable data, and to produce high quality research results. In this study, 35 doctoral students and faculty members were asked to self-rate or rate doctoral students’ current RDM competencies and rate the importance of these competencies. Structured interviews were conducted, using close-ended and open-ended questions, covering research data lifecycle phases such as collection, storing, organization, documentation, processing, analysis, preservation, and data sharing. The quantitative analysis of the respondents’ answers indicated a wide gap between doctoral students’ rated/self-rated current competencies and the rated importance of these competencies. In conclusion, two major educational needs were identified in the qualitative analysis of the interviews: to improve and standardize data management planning, including awareness of the intellectual property and agreements issues affecting data processing and sharing; and to improve and standardize data documenting and describing, not only for the researcher themself but especially for data preservation, sharing, and re-using. Hence the study informs the development of RDM education for doctoral students.

scholarly journals Deskripsi Metadata dalam Manajemen Data Penelitian: Studi Kasus pada Sistem Repositori Ilmiah Nasional

2021 ◽  
Vol 5 (1) ◽  
pp. 35
Author(s):  
Seno Yudhanto ◽  
Nina Mayesti
Keyword(s):  
Data Management ◽  
Research Data ◽  
Case Study Method ◽  
Management Mechanism ◽  
Research Data Management ◽  
Research And Innovation ◽  
Metadata Standards ◽  
Mechanism Research ◽  
The Republic

Organizing research data is very important for data and information managers through a research data management mechanism (research data management/MDP) in a repository system. In this mechanism, research data must be organized and described as an effort to provide access. One important aspect of organizing is the availability of metadata. This Study was supported by the Institute of Sciences of Indonesia (LIPI) and the SAINTEK Scholarship from the Ministry of Research and Technology/National Research and Innovation Agency of the Republic of Indonesia (KEMENRISTEK/BRIN) in 2020 and it’s purpose is to identify and describe metadata standards and metadata elements used in research data management in the National Scientific Repository (RIN) system. This study uses a qualitative approach with a case study method. Sources of data come from literature / document studies and direct observation. The results of the study show that the RIN system adopts descriptive metadata from three main standards, they are DublinCore, DataCite, and DDI. As a medium for describing research data in general, the metadata sections provided by the RIN system in the dataset folder are quite large and complete. Of the 35 metadata fields available in the dataset folder in this system, the three metadata standards complement each other with an adaptation of the dominant DDI standard with 32 metadata fields. However, the fields that are available can also be found in other standards, such as the title, subject, or keyword fields that are also found in the DublinCore and DataCite standards. Thus, the metadata fields provided in the RIN system is good enough and sufficient for research data management needs.

Sign in / Sign up

Export Citation Format

Share Document