scholarly journals Collaboration in RDM activities – Practices and development at Aalto University

2017 ◽  
Author(s):  
Maria Söderholm ◽  
Anne Sunikka
Keyword(s):  
Data Management ◽  
Data Storage ◽  
Research Data ◽  
Service Planning ◽  
Open Access Publishing ◽  
Service Development ◽  
It Services ◽  
Data Services ◽  
Service Portfolio ◽  
Starting Point

Watch the VIDEO here. Presenter – Maria SöderholmResearch data management (RDM) is a complex and dynamic topic, and demands diverse expertise, skills and knowledge. The RDM expertise includes subtopics like collection/provision of data; storage and processing of data; long-term preservation requirements of the data; and funders’ demands and solutions to share, re-find and re-use research data. Usually the expertise related to these RDM subtopics is spread to several university units, both academic and administrative. Therefore, many tasks related to RDM, for example, day-to-day practices, the supply of services and the development work are best carried out in a network-based cooperation.In the presentation, we will introduce our RDM related partnership and networking of Aalto University. As a starting point, we introduce the internal service development working principles that our RDM network work is based on. However, the focus will be on describing our RDM working group and development activities.Aalto’s Research Data Management Programme forms the backbone for RDM work. It establishes seven separate action points for RDM activities: 1) open access  publishing; 2) implementation of data management planning tool; 3) metadata catalogue for open data; 4) data publishing; 5) comprehensive repository service for storage, back-up and collaboration; 6) combining openness and innovation; and 7) RDM awareness building activities. The actors in the RDM network consist of Research and Innovation Services (leading the group), IT Services, and Learning Centre (previously Library).In the presentation, we will introduce the core actors in more detail, paying attention to the complementarity of the roles; and the activities and the aims, which steer the work. We also discuss the meaning and consequences of the network-based cooperation for the working group.First, the RDM group acts as a joint platform for comprehensive RDM information. Important means of data gathering are surveys and informal discussion with researcher. In the future, formal group discussions on RDM needs are hosted. The previous discussions with researchers have underlined the importance of arranging services for both disciplinary and data specific needs in addition to common university level service needs.Second, the group is a messenger of the RDM topics. Our task is to rise internal RDM awareness and disseminate national and international information and development trends in the university.The third and the most challenging aim is the RDM service planning and delivery. Our task is to identify the existing in-house services, to map the suitable services provided by national and international agents as well as to recognize the needs for new services. Our service portfolio covers both consultation/informational services and technical, hands-on services. However, many of our research data services are still in the planning or piloting stage, thus cooperation with researchers is essential.In our experience, the network-based collaboration model that foster individuals’ interconnectedness is crucial for surviving with the built-in dynamism of RDM. This model provides a non-hierarchical and flexible environment for actions to meet the increasing expectations for research data services we face from the funders, governments, and researchers.

scholarly journals Open Science: Reinventing the Librarianship

2016 ◽  
Author(s):  
Esa-Pekka Keskitalo ◽  
Tanja Vienonen
Keyword(s):  
Open Access ◽  
Data Management ◽  
Data Storage ◽  
Service Providers ◽  
Research Output ◽  
Open Science ◽  
Research Data ◽  
Open Access Publishing ◽  
National Library ◽  
Institutional Repositories

Better utilisation of publicly funded research output is an aim of the Finnish Government. To reach that aim, the Open Science and Research (ATT) Initiative was launched in 2014. Lead by the Ministry of Education and Culture, the ATT Initiative has funded a number of projects that support good research data management, opening of research data, and Open Access in general. The Initiative also emphasises cooperation and interoperability nationally, and internationally.The National Library of Finland and other research libraries have an important role in the ATT Initiative. Libraries are in a good position to make meaningful contributions as they can repurpose their expertise on metadata, information retrieval, and collection management. They are finding new ways of collaboration and creating services in the fields of Open Access and Open Science.Libraries and other service providers should, first and foremost, respect the needs of research and researchers: science should always be the guiding force. But Open Access and Open Science do have an effect on how research is conducted and published. Therefore, it must be possible to have a critical look on conventional research practices. Increasing amounts of data, new technological possibilities, and new methods of analysis mean that old practices need to be revised. The more pronounced demands of interoperability and innovative re-usability drive for change, too. Of course, the funders are also very keen on cost-efficiency and measurable impact. There is a demand for harmonisation, collaboration, and shared infrastructures and services.The Open Scientific Publishing Project (TAJUA) in the National Library of Finland is a part of the ATT Initiative. The main focus of the project is to increase and improve the availability of Finnish research output. It comprises of several subprojects that build on the existing expertise of the Library, taking it to new directions. They deal withimproving the institutional repository infrastructure provided by the National Library, with special attention to organisations with restricted resources and basic demands;better guidance for institutional repositories on best practices in metadata creation, licensing, and in gathering statistics in a commensurable manner;a tool for easy creation of metadata about research datasets;improved persistent identifier services (ISNI, ORCID, URN, etc.);better understanding of economics of Open Access publishing, e.g. real level of APC, and recommendations for changes in publishing workflows; andrecommendations for ensuring long-term accessibility of scientific output.The TAJUA project complements others under the umbrella of the ATT Initiative. They deal with more efficient publishing workflows, data management planning, opening datasets, training and education on Open Science, and tools to enrich and work up open linked data. Existing national services on data storage, preservation, and dissemination will also be extended.Research libraries should not be shy about their knowledge and skills. With metadata being the new black, they can really make their mark on the world of Open Science.

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.

scholarly journals Service Integration to Enhance Research Data Management: RSpace Electronic Laboratory Notebook Case Study

2015 ◽  
Vol 10 (1) ◽  
pp. 163-172 ◽  
Author(s):  
Stuart Macdonald ◽  
Rory Macneil
Keyword(s):  
Data Management ◽  
Research Output ◽  
Service Integration ◽  
Research Data ◽  
Responsible Conduct Of Research ◽  
It Services ◽  
Laboratory Notebook ◽  
Research Data Management ◽  
Research Administrators ◽  
Working Together

Research Data Management (RDM) provides a framework that supports researchers and their data throughout the course of their research and is increasingly regarded as one of the essential areas of responsible conduct of research. New tools and infrastructures make possible the generation of large volumes of digital research data in a myriad of formats. This facilitates new ways to analyse, share and reuse these outputs, with libraries, IT services and other service units within academic institutions working together with the research community to develop RDM infrastructures to curate and preserve this type of research output and make them re-usable for future generations. Working on the principle that a rationalised and continuous flow of data between systems and across institutional boundaries is one of the core goals of information management, this paper will highlight service integration via Electronic Laboratory Notebooks (ELN), which streamline research data workflows, result in efficiency gains for researchers, research administrators and other stakeholders, and ultimately enhance the RDM process.

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 Research Data Services at ETH-Bibliothek

IFLA Journal ◽  
2016 ◽  
Vol 42 (4) ◽  
pp. 284-291 ◽  
Author(s):  
Ana Sesartic ◽  
Matthias Töwe
Keyword(s):  
Life Cycle ◽  
Data Management ◽  
Service Providers ◽  
Scientific Practice ◽  
Research Data ◽  
Data Services ◽  
Mutual Learning ◽  
Data Life Cycle ◽  
Long Term Preservation

The management of research data throughout its life-cycle is both a key prerequisite for effective data sharing and efficient long-term preservation of data. This article summarizes the data services and the overall approach to data management as currently practised at ETH-Bibliothek, the main library of ETH Zürich, the largest technical university in Switzerland. The services offered by service providers within ETH Zürich cover the entirety of the data life-cycle. The library provides support regarding conceptual questions, offers training and services concerning data publication and long-term preservation. As research data management continues to play a steadily more prominent part in both the requirements of researchers and funders as well as curricula and good scientific practice, ETH-Bibliothek is establishing close collaborations with researchers, in order to promote a mutual learning process and tackle new challenges.

scholarly journals Research Data Management Initiatives at University of Edinburgh

2011 ◽  
Vol 6 (2) ◽  
pp. 232-244 ◽  
Author(s):  
Robin Rice ◽  
Jeff Haywood
Keyword(s):  
Data Management ◽  
Data Storage ◽  
Academic Staff ◽  
Research Data ◽  
Lessons Learned ◽  
The Public ◽  
Research Data Management ◽  
Online Tools ◽  
University Of Edinburgh ◽  
Future Direction

During the last decade, national and international attention has been increasingly focused on issues of research data management and access to publicly funded research data. The pressure brought to bear on researchers to improve their data management and data sharing practice has come from research funders seeking to add value to expensive research and solve cross-disciplinary grand challenges; publishers seeking to be responsive to calls for transparency and reproducibility of the scientific record; and the public seeking to gain and re-use knowledge for their own purposes using new online tools. Meanwhile higher education institutions have been rather reluctant to assert their role in either incentivising or supporting their academic staff in meeting these more demanding requirements for research practice, partly due to lack of knowledge as to how to provide suitable assistance or facilities for data storage and curation/preservation. This paper discusses the activities and drivers behind one institution’s recent attempts to address this gap, with reflection on lessons learned and future direction.

scholarly journals Supporting FAIR data: categorization of research data as a tool in data management

2018 ◽  
Vol 37 (4) ◽  
Author(s):  
Jessica Parland-von Essen ◽  
Katja Fält ◽  
Zubair Maalick ◽  
Miika Alonen ◽  
Eduardo Gonzalez
Keyword(s):  
Data Management ◽  
Research Data ◽  
Data Types ◽  
Specific Research ◽  
Research Results ◽  
Data Services ◽  
Operational Data

The demand for implementation of the FAIR data principles is in many cases difficult for a researcher to adhere to in efficient ways due to lacking tools. We suggest categorizing data in a more extensive and systematic way with focus on the inherent properties of the data as means to enhancing research data services. After discussing different approaches to categorizing data, we propose a tripartite research data categorization based around the inherent aspect of stability. The three research data types are operational data, generic research data and research data publications. Generic research data is validated data and can be cumulative, i.e. data can be added without versioning, however if it is dynamic it should be versioned. Generic research data should be separated from immutable dataset publications that are published for reasons of reproducibility of specific research results.

scholarly journals Teaching Open Science

2020 ◽  
Author(s):  
Helene N. Andreassen ◽  
Erik Lieungh
Keyword(s):  
Open Access ◽  
Data Management ◽  
Teaching And Learning ◽  
Open Science ◽  
Research Data ◽  
Open Access Publishing ◽  
The Arctic ◽  
Learning Support ◽  
Research Data Management ◽  
The University

In this episode, we are discussing how to teach open science to PhD students. Helene N. Andreassen, head of Library Teaching and Learning Support at the University Library of UiT the Arctic University of Norway shares her experiences with the integration of open science in a special, tailor-made course for PhD's that have just started their project. An interdisciplinary, discussion-based course, "Take Control of Your PhD Journey: From (P)reflection to Publishing" consists of a series of seminars on research data management, open access publishing and other subject matters pertaining to open science. First published online February 26, 2020.

A systematic literature review on research data management practices and services

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Murtaza Ashiq ◽  
Muhammad Haroon Usmani ◽  
Muhammad Naeem
Keyword(s):  
Literature Review ◽  
Data Management ◽  
Systematic Literature Review ◽  
Academic Libraries ◽  
Management Practices ◽  
Developed Countries ◽  
Research Data ◽  
Open Access Publishing ◽  
Content Type ◽  
Research Data Management

Purpose Research data management (RDM) has been called a “ground-breaking” area for research libraries and it is among the top future trends for academic libraries. Hence, this study aims to systematically review RDM practices and services primarily focusing on the challenges, services and skills along with motivational factors associated with it. Design/methodology/approach A systematic literature review method was used focusing on literature produced between 2016–2020 to understand the latest trends. An extensive research strategy was framed and 15,206 results appeared. Finally, 19 studies have fulfilled the criteria to be included in the study following preferred reporting items for systematic reviews and meta-analysis. Findings RDM is gradually gaining importance among researchers and academic libraries; however, it is still poorly practiced by researchers and academic libraries. Albeit, it is better observed in developed countries over developing countries, however, there are lots of challenges associated with RDM practices by researchers and services by libraries. These challenges demand certain sets of skills to be developed for better practices and services. An active collaboration is required among stakeholders and university services departments to figure out the challenges and issues. Research limitations/implications The implications of policy and practical point-of-view present how research data can be better managed in the future by researchers and library professionals. The expected/desired role of key stockholders in this regard is also highlighted. Originality/value RDM is an important and emerging area. Researchers and Library and Information Science professionals are not comprehensively managing research data as it involves complex cooperation among various stakeholders. A combination of measures is required to better manage research data that would ultimately move forward for open access publishing.

scholarly journals Research data management and openness

2015 ◽  
Vol 49 (4) ◽  
pp. 364-381 ◽  
Author(s):  
Rosie Higman ◽  
Stephen Pinfield
Keyword(s):  
Data Management ◽  
Case Studies ◽  
Data Sharing ◽  
Actor Network Theory ◽  
Research Data ◽  
Policy Formation ◽  
Service Development ◽  
Content Type ◽  
Research Data Management ◽  
The Relationship

Purpose – The purpose of this paper is to investigate the relationship between research data management (RDM) and data sharing in the formulation of RDM policies and development of practices in Higher Education Institutions (HEIs). Design/methodology/approach – Two strands of work were undertaken sequentially: first, content analysis of 37 RDM policies from UK HEIs; and second, two detailed case studies of institutions with different approaches to RDM based on semi-structured interviews with staff involved in the development of RDM policy and services. The data are interpreted using insights from Actor Network Theory. Findings – RDM policy formation and service development has created a complex set of networks within and beyond institutions involving different professional groups with widely varying priorities shaping activities. Data sharing is considered an important activity in the policies and services of HEIs studied, but its prominence can in most cases be attributed to the positions adopted by large research funders. Research limitations/implications – The case studies, as research based on qualitative data, cannot be assumed to be universally applicable but do illustrate a variety of issues and challenges experienced more generally, particularly in the UK. Practical implications – The research may help to inform development of policy and practice in RDM in HEIs and funder organisations. Originality/value – This paper makes an early contribution to the RDM literature on the specific topic of the relationship between RDM policy and services, and openness – a topic which to date has received limited attention.

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