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This report investigates the meaning and (potential) impact of the FAIR data principles in practice. These principles were established by a group of diverse stakeholders engaging via a working group in FORCE11. They are referenced in many policy documents and in developments of open science, for example, the European Open Science Cloud. This report explored FAIR with stakeholders in the UK academic research community. Its aims were to understand how using or being inspired by these principles improves the findability, accessibility, interoperability and reuse of research data, including consideration of disciplinary differences. Jisc established a group of research data experts and Jisc staff who provided expertise and helped to validate findings. Interviews and focus groups were conducted, primarily with researchers, but also involving input from research support professionals, publishers and funders. An assessment of the use of FAIR principles in institutional research data management (RDM) guidance was also carried out. Data collected from these activities was synthesised and structured using a PEST framework - grouped into factors relating to Political, Economic, Social and Technical aspects. Explicit use of FAIR was seen to be limited, in many cases, to discussion at a fairly conceptual level amongst those most heavily involved in best practice of data management. Even where FAIR was fairly well established as a term and a concept, it tended to largely reflect existing practice. Arguably this was without significantly influencing many practical changes for those at the "leading edge" of data management, although it did provide a new and effective common way of communicating best practice. However, in exploring the underlying practices of research, demonstrating findability, accessibility, interoperability and reusability, there was considerable evidence that good practice existed in all of these elements. In many cases this was both well established (over many years) and continually improving.

The dynamic network of 31 research data centres (RDCs) accredited by the German Data Forum (Rat für Sozial- und Wirtschaftsdaten, RatSWD) provides science and research with comprehensive access to quality-assured and sensitive data. The annual number of processing requests and publications indicate that the data and services provided by RDCs are in high demand. They also underscore the importance of the research data centres for the social, behavioural and economic sciences. As shown in two new publications by the German Data Forum, the research data infrastructure is highly effective and can serve as a best practice model on a national and international level.

This book aims to help the reader better understand the importance of data analysis in project management. Moreover, it provides guidance by showing tools, methods, techniques and lessons learned on how to better utilize the data gathered from the projects. First and foremost, insight into the bridge between data analytics and project management aids practitioners looking for ways to maximize the practical value of data procured. The book equips organizations with the know-how necessary to adapt to a changing workplace dynamic through key lessons learned from past ventures. The book's integrated approach to investigating both fields enhances the value of research findings.

The 2011 Canadian Research Data Summit was held at the Ottawa Convention Centre on September 14. About the Summit On September 14-15, 2011, The 2011 Canadian Research Data Summit brings together 100-150 senior researchers, high level policy makers, university administrators, and members of the private sector. Together, participants will work on formulating a shared strategy for addressing the challenges and opportunities for maximizing the benefits of our collective investment in research data in Canada. The Summit will act as a catalyst for the development of a made-inCanada approach for maximizing the availability and use of research data. About the Research Data Strategy Working Group The Research Data Strategy Working Group is a collaborative effort launched in 2008 to address the challenges and issues surrounding the access and preservation of data arising from Canadian research. This multi-disciplinary group of universities, institutes, libraries, operators of research infrastructure, granting agencies, governments, and individual researchers are united through a shared recognition of the pressing need to deal with Canadian data stewardship issues. Together, they are focussing on the necessary actions, next steps and leadership roles that researchers and institutions can take to ensure Canada's research data are accessible and usable for current and future generations of researchers

Das Poster der Stiftung Universität Hildesheim zum Forschungsdatenmanagement zeigt, wie eine wissenschaftliche Bibliothek, so wie die Universitätsbibliothek Hildesheim, geisteswissenschaftliche Disziplinen im Forschungsdatemanagement aktiv unterstützt. Forschungsprojekte werden durch Serviceinfrastrukturen, den technischen Infrastrukturen intern (Rechenzentrum) und extern (GWDG, NFDI4Culture, usw.) in allen Phasen begleitet. Geisteswissenschaftliche Projekte werden außerdem hinsichtlich der forschungsethischen Belange unterstützt. Ende 2020 fand ein Tag der Forschung zur Forschungsethik statt. Das FDM der UB Hildesheim orientiert sich u.a. an den FAIR- und Care-Prinzipien. Methodenorientierte Beratungen gehen über das Dienstleistungsportfolio der UB hinaus. Workshops zum geisteswissenschaftlichen Forschungsdatenmanagement finden jedes Semester statt. Der Kontakt zur FDM-Stelle kann den Weg zu den Ethikkommissionen weisen. Überlegungen zur Ethik gehen über die erforderlichen datenschutzrechtlichen zu den personenbezogenen Daten hinaus. Das gesamte Forschungsfeld wird reflektiert. Der Fachbereich 2, Kulturwissenschaften und Ästhetische Kommunikation, vereint die Institute für bildende Kunst und Kunstwissenschaft, das Institut für Kulturpolitik, das Institut für Literarisches Schreiben und Literaturwissenschaft, das Institut für Medien, Theater und Populäre Kultur, das Institut für Musik und Musikwissenschaft sowie das Institut für Philosophie.

Das Poster der Stiftung Universität Hildesheim zum Forschungsdatenmanagement zeigt, wie eine wissenschaftliche Bibliothek, so wie die Universitätsbibliothek Hildesheim, geisteswissenschaftliche Disziplinen im Forschungsdatemanagement aktiv unterstützt. Forschungsprojekte werden durch Serviceinfrastrukturen, den technischen Infrastrukturen intern (Rechenzentrum) und extern (GWDG, NFDI4Culture, usw.) in allen Phasen begleitet. Geisteswissenschaftliche Projekte werden außerdem hinsichtlich der forschungsethischen Belange unterstützt. Ende 2020 fand ein Tag der Forschung zur Forschungsethik statt. Das FDM der UB Hildesheim orientiert sich u.a. an den FAIR- und Care-Prinzipien. Methodenorientierte Beratungen gehen über das Dienstleistungsportfolio der UB hinaus. Workshops zum geisteswissenschaftlichen Forschungsdatenmanagement finden jedes Semester statt. Der Kontakt zur FDM-Stelle kann den Weg zu den Ethikkommissionen weisen. Überlegungen zur Ethik gehen über die erforderlichen datenschutzrechtlichen zu den personenbezogenen Daten hinaus. Das gesamte Forschungsfeld wird reflektiert. Der Fachbereich 2, Kulturwissenschaften und Ästhetische Kommunikation, vereint die Institute für bildende Kunst und Kunstwissenschaft, das Institut für Kulturpolitik, das Institut für Literarisches Schreiben und Literaturwissenschaft, das Institut für Medien, Theater und Populäre Kultur, das Institut für Musik und Musikwissenschaft sowie das Institut für Philosophie.

Australian government funding and policy guidelines increasingly encourage researchers to deposit their research data in institutional or subject repositories, but there are significant technical and organisational practicalities involved in achieving this. In this paper, Monash University Library staff members with responsibility for repository development and research data management describe their work together to establish the Monash University ARROW Repository as a key part of the university's overall program to improve research data management. Repository - related activities are discussed in the context of wider developments, both in technical infrastructure and in terms of professional development and outreach to researchers. Presented at 'Connections content conversations', the 15th VALA Biennial Conference and Exhibition (VALA 2010), Melbourne, Victoria, Australia, 9-11 February 2010 handle 1959.1/539468 pid monash:81820

Deliverable 1.1 – Data Management Plan (DMP) is related to WP1 – Coordination and management, Task 1.4 - Data protection, data management plan and ethics compliance. Task 1.4 runs for the entire duration of the project to ensure that the implementation of reCreating Europe adheres to the EU legal and normative framework, as well as to key ethical and societal values and principles. ReCreating Europe's Compliance Framework (CF) is developed as a structured set of guidelines covering the broadest possible spectrum of legal and ethical issues arising during the development of the project, considering, in particular, the rights of all relevant stakeholders and actors, both as end-users and as participants in surveys, workshops, and semistructured interviews. This DMP records the procedures for data management within the reCreating Europe project. It documents the types of data the project will generate or collect, the standards and platforms that will be used for storage and processing, measures to assure legal compliance, and the plan for how these data will be curated and preserved to enable maximal future exploitation, sharing and re-use. It represents the general strategy of reCreating Europe Consortium to establish a FAIR ecosystem on research data developed during the project in order to fulfil the Open Research Data Pilot policy. It has been already identified that several project's research activities will involve human participants, some of them being vulnerable, and the collection and processing of personal data will require the collection of informed consent and ethics clearance. Informed consent and ethical approval procedures and forms are included in D1.2 Informed consent forms and information sheets, to be read in conjunction with this document. This document provides in attachment a detailed list of datasets to be developed in each WP and specifies the rules to be applied for each research data category, in order to identify common rules on how data will be curated and preserved in the long term, and ...

With an identical data base -- the U of Michigan Survey Research Center/Center for Political Studies election studies conducted over the 1952-1976 period -- scholars arrive at conflicting conclusions about the future politics of the South. One problem is alternative regional definitions -- the survey category Solid South (which includes the states of the former Confederacy minus Tenn) or the combined categories Solid South & Border South. Another problem is the choice to analyze native whites, whites, or all election participants. Survey data presented here show that these choices are not neutral; rather, they influence research findings. If the intent is to build on the aggregate data-based research of V. O. Key, Jr., & others, one should use the Solid South definition. Moreover, if the intent is to predict the future politics of the South, one should analyze all election participants. 5 Tables. AA.

Purpose: To determine the current state of development of open science in the paradigm of open research data in Ukraine and the world, as well as to analyze the representation of Ukraine in the world research space, in terms of research data exchange. Design / Method / Research Approach: Methods of synthesis, logical and comparative analysis used to determine the dynamics of the number of research data journals and data files in the world, as well as to quantify the share of research data repositories in Ukraine and the world. Trend and bibliometric analysis were used to determine the share of publications with their open primary data; analysis of their thematic structures; identification of the main scientific clusters of such publications; research of geographic indicators and share of publications by research institutions. Findings: The study found a tendency to increase both the number of data logs and data files in Dryad (open data repository). The results of the analysis of the share of data repositories indexed in re3data (register of research data repositories) show that 51% of the total number are repositories of data from European countries, with Germany leading with 460 repositories, followed by the United Kingdom (302 repositories) and France (116 repositories). Ukraine has only 2 data repositories indexed in re3data. The trend of relevance of data exchange is confirmed by the increase of publications with datasets for the last 10 years (2011-2020) in 5 times. Research institutions and universities are the main sources of research data, which are mainly focused on the fields of knowledge in chemistry (23.3%); biochemistry, genetics and molecular biology (13.8%); medicine (12.9%). An analysis of the latest thematic groups formed on the basis of publications with datasets shows that there is a significant correlation between publications with open source data and COVID-19 studies. More than 50% of publications with datasets both in Ukraine and around the world are aimed at achieving the goal of SDG 3 Good Health. Theoretical Implications: It is substantiated that in Ukraine there is a need to implement specific tactical and strategic plans for open science and open access to research data. Practical Implications: The results of the study can be used to support decision-making in the management of research data at the macro and micro levels. Future Research: It should be noted that the righteous bibliometric analysis of the state of the dissemination of data underlying the research results did not include the assessment of quality indicators and compliance with the FAIR principles, because accessibility and reusability are fundamental components of open science, which may be an area for further research. Moreover, it is advisable to investigate the degree of influence of the disclosure of the data underlying the research result on economic indicators, as well as indicators of ratings of higher education, etc. Research Limitations: Since publications with datasets in Scopus-indexed journals became the information base of the analysis for our study, it can be assumed that the dataset did not include publications with datasets published in editions that the Scopus bibliographic database does not cover. Paper type: Theoretical