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The InnoRenew CoE Renewable Materials and Healthy Environments Research and Innovation Centre of Excellence is a young interdisciplinary research institute with two key research areas: wood modification and restorative environmental and ergonomic design. It was established as part of the InnoRenew project funded by the Horizon 2020 Framework of the European Union (H2020 WIDESPREAD-2-2Teaming: #739574) and has received investment funding of the Republic of Slovenia and the European Union of the European Regional Development Fund. In September 2017 the InnoRenew CoE and its project partners prepared the InnoRenew project and InnoRenew CoE Data management plan (DMP). The DMP was based on a survey of researchers at the institute and partner institutions regarding the kinds of data that they plan to collect and in what form, about metadata standards they use, about possible privacy and security issues, and about their previous practices of storing research data. The DMP is quite complex, as it covers the activities of researchers from various disciplines and each has specific challenges. Some of the planned research involves human subjects, so it addresses ethical and legal issues regarding personal data protection as well.

"Research methods courses have become a compulsory component of most degree programs in sport management. This is the first introductory research methods textbook to focus exclusively on sport management. Through the use of examples, cases and data taken from the real world of sport management it opens up a traditionally dry area of study, helping the student to understand the vital importance of sound methodology in their studies and subsequent professional practice. The book covers the full range of quantitative and qualitative methods across the whole span of the research process, from research design and the literature review to data analysis and report writing. Every chapter contains a range of useful features to aid student learning, including summaries, discussion questions and guides to further resources, as well as examples drawn from contemporary sport around the world. Research Methods for Sport Management is an essential course text for all sport management students and an invaluable reference for any sport management professional involved in operational research"--

With its new general programme "Horizon 2020" the European Commission has made research data an essential topic of science policy and research funding. Over the last few years numerous universities and research facilities have felt out the current documentary practices of their researchers by surveys. In 2015 within the framework of e-Infrastructures Austria there was a survey in which 3,000 researchers of 20 public universities and 3 extramural research institutions participated. This report shows several findings as well as suggestions derived from the survey about the preferable future of research data management. ; Mit ihrem neuen Rahmenprogramm "Horizon 2020" hat die Europäische Kommission das Thema Forschungsdaten zu einem zentralen Thema der Forschungspolitik und der Forschungsförderung gemacht. Zahlreiche Hochschulen und Forschungseinrichtungen haben in den letzten Jahren mittels Umfragen die aktuelle Praxis ihrer Forschenden im Umgang mit Forschungsdaten ergründet. 2015 wurde im Rahmen von e-Infrastructures Austria eine österreichweite Befragung durchgeführt, an der sich 3.000 Forschende an 20 öffentlichen Universitäten sowie an drei außeruniversitären Forschungseinrichtungen beteiligt haben. Im vorliegenden Beitrag werden einzelne Ergebnisse sowie aus der Umfrage abgeleitete Empfehlungen für den wünschenswerten zukünftigen Umgang mit Forschungsdaten vorgestellt.

The existing body of knowledge has witnessed gaps arising from the paucity of research literature on the quality of educational research output in higher education. This study shows how the management of data in higher education affects the quality of academic research conducted by university lecturers in South-South Nigeria. A sample of 602 lecturers were accessed during data collection and responded to two questionnaires (Data Management Practices Questionnaire – DMPQ and "Educational Research Effectiveness Questionnaire – EREQ). Multiple regression was employed in the analysis of data. Findings revealed amongst others that; data storage, data security, data retrieval, data sharing, and data re-use jointly contributed to the total variance in educational research effectiveness of university lecturers in terms of proper citations by 56.25%, problem-solving by 22.14%, knowledge creation by 34.50%, and generation of testable data by 36.88%. The five data management practices compositely influences the educational research effectiveness of university lecturers in terms of proper citations (F=152.25,p<.05), problem-solving (F=33.90,p<.05), knowledge creation (F=62.78,p<.05), and the generation of testable data (F=69.65,p<.05), is statistically significant. Based on the findings of this study, it was concluded that data management practices (storage, security, retrieval, sharing, and re-use) jointly and relatively contributes to the total variance in educational research effectiveness in terms of proper citations, problem-solving, knowledge creation and generation of testable data at varying extents. It was recommended, among others that, lecturers should practice the habit of managing research data in their personal computers and through manual channels. These records could become vital in the future for further problem-solving.

Data Organization and Management

This paper urges organizational researchers to collect data from subjects in the form of pictures, diagrams, computer graphics, and other visual representations. Drawing on theoretical and empirical work in cognitive psychology, neurophysiology, linguistics, and artificial intelligence, it presents a rationale for collecting visual data, provides examples, and suggests research questions and settings where visual data may be preferable to verbal data.

PurposeThe purpose of this study is to map current knowledge on big data analytics (BDA) for supply chain risk management (SCRM) while providing future research needs.Design/methodology/approachThe research team systematically reviewed 53 articles published between 2015 and 2021 and further contrasted the synthesis of these articles with four in-depth interviews with BDA startups that provider solutions for SCRM.FindingsThe analysis is framed in three perspectives. First, supply chain visibility – i.e. the number of tiers in the solutions; second, BDA analytical approach – descriptive, prescriptive or predictive approaches; third, the SCRM processes from risk monitoring to risk optimization. The study underlines that the forefront of innovation lies in multi-tiered, multi-directional solutions based on prescriptive BDA to support risk response and optimization (SCRM). In addition, we show that research on these innovations is scant, thus offering an important avenue for future studies.Originality/valueThis study makes relevant contributions to the field. We offer a theoretical framework that highlights the key relationships between supply chain visibility, BDA approaches and SCRM processes. Despite being at forefront of the innovation frontier, startups are still an under-explored agent. In times of major disruptions such as COVID-19 and the emergence of a plethora of new technologies that reshape businesses dynamically, future studies should map the key role of such actors to the advancement of SCRM.

Aspects of Data Management