Upravljanje oz. ravnanje z raziskovalnimi podatki (Research Data Management ali RDM) je izraz, ki opisuje organizacijo, shranjevanje, arhiviranje in izmenjavo podatkov, ki so bili zbrani in uporabljeni v raziskovalnem projektu. Vključuje vsakodnevno ravnanje z raziskovalnimi podatki v času trajanja raziskovalnega projekta (npr. dosledna uporaba dogovorjenega poimenovanja datotek). Zajema tudi odločitve o tem, kako se bodo podatki hranili in delili po zaključku projekta (npr. hramba podatkov v repozitoriju za dolgotrajno arhiviranje in dostop).
Obstaja vrsta razlogov, zakaj je upravljanje raziskovalnih podatkov pomembno:
Priročnik o načrtovanju ravnanja z raziskovalnimi podatki
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Priročnik nudi osnovne informacije in praktične usmeritve za ravnanje z raziskovalnimi podatki v skladu z načeli odprte znanosti. Vsebuje ključne korake za ravnanje s podatki v vseh fazah raziskovalnega procesa.
Spoznaj FAIR: priročnik o odprti znanosti v Sloveniji
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Namen priročnika je različnim akterjem in akterkam s širokega polja znanstvenih disciplin v slovenskem jeziku predstaviti temeljne pojme o odprti znanosti ter približati raziskovalno infrastrukturo in storitve, ki v slovenskem okolju služijo odprti znanosti in se hkrati neločljivo povezujejo z evropskim ter s širšim mednarodnim raziskovalnim prostorom.
23 točk za knjižničarke in knjižničarje: Podpora pri delu z raziskovalnimi podatki
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Dokument predstavlja zbirko virov o ravnanju z raziskovalnimi podatki. Temelji na dokumentu 23 Things: Libraries for Research Data, za slovensko okolje pa ga je priredila delovna skupina za podporo pri RDA vozlišču Slovenija.
Engaging Researchers with Data Management
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Effective Research Data Management (RDM) is a key component of research integrity and reproducible research, and its importance is increasingly emphasised by funding bodies, governments, and research institutions around the world. However, many researchers are unfamiliar with RDM best practices, and research support staff are faced with the difficult task of delivering support to researchers across different disciplines and career stages. What strategies can institutions use to solve these problems? Engaging Researchers with Data Management is an invaluable collection of 24 case studies, drawn from institutions across the globe, that demonstrate clearly and practically how to engage the research community with RDM. These case studies together illustrate the variety of innovative strategies research institutions have developed to engage with their researchers about managing research data. Each study is presented concisely and clearly, highlighting the essential ingredients that led to its success and challenges encountered along the way. By interviewing key staff about their experiences and the organisational context, the authors of this book have created an essential resource for organisations looking to increase engagement with their research communities. This handbook is a collaboration by research institutions, for research institutions. It aims not only to inspire and engage, but also to help drive cultural change towards better data management. It has been written for anyone interested in RDM, or simply, good research practice.
Data Management for Researchers
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A comprehensive guide to everything scientists need to know about data management, this book is essential for researchers who need to learn how to organize, document and take care of their own data. Researchers in all disciplines are faced with the challenge of managing the growing amounts of digital data that are the foundation of their research. Kristin Briney offers practical advice and clearly explains policies and principles, in an accessible and in-depth text that will allow researchers to understand and achieve the goal of better research data management. Data Management for Researchers includes sections on: * The data problem - an introduction to the growing importance and challenges of using digital data in research. Covers both the inherent problems with managing digital information, as well as how the research landscape is changing to give more value to research datasets and code. * The data lifecycle - a framework for data's place within the research process and how data's role is changing. Greater emphasis on data sharing and data reuse will not only change the way we conduct research but also how we manage research data. * Planning for data management - covers the many aspects of data management and how to put them together in a data management plan. This section also includes sample data management plans. * Documenting your data - an often overlooked part of the data management process, but one that is critical to good management; data without documentation are frequently unusable. * Organizing your data - explains how to keep your data in order using organizational systems and file naming conventions. This section also covers using a database to organize and analyze content. * Improving data analysis - covers managing information through the analysis process. This section starts by comparing the management of raw and analyzed data and then describes ways to make analysis easier, such as spreadsheet best practices. It also examines practices for research code, including version control systems. * Managing secure and private data - many researchers are dealing with data that require extra security. This section outlines what data falls into this category and some of the policies that apply, before addressing the best practices for keeping data secure. * Short-term storage - deals with the practical matters of storage and backup and covers the many options available. This section also goes through the best practices to insure that data are not lost. * Preserving and archiving your data - digital data can have a long life if properly cared for. This section covers managing data in the long term including choosing good file formats and media, as well as determining who will manage the data after the end of the project. * Sharing/publishing your data - addresses how to make data sharing across research groups easier, as well as how and why to publicly share data. This section covers intellectual property and licenses for datasets, before ending with the altmetrics that measure the impact of publicly shared data. * Reusing data - as more data are shared, it becomes possible to use outside data in your research. This chapter discusses strategies for finding datasets and lays out how to cite data once you have found it. This book is designed for active scientific researchers but it is useful for anyone who wants to get more from their data: academics, educators, professionals or anyone who teaches data management, sharing and preservation. "An excellent practical treatise on the art and practice of data management, this book is essential to any researcher, regardless of subject or discipline." --Robert Buntrock, Chemical Information Bulletin
Managing and sharing research data : a guide to good practice
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Research funders in the UK, USA and across Europe are implementing data management and sharing policies to maximize openness of data, transparency and accountability of the research they support. Written by experts from the UK Data Archive with over 20 years experience, this book gives post-graduate students, researchers and research support staff the data management skills required in today's changing research environment. The book features guidance on: how to plan your research using a data management checklist how to format and organize data how to store and transfer data research ethics and privacy in data sharing and intellectual property rights data strategies for collaborative research how to publish and cite data how to make use of other people's research data, illustrated with six real-life case studies of data use.
Exploring Research Data Management
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Read a blog post by one of the authors now! Research Data Management (RDM) has become a professional topic of great importance internationally following changes in scholarship and government policies about the sharing of research data. Exploring Research Data Management provides an accessible introduction and guide to RDM with engaging tasks for the reader to follow and develop their knowledge. Starting by exploring the world of research and the importance and complexity of data in the research process, the book considers how a multi-professional support service can be created. It then examines the decisions that need to be made in designing different types of research data service from local policy creation, training, through to creating a data repository. Coverage includes a discussion of the drivers and barriers to RDM; institutional policy and making the case for Research Data Services; practical data management; data literacy and training researchers; ethics and research data services; and case studies and practical advice from working in a Research Data Service.
Managing Research Data
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This title defines what is required to achieve a culture of effective data management offering advice on the skills required, legal and contractual obligations, strategies and management plans and the data management infrastructure of specialists and services. Data management has become an essential requirement for information professionals over the last decade, particularly for those supporting the higher education research community, as more and more digital information is created and stored. As budgets shrink and funders of research demand evidence of value for money and demonstrable benefits for society, there is increasing pressure to provide plans for the sustainable management of data. Ensuring that important data remains discoverable, accessible and intelligible and is shared as part of a larger web of knowledge will mean that research has a life beyond its initial purpose and can offer real utility to the wider community. This edited collection, bringing together leading figures in the field from the UK and around the world, provides an introduction to all the key data issues facing the HE and information management communities. Each chapter covers a critical element of data management: Why manage research data? The lifecycle of data management Research data policies: principles, requirements and trends Sustainable research data Data management plans and planning Roles and responsibilities – libraries, librarians and data Research data management: opportunities and challenges for HEIs The national data centres Contrasting national research data strategies: Australia and the USA Emerging infrastructure and services for research data management and curation in the UK and Europe. Readership: This is essential reading for librarians and information professionals working in the higher education sector, the research community, policy makers and university managers. It will also be a useful introduction for students taking courses in information management, archivists and national library services.
Vprašanja glede odprte znanosti in ravnanja z raziskovalnimi podatki lahko naslovite na naslov odprimo@um.si.
Raziskovalni vodič Upravljanje z raziskovalnimi podatki je nastal s pomočjo virov
Raziskovalni vodič Upravljanje z raziskovalnimi podatki avtorja Brina Klemenčič je objavljen pod licenco Creative Commons Priznanje avtorstva 4.0 Mednarodna.