(S3 E6) First class research objects, FAIR data and where next for Open Science with Professor Hu... скачать в хорошем качестве

(S3 E6) First class research objects, FAIR data and where next for Open Science with Professor Hu...

In our weekly Research Culture Uncovered conversations we are asking what is Research Culture and why does it matter? This episode is part of Season 3, hosted by Nick Sheppard who will be speaking to colleagues from both the University of Leeds and from other universities and organizations about open research, what it is, how it's practiced in different disciplines, and how it relates to research culture. In this episode Nick is joined by Hugh Shanahan, Professor of Open Science at Royal Holloway University of London. Hugh has expertise in computational biology and statistics. He's co-chair of the Codata, RDA Schools of Research Data Science, and Vice-Chair of the World Data System Scientific Committee. You can connect with Hugh via Twitter (  / hughshanahan  ) or LinkedIn (  / hugh-shanahan-340b343  ) In this episode we talk about: • Hugh's varied academic background that led him to a professorship in Open Science • Different definitions of open science, which in addition to making scientific research more efficient and transparent, also encompasses research integrity, community and equality • How open research differs from open science, and that it needs to be defined by its practitioners in a specific discipline • The different professional roles that contribute to open research beyond scientists, researchers and academics themselves • Openness as a spectrum, that it's not all or nothing: it’s possible to take small, practical and useful steps which can be built on incrementally • Recent progress embedding open research principles in universities in the UK and beyond • The concept of the "first class research object" as the components of research - datasets, software and code, protocols - that are often as important as a final published journal article • Underpinning research infrastructure, and its importance to open science: repositories, preprint servers, computational notebooks and persistent identifiers (DOIs, ORCiD) • The relationship between open research training, and reward and recognition: people need the skills to be rewarded for the practice • The FAIR data principles and that data should be findable, accessible, interoperable and reusable. What do these concepts mean in practice? • Priorities for open science in the future, in particular bringing together generic support with more disciplinary expertise Be sure to check out the other episodes in this season! Links: • CODATA-RDA Schools of Research Data Science (https://www.datascienceschools.org/ab...) • World Data System Scientific Committee (https://worlddatasystem.org/about/sci...) • Open from beginning to end: addressing barriers to open research (https://leedsunilibrary.wordpress.com...) (online event with Hugh hosted at Leeds in May 26 2021) • The Software Heritage Archive (https://archive.softwareheritage.org/) • Project Jupyter (https://jupyter.org/) • NeuroLibre - a preprint server for reproducible data analyses (https://www.neurolibre.org/) • CORE - the world's largest collection of open access research papers (https://core.ac.uk/) • GO-FAIR - FAIR Implementation Profile (https://www.go-fair.org/how-to-go-fai...)