Group items tagged

Be able to distinguish between various types of research data. Recognise the importance of managing ancillary research materials. Be able to use the information featured in the course to contribute to research data management best practice. Understand the general rules of appropriate data management in accordance with responsible conduct of research. Be aware of good practice in managing research data in general and apply it within your own work context. Use the information featured in the unit to draw up a data management plan and maintain it through the course of your research. Understand why research data organisation or housekeeping is important. Recognise the importance of managing data file versioning, naming and re-naming conventions. Be able to use the information featured in the course to contribute to research data management best practice. Understand why research data formatting and transformation is important. Know how to make decisions about data file formatting, compression, normalisation and other transformations. Use the information featured in the course to contribute to research data management best practice. Understand why documenting your research data is important. Know why and when to use metadata. Use the information featured in this unit to contribute to research data management best practice. Be aware of the options available to you to safely store your data. Recognise the importance of data backups. Use the information featured in the unit to secure your data through the course of your research. Be aware of ethical requirements that apply to the collection and management of data involving human subjects. Understand the difference between privacy and confidentiality and how they apply to the management of research data. Be aware of the UK Data Protection Act and its consequences for research. Know what IPR is and how it applies to your research data. Know how Freedom of Information and related legislation affects legitimate access to your da

Lien vers les présentations : - Aims and Introduction - Jonathan Tedds, University of Leicester/ PREPARDE - Data Centre workflows for publication - Sarah Callaghan, BADC/ PREPARDE - Geoscience Data Journal: developing a workflow for cross-linking between dataset and Data Paper - Tim Roberts, Wiley/PREPARDE - Data aggregations for facilities science - Vasily Bunakov, STFC - Linking datasets with user commentary, annotations and publications: the CHARMe project - Jon Blower, University of Reading - The OpenAIRE Scholarly Communication Infrastructure: On Interlinking Datasets, Literature, Fundings, and Research Initiatives - Paolo Manghi, OpenAIREplus - Interlinking Articles & Data in the Article of the Future - Bethan Keall, Elsevier - Data citation and persistent identifiers: the DataCite approach - Elizabeth Newbold, British Library

Lesson 01: Why Data Management Lesson 02: Data Sharing Lesson 03: Data Management Planning Lesson 04: Data Entry and Manipulation Lesson 05: Data Quality Control and Assurance Lesson 06: Data Protection and Backups Lesson 07: Metadata Lesson 08: How to Write Good Quality Metadata Lesson 09: Data Citation Lesson 10: Analysis and Workflows

Open Context publishes data contributed by researchers through a process that reviews, edits, and aligns data to standards. Major aspects of publishing with Open Contexct include: - Excavation, survey and collections data published in a citable venue - Data safeguarded and preserved though archiving with the University of California's California Digital Library - Expert editorial and peer review of your project's data - Tools to track citations of your data along with your other publications - All data published free and open access for barrier-free search, discovery and analysis - Data aligned to key "Linked Open Data" standards to facilitate future analyses, data integration, visualization, and understanding Domaine : archaeological datasets and museum collections Fournit un ensemble de services à haute valeur ajoutée. Utilise les méthodes des Linked Open Data : annotation des données avec : - Geographic places reference GeoNames.org and Pleiades - Biological taxa reference the Encyclopedia of Life - Units of measurement reference Freebase identifers - Biological morphology references use UBERON

Data publishing : http://www.pensoft.net/page.php?P=23

This paper discusses many of the issues associated with formally publishing data in academia, focusing primarily on the structures that need to be put in place for peer review and formal citation of datasets. Data publication is becoming increasingly important to the scientific community, as it will provide a mechanism for those who create data to receive academic credit for their work and will allow the conclusions arising from an analysis to be more readily verifiable, thus promoting transparency in the scientific process. Peer review of data will also provide a mechanism for ensuring the quality of datasets, and we provide suggestions on the types of activities one expects to see in the peer review of data. A simple taxonomy of data publication methodologies is presented and evaluated, and the paper concludes with a discussion of dataset granularity, transience and semantics, along with a recommended human-readable citation syntax. PDF de l'article en libre accès.

Rapport de 47 pages, récent (avril 2013). L'objectif du document est de faire un état de l'art pour analyser les meilleures pratiques et encourager l'évaluation des données. L'hypothèse est que cet angle encouragerait le partage des données par les chercheurs. Intéressant aussi pour nous : les annexes - annexe 1 : grille d'analyse des entrepôts - annexe 2 : inventaire et analyse de quelques entrepôts - annexe 3 : liste de Data Journals

"promote best practices in data citation to facilitate access to data sets and to enable attribution and reward for those who publish data"

Cet article rapporte une étude réalisée en 2011 et 2012 sur un lot de 170 journaux classés dans un certain nombre de disciplines du JCR (dominante : sciences informatiques) et associés à des FI de différents niveaux. Méthode * Examen en juin 2011 puis en juin 2012 des sites web des 170 journaux pour vérifier leur politique en matière de : Data Sharing, Code Sharing, Supplementary Materials * Evaluation de la politique de chaque journal sur les 5 points suivants : 1. Partage de données exigé comme condition de publication, certaines exceptions autorisées (par exemple, pour des aspects de confidentialité ) 2. Partage demandé mais sans influence sur les décisions éditoriales et la publication 3. Dépôt explicitement encouragé ; les données peuvent être révisées et / ou hébergées 4. Partage Implicite 5. Aucune mention du partage de données et pondération supplémentaire basée sur l'évaluation d'autres critères : o partage de données réalisé lors du processus de soumission ou à la demande des reviewers, ou pas précisé o partage de données réservé ou tout public o partage de données pour tous les articles ou réservé aux articles riches en données o autorisation de dépôt sur le site de l'auteur soit de la version auteur seulement, soit de la version publiée o type de reviewing (des données, des codes, des supplementary materials) et les possibilités ou non d'hébergement des données. Résultats accessibles à l'URL : http://www.stodden.net/JournalPolicies2013/ * La majorité des journaux examinés n'affichent pas clairement leur politique en matière de partage et codage de données. En cela, ils ne suivent pas les recommandations du « National Academies committee » (2003) * En juin 2012, 62% des journaux ne faisaient aucune mention de politique en matière de partage de données, et 79

There is a need to establish a new publishing paradigm to cope with the deluge of data artifacts produced by data-intensive science, many of which are vital to data re-use and verification of published scientific conclusions. Due to the limitations of traditional publishing, most of these artifacts are not usually disseminated, cited, or preserved. Intéressant pour la définition de la notion de "Data paper"

Il s'agit d'un projet 2012-2013 financé par l'ACLS Digital Innovation Fellowship.

Présentation ppt - IASSIST, Cologne, 2013/05/31 Intègre différentes questions : - qu'est ce qu'est un data paper/article - comment le soumettre ? - liste de journaux qualifiés de Data Journals - projet PREPARDE (Peer Review for Publication & Accreditation of Research Data in the Earth Sciences) - projet PRIME (Publisher, Repository and Institutional Metadata Exchange) - projet JoRD

The re3data.org registry allows the easy identification of appropriate research data repositories, both for data producers and users. The registry covers research data repositories from all academic disciplines. Information icons display the principal attributes of a repository, allowing users to identify the functionalities and qualities of a data repository. By April 2013, 338 research data repositories were indexed in re3data.org (http://doi.org/kv3).

Politique des éditeurs concernant les données, dans le domaine économique. A rapprocher de JoRD. (EDaWaX = European Data Watch eXtended) the management of publication related research data in economics is still at its early stages. We were able to find 29 journals with data availability policies.

This guide will help you decide how to apply a licence to your research data, and which licence would be most suitable. It should provide you with an awareness of why licensing data is important, the impact licences have on future research, and the potential pitfalls to avoid.

A data paper is a journal publication whose primary purpose is to describe data, rather than to report a research investigation.

Rapport de 40 p., mis à jour en 2011. Il s'agit d'un guide de bonnes pratiques orienté sur les besoins du chercheur. Les différentes étapes sont décrites : pourquoi partager ses données, comment ? - le plan de management des données, l'indexation des données, le formatage, le stockage, les aspects éthiques ...

The Policy RECommendations for Open Access to Research Data in Europe (RECODE) project will leverage existing networks, communities and projects to address challenges within the open access and data dissemination and preservation sector and produce policy recommendations for open access to research data based on existing good practice.