“Data Stewardship Wizard”: A Tool Bringing Together Researchers, Data Stewards, and Data Experts around Data Management Planning

Pergl, Robert; Hooft, Rob; Suchánek, Marek; Knaisl, Vojtěch; Slifka, Jan

doi:10.5334/dsj-2019-059

Cited by 37 publications

(35 citation statements)

References 6 publications

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“…Out of thirteen repositories created for the BioHackathon Europe, ten of them were very active mostly during the event but commits declined after it while the remaining three showed a good number of commits even after the event. Although all of the participant projects are of interest for the Life Sciences community and bring in advances and developments worth sharing, we want to highlight these three cases as they correspond to projects (or at least code repositories) which started during the event and grew after it, i.e., they showed some post-event continuity, a desirable, although not always possible, effect on the BioHackathon projects.These three projects correspond to (i) a Data Management Plan template part of the Data Stewardship Wizard (Pergl, Hooft, Suchanek, Knaisl, & Slifka, 2019), a well established part of the ELIXIR Europe network, (ii) PubDictionaries, part of the PubAnnotation tools ecosystem (Kim et al, 2019), a text mining platform for Bioinformatics offered by DBCLS, and (iii) an ontology related to COVID-19 epidemiology and monitoring. The latter started as a research project at the COVID-19 Virtual BioHackathon held in 2019 and, since then, has continued evolving.…”

Section: Github-based Measuresmentioning

confidence: 99%

Measuring outcomes and impact from the BioHackathon Europe

Castro¹,

Martin²,

Lazarov³

et al. 2021

Preprint

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One of the recurring questions when it comes to BioHackathons is how to measure their impact, especially when funded and/or supported by the public purse (e.g., research agencies, research infrastructures, grants). In order to do so, we first need to understand the outcomes from a BioHackathon, which can include software, code, publications, new or strengthened collaborations, along with more intangible effects such as accelerated progress and professional and personal outcomes. In this manuscript, we report on three complementary approaches to assess outcomes of three BioHackathon Europe events: survey-based, publication-based and GitHub-based measures. We found that post-event surveys bring very useful insights into what participants feel they achieved during the hackathon, including progressing much faster on their hacking projects, broadening their professional network and improving their understanding of other technical fields and specialties. With regards to published outcomes, manual tracking of publications from specific servers is straightforward and useful to highlight the scientific legacy of the event, though there is much scope to automate this via text-mining. Finally, GitHub-based measures bring insights on some of the software and data best practices (e.g., license usage) but also on how the hacking activities evolve in time (e.g., activities observed in GitHub repositories prior, during and after the event). Altogether, these three approaches were found to provide insightful preliminary evidence of outcomes, thereby supporting the value of financing such large-scale events with public funds.

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Section: Github-based Measuresmentioning

confidence: 99%

Measuring outcomes and impact from the BioHackathon Europe

Castro¹,

Martin²,

Lazarov³

et al. 2021

Preprint

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“…Estas plataformas online são o resultado dos esforções por colaborar com pesquisadores e administradores de dados a criar PGDs inteligentes para projetos de Ciência Aberta alinhados com os princípios FAIR atendendo aos requisitos dos patrocinadores, possibilitando colaboração em tempo real, customização de questionários e listas de verificação para garantir consistência e compatibilidade entre planos de contextos diferentes, além de oferecer serviços para simplificar o gerenciamento, validação, monitoramento e manutenção dos PGDs auxiliando no gerenciamento de datasets, proveniência de dados e versionamento, ademais de apresentar de forma simplificada as informações do plano numa interface limpa [Argos, 2021;Dmptool, 2021;Ds-wizard, 2021;Pergl et al, 2019;Simms and Jones, 2017].…”

Section: Ds Wizard Dmponline Dmptool E Argosunclassified

Criação de Planos de Gestão de Dados em Projetos de Ciência de Dados para Detecção de Fake News Apoiados pelos princípios FAIR

Zavaleta

Pinheiro

Cerceau

et al. 2021

Anais Da VII Escola Regional De Sistemas De Informação Do Rio De Janeiro (ERSI-RJ 2021)

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Pesquisadores da área de Ciência de Dados vivenciam uma realidade cada vez mais multifacetada no que diz respeito à governança de dados. Mudança do paradigma de silos de dados desconectados para planos de gestão de dados (PGD) e repositórios padronizados online aderentes aos princípios FAIR ainda não é uma realidade. Este texto discute, compara plataformas e, descreve o percurso semi-automatizado de criação PGD, com aplicação em projetos de Machine Learning adotados na detecção de Fake News. Como resultados, oferecemos um trajeto para elaboração de PGDs na plataforma DS-Wizard e a oferta de um artigo do tipo executável sobre o projeto que pode ser executado pelos leitores.

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“…The DMP Tool (Strasser, Abrams, & Cruse, 2014), for instance, is an online tool that supports designing and implementing a DMP. The Data Stewardship Wizard (Pergl, Hooft, Such´anek, Knaisl, & Slifka, 2019) is a web application for supporting the creation of DMPs by presenting hierarchical questionnaires to data stewards, researchers, and data scientists. These questionnaires leverage knowledge collected from the research data management community on best practices for elaborating DMPs.…”

Section: Data Planning and Collectionmentioning

confidence: 99%

A survey of biodiversity informatics: Concepts, practices, and challenges

Gadelha

Siracusa

Dalcin

et al. 2020

WIREs Data Min & Knowl

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The unprecedented size of the human population, along with its associated economic activities, has an ever‐increasing impact on global environments. Across the world, countries are concerned about the growing resource consumption and the capacity of ecosystems to provide resources. To effectively conserve biodiversity, it is essential to make indicators and knowledge openly available to decision‐makers in ways that they can effectively use them. The development and deployment of tools and techniques to generate these indicators require having access to trustworthy data from biological collections, field surveys and automated sensors, molecular data, and historic academic literature. The transformation of these raw data into synthesized information that is fit for use requires going through many refinement steps. The methodologies and techniques applied to manage and analyze these data constitute an area usually called biodiversity informatics. Biodiversity data follow a life cycle consisting of planning, collection, certification, description, preservation, discovery, integration, and analysis. Researchers, whether producers or consumers of biodiversity data, will likely perform activities related to at least one of these steps. This article explores each stage of the life cycle of biodiversity data, discussing its methodologies, tools, and challenges. This article is categorized under: Algorithmic Development > Biological Data Mining

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“Data Stewardship Wizard”: A Tool Bringing Together Researchers, Data Stewards, and Data Experts around Data Management Planning

Cited by 37 publications

References 6 publications

Measuring outcomes and impact from the BioHackathon Europe

Measuring outcomes and impact from the BioHackathon Europe

Criação de Planos de Gestão de Dados em Projetos de Ciência de Dados para Detecção de Fake News Apoiados pelos princípios FAIR

A survey of biodiversity informatics: Concepts, practices, and challenges

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