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Latest Research

News & Comment

  • Comment
    | Open Access

    A significant challenge facing rare disease communities is finding a sufficient quantity and variety of data to develop and test disease-specific hypotheses. Here we describe an approach to data sharing in which stakeholders from the neurofibromatosis (NF) research community collaborated to develop a disease-focused data portal with the goal of supporting scientists within and outside the community as well as clinicians and patient advocates.

    • Robert J. Allaway
    • , Salvatore La Rosa
    • , Sharad Verma
    • , Lara Mangravite
    • , Justin Guinney
    • , Jaishri Blakeley
    • , Annette Bakker
    •  & Sara J. C. Gosline
  • Comment
    | Open Access

    We outline a principled approach to data FAIRification rooted in the notions of experimental design, and whose main intent is to clarify the semantics of data matrices. Using two related metabolomics datasets associated to journal articles, we perform retrospective data and metadata curation and re-annotation, using community, open, interoperability standards. The results are semantically-anchored data matrices, deposited in public archives, which are readable by software agents for data-level queries, and which can support the reproducibility and reuse of the data underpinning the publications.

    • Philippe Rocca-Serra
    •  & Susanna-Assunta Sansone
  • Comment
    | Open Access

    In the past decade, there has been a surge in the number of sensitive human genomic and health datasets available to researchers via Data Access Agreements (DAAs) and managed by Data Access Committees (DACs). As this form of sharing increases, so do the challenges of achieving a reasonable level of data protection, particularly in the context of international data sharing. Here, we consider how excessive variation across DAAs can hinder these goals, and suggest a core set of clauses that could prove useful in future attempts to harmonize data governance.

    • Katie M. Saulnier
    • , David Bujold
    • , Stephanie O. M. Dyke
    • , Charles Dupras
    • , Stephan Beck
    • , Guillaume Bourque
    •  & Yann Joly
  • Comment
    | Open Access

    Climate change cannot be addressed without improving the energy efficiency of the buildings in which we live and work. The papers in this collection describe and release a series of datasets that help us understand how occupants influence and experience building energy use, both to aid future research and policy-development, and to spark wider data sharing in this important area.

    • Gesche Margarethe Huebner
    •  & Ardeshir Mahdavi
  • Comment
    | Open Access

    A special collection on multi-omics data sharing, launched today at Scientific Data, offers to the scientific community a compendium of multi-omics datasets ready for reuse, which showcase the diversity of multi-omics projects and highlights innovative approaches for preprocessing, quality control, hosting and access.

    • Ana Conesa
    •  & Stephan Beck
  • Comment
    | Open Access

    UniProt continues to support the ongoing process of making scientific data FAIR. Here we contribute to this process with a FAIRness assessment of our UniProtKB dataset followed by a critical reflection on the challenges and future directions of the adoption and validation of the FAIR principles and metrics.

    • Leyla Garcia
    • , Jerven Bolleman
    • , Sebastien Gehant
    • , Nicole Redaschi
    • , Maria Martin
    • , Alex Bateman
    • , Michele Magrane
    • , Maria Martin
    • , Sandra Orchard
    • , Shriya Raj
    • , Shadab Ahmad
    • , Emanuele Alpi
    • , Emily Bowler
    • , Ramona Britto
    • , Borisas Bursteinas
    • , Hema Bye-A-Jee
    • , Tunca Dogan
    • , Leyla Garcia
    • , Penelope Garmiri
    • , George Georghiou
    • , Leonardo Gonzales
    • , Emma Hatton-Ellis
    • , Alexandr Ignatchenko
    • , Giuseppe Insana
    • , Rizwan Ishtiaq
    • , Vishal Joshi
    • , Dushyanth Jyothi
    • , Jie Luo
    • , Yvonne Lussi
    • , Alistair MacDougall
    • , Mahdi Mahmoudy
    • , Andrew Nightingale
    • , Carla Oliveira
    • , Joseph Onwubiko
    • , Vivek Poddar
    • , Sangya Pundir
    • , Guoying Qi
    • , Ahmet Rifaioglu
    • , Daniel Rice
    • , Rabie Saidi
    • , Elena Speretta
    • , Edward Turner
    • , Nidhi Tyagi
    • , Preethi Vasudev
    • , Vladimir Volynkin
    • , Kate Warner
    • , Xavier Watkins
    • , Rossana Zaru
    • , Hermann Zellner
    • , Alan Bridge
    • , Lionel Breuza
    • , Elisabeth Coudert
    • , Damien Lieberherr
    • , Ivo Pedruzzi
    • , Sylvain Poux
    • , Manuela Pruess
    • , Nicole Redaschi
    • , Lucila Aimo
    • , Ghislaine Argoud-Puy
    • , Andrea Auchincloss
    • , Kristian Axelsen
    • , Parit Bansal
    • , Delphine Baratin
    • , Teresa Batista Neto
    • , Marie-Claude Blatter
    • , Jerven Bolleman
    • , Emmanuel Boutet
    • , Cristina Casals-Casas
    • , Beatrice Cuche
    • , Edouard De Castro
    • , Anne Estreicher
    • , Livia Famiglietti
    • , Marc Feuermann
    • , Elisabeth Gasteiger
    • , Sebastien Gehant
    • , Vivienne Gerritsen
    • , Arnaud Gos
    • , Nadine Gruaz
    • , Ursula Hinz
    • , Chantal Hulo
    • , Nevila Hyka-Nouspikel
    • , Florence Jungo
    • , Arnaud Kerhornou
    • , Philippe Lemercier
    • , Thierry Lombardot
    • , Patrick Masson
    • , Anne Morgat
    • , Sandrine Pilbout
    • , Monica Pozzato
    • , Catherine Rivoire
    • , Christian Sigrist
    • , Shyamala Sundaram
    • , Cathy Wu
    • , Cecilia Arighi
    • , Hongzhan Huang
    • , Peter McGarvey
    • , Darren Natale
    • , Leslie Arminski
    • , Chuming Chen
    • , Yongxing Chen
    • , John Garavelli
    • , Kati Laiho
    • , Karen Ross
    • , C. R. Vinayaka
    • , Qinghua Wang
    • , Yuki Wang
    • , Lai-Su Yeh
    •  & Jian Zhang

Collection

Multi-Omics Data Sharing

'Multi-omics' refers to a family of complex experimental designs where researchers apply more than one molecular profiling technology – capturing, for example, the genome, proteome and metabolome – across a common set of biological samples. These experiments offer a wealth of opportunities for subsequent analyses, but the size of the resulting datasets and the diversity of the study designs makes data sharing inherently challenging. In this collection, we present a series of multi-omics studies where the authors have used innovative means to maximize the accessibility and reusability of their datasets.
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