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  • Comment
    | Open Access

    “Speak to the past and it shall teach thee”. I first read those words on a dedication tablet within the John Carter Brown library at Brown University where I was a graduate student. Little did I know the phrase would accurately describe the next three and a half decades of my career. Paleoclimate data are the language we use to look into the past to understand ourselves and ultimately our future.

    • Harry Dowsett
  • Comment
    | Open Access

    Efficient response to the pandemic through the mobilization of the larger scientific community is challenged by the limited reusability of the available primary genomic data. Here, the Genomic Standards Consortium board highlights the essential need for contextual genomic data FAIRness, for empowering key data-driven biological questions.

    • Lynn M. Schriml
    • , Maria Chuvochina
    • , Neil Davies
    • , Emiley A. Eloe-Fadrosh
    • , Robert D. Finn
    • , Philip Hugenholtz
    • , Christopher I. Hunter
    • , Bonnie L. Hurwitz
    • , Nikos C. Kyrpides
    • , Folker Meyer
    • , Ilene Karsch Mizrachi
    • , Susanna-Assunta Sansone
    • , Granger Sutton
    • , Scott Tighe
    •  & Ramona Walls
  • Comment
    | Open Access

    The Coronavirus Infectious Disease Ontology (CIDO) is a community-based ontology that supports coronavirus disease knowledge and data standardization, integration, sharing, and analysis.

    • Yongqun He
    • , Hong Yu
    • , Edison Ong
    • , Yang Wang
    • , Yingtong Liu
    • , Anthony Huffman
    • , Hsin-hui Huang
    • , John Beverley
    • , Junguk Hur
    • , Xiaolin Yang
    • , Luonan Chen
    • , Gilbert S. Omenn
    • , Brian Athey
    •  & Barry Smith
  • Comment
    | Open Access

    As information and communication technology has become pervasive in our society, we are increasingly dependent on both digital data and repositories that provide access to and enable the use of such resources. Repositories must earn the trust of the communities they intend to serve and demonstrate that they are reliable and capable of appropriately managing the data they hold.

    • Dawei Lin
    • , Jonathan Crabtree
    • , Ingrid Dillo
    • , Robert R. Downs
    • , Rorie Edmunds
    • , David Giaretta
    • , Marisa De Giusti
    • , Hervé L’Hours
    • , Wim Hugo
    • , Reyna Jenkyns
    • , Varsha Khodiyar
    • , Maryann E. Martone
    • , Mustapha Mokrane
    • , Vivek Navale
    • , Jonathan Petters
    • , Barbara Sierman
    • , Dina V. Sokolova
    • , Martina Stockhause
    •  & John Westbrook
  • Comment
    | Open Access

    Researchers around the world join forces to reconstruct the molecular processes of the virus-host interactions aiming to combat the cause of the ongoing pandemic.

    • Marek Ostaszewski
    • , Alexander Mazein
    • , Marc E. Gillespie
    • , Inna Kuperstein
    • , Anna Niarakis
    • , Henning Hermjakob
    • , Alexander R. Pico
    • , Egon L. Willighagen
    • , Chris T. Evelo
    • , Jan Hasenauer
    • , Falk Schreiber
    • , Andreas Dräger
    • , Emek Demir
    • , Olaf Wolkenhauer
    • , Laura I. Furlong
    • , Emmanuel Barillot
    • , Joaquin Dopazo
    • , Aurelio Orta-Resendiz
    • , Francesco Messina
    • , Alfonso Valencia
    • , Akira Funahashi
    • , Hiroaki Kitano
    • , Charles Auffray
    • , Rudi Balling
    •  & Reinhard Schneider
  • 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
  • Comment
    | Open Access

    The Brain Imaging Data Structure (BIDS) project is a rapidly evolving effort in the human brain imaging research community to create standards allowing researchers to readily organize and share study data within and between laboratories. Here we present an extension to BIDS for electroencephalography (EEG) data, EEG-BIDS, along with tools and references to a series of public EEG datasets organized using this new standard.

    • Cyril R. Pernet
    • , Stefan Appelhoff
    • , Krzysztof J. Gorgolewski
    • , Guillaume Flandin
    • , Christophe Phillips
    • , Arnaud Delorme
    •  & Robert Oostenveld
  • Comment
    | Open Access

    The Brain Imaging Data Structure (BIDS) is a community-driven specification for organizing neuroscience data and metadata with the aim to make datasets more transparent, reusable, and reproducible. Intracranial electroencephalography (iEEG) data offer a unique combination of high spatial and temporal resolution measurements of the living human brain. To improve internal (re)use and external sharing of these unique data, we present a specification for storing and sharing iEEG data: iEEG-BIDS.

    • Christopher Holdgraf
    • , Stefan Appelhoff
    • , Stephan Bickel
    • , Kristofer Bouchard
    • , Sasha D’Ambrosio
    • , Olivier David
    • , Orrin Devinsky
    • , Benjamin Dichter
    • , Adeen Flinker
    • , Brett L. Foster
    • , Krzysztof J. Gorgolewski
    • , Iris Groen
    • , David Groppe
    • , Aysegul Gunduz
    • , Liberty Hamilton
    • , Christopher J. Honey
    • , Mainak Jas
    • , Robert Knight
    • , Jean-Philippe Lachaux
    • , Jonathan C. Lau
    • , Christopher Lee-Messer
    • , Brian N. Lundstrom
    • , Kai J. Miller
    • , Jeffrey G. Ojemann
    • , Robert Oostenveld
    • , Natalia Petridou
    • , Gio Piantoni
    • , Andrea Pigorini
    • , Nader Pouratian
    • , Nick F. Ramsey
    • , Arjen Stolk
    • , Nicole C. Swann
    • , François Tadel
    • , Bradley Voytek
    • , Brian A. Wandell
    • , Jonathan Winawer
    • , Kirstie Whitaker
    • , Lyuba Zehl
    •  & Dora Hermes
  • Comment
    | Open Access

    Although increasingly recognized as critical to genomic research, genomic data sharing is hindered by an absence of standards regarding timing, patient privacy, use agreement standards, and data characterization and quality. Only after months of identifying, permissioning for use, committing to terms restricting use and sharing, downloading, and assessing quality, is it possible to know whether or not a dataset can be used. In this paper, we evaluate the barriers to data sharing based on the Treehouse experience and offer recommendations for use agreement standards, data characterization and metadata standardization to enhance data sharing and outcomes for all pediatric cancer patients.

    • Katrina Learned
    • , Ann Durbin
    • , Robert Currie
    • , Ellen Towle Kephart
    • , Holly C. Beale
    • , Lauren M. Sanders
    • , Jacob Pfeil
    • , Theodore C. Goldstein
    • , Sofie R. Salama
    • , David Haussler
    • , Olena Morozova Vaske
    •  & Isabel M. Bjork
  • Comment
    | Open Access

    There is an urgent need to improve integrity of large industrial infrastructure. Sharing data can support better understanding of accidents such as recent mining dam collapses, making them less likely to occur, and contributing to sustainability.

    • Paulo A. de Souza Jr.
  • Comment
    | Open Access

    The number of chemical compounds and associated experimental data in public databases is growing, but presently there is no simple way to access these data in a quick and synoptic manner. Instead, data are fragmented across different resources and interested parties need to invest invaluable time and effort to navigate these systems.

    • Sten Ilmjärv
    • , Fiona Augsburger
    • , Jerven Tjalling Bolleman
    • , Robin Liechti
    • , Alan James Bridge
    • , Jenny Sandström
    • , Vincent Jaquet
    • , Ioannis Xenarios
    •  & Karl-Heinz Krause
  • Comment
    | Open Access

    The past two decades have seen a revolution in digital imaging techniques for capturing gross morphology, offering an unprecedented volume of data for biological research. Despite the rapid increase in scientific publications incorporating those images, the underlying datasets remain largely inaccessible. As the technical barriers to data sharing continue to fall, we face a more intimate, and perhaps more complicated, obstacle to open data – the one in our minds.

    • Christy A. Hipsley
    •  & Emma Sherratt
  • Comment
    | Open Access

    The breadcrumbs we leave behind when using our mobile phones—who somebody calls, for how long, and from where—contain unprecedented insights about us and our societies. Researchers have compared the recent availability of large-scale behavioral datasets, such as the ones generated by mobile phones, to the invention of the microscope, giving rise to the new field of computational social science.

    • Yves-Alexandre de Montjoye
    • , Sébastien Gambs
    • , Vincent Blondel
    • , Geoffrey Canright
    • , Nicolas de Cordes
    • , Sébastien Deletaille
    • , Kenth Engø-Monsen
    • , Manuel Garcia-Herranz
    • , Jake Kendall
    • , Cameron Kerry
    • , Gautier Krings
    • , Emmanuel Letouzé
    • , Miguel Luengo-Oroz
    • , Nuria Oliver
    • , Luc Rocher
    • , Alex Rutherford
    • , Zbigniew Smoreda
    • , Jessica Steele
    • , Erik Wetter
    • , Alex “Sandy” Pentland
    •  & Linus Bengtsson
  • Comment
    | Open Access

    • Thomas Pasquier
    • , Matthew K. Lau
    • , Ana Trisovic
    • , Emery R. Boose
    • , Ben Couturier
    • , Mercè Crosas
    • , Aaron M. Ellison
    • , Valerie Gibson
    • , Chris R. Jones
    •  & Margo Seltzer
  • Comment
    | Open Access

    • Mark D. Wilkinson
    • , Michel Dumontier
    • , IJsbrand Jan Aalbersberg
    • , Gabrielle Appleton
    • , Myles Axton
    • , Arie Baak
    • , Niklas Blomberg
    • , Jan-Willem Boiten
    • , Luiz Bonino da Silva Santos
    • , Philip E. Bourne
    • , Jildau Bouwman
    • , Anthony J. Brookes
    • , Tim Clark
    • , Mercè Crosas
    • , Ingrid Dillo
    • , Olivier Dumon
    • , Scott Edmunds
    • , Chris T. Evelo
    • , Richard Finkers
    • , Alejandra Gonzalez-Beltran
    • , Alasdair J.G. Gray
    • , Paul Groth
    • , Carole Goble
    • , Jeffrey S. Grethe
    • , Jaap Heringa
    • , Peter A.C ’t Hoen
    • , Rob Hooft
    • , Tobias Kuhn
    • , Ruben Kok
    • , Joost Kok
    • , Scott J. Lusher
    • , Maryann E. Martone
    • , Albert Mons
    • , Abel L. Packer
    • , Bengt Persson
    • , Philippe Rocca-Serra
    • , Marco Roos
    • , Rene van Schaik
    • , Susanna-Assunta Sansone
    • , Erik Schultes
    • , Thierry Sengstag
    • , Ted Slater
    • , George Strawn
    • , Morris A. Swertz
    • , Mark Thompson
    • , Johan van der Lei
    • , Erik van Mulligen
    • , Jan Velterop
    • , Andra Waagmeester
    • , Peter Wittenburg
    • , Katherine Wolstencroft
    • , Jun Zhao
    •  & Barend Mons