Inspired by the efforts of scientists around the world
and the game-changing efforts of projects like the
Creative Commons, the Wikipedia Foundation, and the Free
Software movement, we
hope to engage the larger community in an open and
fruitful discussion on issues concerning the use and
reuse of scientific data, including the balance of
openness and how to make ends meet in an increasingly
competitive environment.
If you would like to join our efforts to highlight the
use and reuse of data in the sciences, please feel free
to contact us on
our tracker
or create a pull request against
our repository.
We are not lawyers and this is not legal advice: all
institutions and groups have their own perspectives
and counsel. We are a group of scientists, engineers,
and specialists that are concerned about the use and
reuse of increasingly interconnected, derived, and
reprocessed data. We want to make sure that
data-driven scientific endeavors can work with one
another in meaningful ways without undue legal
concerns.
The (Re)usable Data Project is meant provide a
resource that looks at some of the issues
around the reuse of scientific data and open a
conversation about how to deal with them.
We also want to actively work with the community in
considering our criteria and in making sure that our
information about scientific data resources is
up-to-date and correct. If you have any questions,
concerns, or see any problems, please open a ticket on
our GitHub
tracker.
The initial driving concern of this project is the use
and reuse of biological and biomedical data. However,
this is a general problem in the scientific community
and needs to be addressed directly. For each
resource, using
our criteria, we attempt
to objectively assign zero to five stars for how well
we believe a resource's data may build upon, edited,
modified, and redistributed. Grossly speaking:
5 stars★ ★ ★ ★ ★
The license unambiguously allows the unfettered (re)use
and redistribution of the data.
4 stars★ ★ ★ ★
The license unambiguously allows (re)use and
redistribution of the data under some terms.
3 stars★ ★ ★
The license is clearly stated, unambiguous, and of
a standard type, and has clear access, but has
terms that may greatly impact the (re)use and
redistribution of the data.
2.5 or less stars★ ★ ½ - ∅
There are likely issues in definitively finding
the license, ambiguities in the license that
hamper further analysis, issues with clean data
access, or terms that require legal advice.
If you see any problems with our determinations or would
like to make corrections or clarifications, please open
a ticket for us on
our issue
tracker.
This is a short overview of the criteria that we use
when evaluating a resource's data license for use and
reuse. We have attempted to balance many needs
(credit, mutability, commercialization,
redistribution, etc.) and focused on trying to
objectively see how licenses can interact across
resources.
To learn more about how we look at resource data
licenses, please see
our criteria
and license type
pages.
Clearly stated
A clearly stated, unambiguous, and hopefully
standard, license for data use is critical for any
(re)use of data: if there is no license to be
found, then rights are unclear and one needs to
assume the default: all rights reserved.
more »
Comprehensive and non-negotiated
Data that is mixed under different licenses, only
partially available, or must be in some way
negotiated creates barriers to the (re)use of
data. more »
Accessible
Data must be accessible in a reasonable and manner
to be useful to the broader
community. more »
Avoid restrictions on kinds of (re)use
Data should be able to be copied, built upon,
edited, and modified as freely as
possible. more
»
Avoid restrictions who may (re)use
Data should should be available to as many people
as possible for their
(re)use. more
»
Bgee is a database to retrieve and compare gene expression patterns in multiple animal species, produced from multiple data types (RNA-Seq, Affymetrix, in situ hybridization, and EST data).
After some search we were unable to determine the license of the non-ontology portions of the BGee data. No explicit license statements were apparent, causing a cascade of criteria violations. In spite of this, access itself is clear, so one star is awarded accordingly for C.
Bgee is a database to retrieve and compare gene expression patterns in multiple animal species, produced from multiple data types (RNA-Seq, Affymetrix, in situ hybridization, and EST data).
CTD promotes understanding about the effects of environmental chemicals on human health by integrating data from curated scientific literature to describe chemical interactions with genes and proteins, and associations between diseases and chemicals, and diseases and genes/proteins.
The database of Genotypes and Phenotypes (dbGaP) was developed to archive and distribute the data and results from studies that have investigated the interaction of genotype and phenotype in Humans. Provides authorized access to protected and raw data (e.g., Genotype-Tissue Expression (GTEx) project).
Per the dgGaP data use certification, 'The terms and conditions of using dbGaP data vary by study'. All terms and conditions are to align with NIH GDS.
The Encyclopedia of DNA Elements (ENCODE) Consortium is an international collaboration of research groups funded by the National Human Genome Research Institute (NHGRI). The goal of ENCODE is to build a comprehensive parts list of functional elements in the human genome, including elements that act at the protein and RNA levels, and regulatory elements that control cells and circumstances in which a gene is active.
We are complex multicellular organisms composed of ~400 distinct cell types. This diversity of cell types allow us to see, think, hear, fight infections etc. yet all of this is encoded in the same genome. The difference between all these cells is what parts of the genome they use – for instance, neurons use different genes than muscle cells, and therefore they work very differently. In FANTOM5, we have systematically investigated exactly what are the sets of genes used in virtually all cell types across the human body, and the genomic regions which determine where the genes are read from. We aim to use this information to build transcriptional regulatory models for every primary cell type that makes up a human.
Copyright statement includes 'This publication may be copied for non-commercial, scientific uses by individuals or organizations (including for-profit organizations). FlyBase is freely distributed to the scientific community on the understanding that it will not be used for commercial gain by any organization. Any commercial use of this publication, or any parts thereof, is expressly prohibited without permission in writing from the FlyBase consortium.'
The Genotype-Tissue Expression (GTEx) project aims to provide to the scientific community a resource with which to study human gene expression and regulation and its relationship to genetic variation. This project will collect and analyze multiple human tissues from donors who are also densely genotyped, to assess genetic variation within their genomes. By analyzing global RNA expression within individual tissues and treating the expression levels of genes as quantitative traits, variations in gene expression that are highly correlated with genetic variation can be identified as expression quantitative trait loci, or eQTLs.
A curated database of human hereditary syndromes from OMIM, Orphanet, and DECIPHER mapped to classes of the human phenotype ontology. Various meta-attributes such as frequency, references and negations are associated with each annotation. These are presently limited to rare mendelian diseases.
The International Mouse Phenotyping Consortium (IMPC) is generating a knockout mouse strain for every protein coding gene by using the embryonic stem cell resource generated by the International Knockout Mouse Consortium (IKMC). Systematic broad-based phenotyping is performed by each IMPC center using standardized procedures found within the International Mouse Phenotyping Resource of Standardised Screens (IMPReSS) resource. Gene-to-phenotype associations are made by a versioned statistical analysis.
MGI is the international database resource for the laboratory mouse, providing integrated genetic, genomic, and biological data to facilitate the study of human health and disease.
biology, MOD, genotype (strain)-phenotype association
★ ★ ★ ★ ½
The Mouse Phenome Database is a collaborative standardized collection of measured data on laboratory mouse strains, and includes: baseline phenotype data sets; studies of drug, diet, disease and aging effect; protocols, projects, and publications; and SNP, variation and gene expression studies. MPD collects data for classical inbred strains, other fixed-genotype strains, derived lines and populations that are openly acquirable (strain panel examples). Strains can be from JAX-Mice or from any other vendor that\'s a recognized breeding source.
biology, genomic resource, gene definition, taxon definition, gene-publication association
★ ½
Gene integrates information from a wide range of species. A record may include nomenclature, Reference Sequences (RefSeqs), maps, pathways, variations, phenotypes, and links to genome-, phenotype-, and locus-specific resources worldwide.
biology, veterinary x-species, gene-disease association
★ ★ ★
Online Mendelian Inheritance in Animals (OMIA) is a catalogue/compendium of inherited disorders, other (single-locus) traits, and genes in 215 (non-model) animal species.
Orphanet provides reference information on rare diseases and orphan drugs to help improve the diagnosis, care and treatment of patients with rare diseases.
The PANTHER (Protein ANalysis THrough Evolutionary Relationships) Classification System was designed to classify proteins (and their genes) according to evolutionary family/subfamily, molecular function, biological process, and pathway. The PANTHER Classifications are the result of human curation as well as sophisticated bioinformatics algorithms.
Reactome is a free, open-source, curated and peer reviewed pathway database. Our goal is to provide intuitive bioinformatics tools for the visualization, interpretation and analysis of pathway knowledge to support basic research, genome analysis, modeling, systems biology and education.
KEGG gene and pathway annotations used to construct Reactome Functional Interaction (FI) Network are not licenced CC-BY-4.0. There is a comment that "the recipient may not distribute this data to other users without a license from Pathway Solutions, Inc."
WormBase is an international consortium dedicated to providing the research community with accurate, current, accessible information concerning the genetics, genomics and biology of C. elegans and related nematodes.
A single license is not provided, rather data users are intructed that they are responsible for identifying and complying with licensing and copyright restrictions for each piece of information in the database.
The Zebrafish Information Resource is the community database resource for the laboratory use of zebrafish which develops and supports integrated zebrafish genetic, genomic and developmental information, maintains the definitive reference data sets of zebrafish research information toward facilitation of the use of zebrafish as a model for human biology.
