Find open-source science resources
A directory of tools, AI models, datasets, and research resources for biotech, bioinformatics, and other scientific fields. Aggregated from curated GitHub awesome-lists, HuggingFace, bio.tools, Bioconductor, and more.
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2,418 of 5,923 resources
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The Semantic Web for Earth and Environmental Terminology is a mature foundational ontology that contains over 6000 concepts organized in 200 ontologies represented in OWL. Top level concepts include Representation (math, space, science, time, data), Realm (Ocean, Land Surface, Terrestrial Hydroshere, Atmosphere, etc.), Phenomena (macro-scale ecological and physical), Processes (micro-scale physical, biological, chemical, and mathematical), Human Activities (Decision, Commerce, Jurisdiction, Environmental, Research).
BioCompute is shorthand for the IEEE 2791-2020 standard for Bioinformatics Analyses Generated by High-Throughput Sequencing (HTS) to facilitate communication. This pipeline documentation approach has been adopted by a few FDA centers. The goal is to ease the communication burdens between research centers, organizations, and industries. This web portal allows users to build a BioCompute Objects through the interface in a human and machine readable format.
DOAP is a project to create an XML/RDF vocabulary to describe software projects, and in particular open source projects.
A controlled vocabulary to support the study of transcription in the primate brain
The AOPO provides classes and relationships for the semantic representation of the Adverse Outcome Pathway framework.
MIBiG (Minimum Information about a Biosynthetic Gene Cluster) is a data repository and associated data standard designed to describe biosynthetic gene clusters involved in the production of specialized metabolites. It also stores data on measured biological activities and links to other resources such as NCBI, NPAtlas, and ChEBI. MIBiG is used as a reference database, knowledgebase, and training dataset for machine learning.
MIMIC-III is a dataset comprising health-related data associated with over 40,000 patients who stayed in critical care units of the Beth Israel Deaconess Medical Center between 2001 and 2012
OntoDM-core defines the most essential data mining entities in a three-layered ontological structure comprising of a specification, an implementation and an application layer. It provides a representational framework for the description of mining structured data, and in addition provides taxonomies of datasets, data mining tasks, generalizations, data mining algorithms and constraints, based on the type of data. OntoDM-core is designed to support a wide range of applications/use cases, such as semantic annotation of data mining algorithms, datasets and results; annotation of QSAR studies in the context of drug discovery investigations; and disambiguation of terms in text mining. (from abstract)
This is a vocabulary for educational sectors as used in the OER World Map (https://oerworldmap.org)
This SKOS vocabulary describes types of primary and secondary schools in Germany, such as Grundschule, Gymnasium, and Realschule. This does not include post-secondary education such as universities or hochschulen.
This is a code repository for the SIB - Swiss Institute of Bioinformatics CALIPHO group neXtProt project, which is a comprehensive human-centric discovery platform, that offers a integration of and navigation through protein-related data. CALIPHO is an interdisciplinary team which aims to use a variety of methodologies to help uncover the function of uncharacterized human proteins.
The FRBR-aligned Bibliographic Ontology (FaBiO) is an ontology for describing entities that are published or potentially publishable (e.g., journal articles, conference papers, books), and that contain or are referred to by bibliographic references.
The covid-19 epidemiology and monitoring ontology (cemo) provides a common ontological model to make epidemiological quantitative data for monitoring the covid-19 outbreak machine-readable and interoperable to facilitate its exchange, integration and analysis, to eventually support evidence-based rapid response.
The Science Data Discovery Ontology (sddo) is being developed to provide a semantic foundation for the discovery of information managed by NASA's Science Mission Directorate. This information spans many scientific disciplines, fields and subfields, including heliophysics, earth science, planetary science, astrophysics, biology, astrobiology, and physical science. [from repository]
Algorithm Metadata Vocabulary is a vocabulary for capturing and storing the metadata about the algorithms (a procedure or a set of rules that is followed step-by-step to solve a problem, especially by a computer). There are uncountable algorithms present in every area (e.g., Computer Science, Mathematics), which makes it hard for specialists, academicians, application engineers, and so forth to discover, distinguish, select, and reuse them. [from repository]
An ontology transcription of definitions in the Functional Mock-up Interface (FMI) standard document from https://fmi-standard.org/ that enables representing Functional Mock-up Units (FMUs) in RDF
An ontology to support disciplinary annotation of Arctic Data Center datasets.
An ontology encoding the Common Information Model (CIM) schema
This proposed vocabulary allows edges in Property Graphs (e.g Neo4j, RDF*) to be augmented with edge properties that specify ontological semantics, including (but not limited) to OWL-DL interpretations. [from GitHub]
The Reagent Ontology (ReO) adheres to OBO Foundry principles (obofoundry.org) to model the domain of biomedical research reagents, considered broadly to include materials applied “chemically” in scientific techniques to facilitate generation of data and research materials. ReO is a modular ontology that re-uses existing ontologies to facilitate cross-domain interoperability. It consists of reagents and their properties, linking diverse biological and experimental entities to which they are related. ReO supports community use cases by providing a flexible, extensible, and deeply integrated framework that can be adapted and extended with more specific modeling to meet application needs.
The Semantic Resource Types Vocabulary was created for NSF's EarthCube Program's Resource Repository. Includes entries for things like 'thesaurus', 'ontology', 'controlled vocabulary', 'taxonomy'.
The Data Model Language Controlled Vocabulary was created for NSF's EarthCube Program's Resource Registry. At this point it merely lists a few of the languages used by data model resources in the registry.
The Audience Types Controlled Vocabulary was created for NSF's EarthCube program's Resource Registry. The vocabulary defines the types of audience each resource in the program is targeted to. At this point the vocabulary is very bare - no term definitions even; however, the intention is to extend the vocabulary over time. If you would like to assist with this or in extending any of the other controlled vocabularies/ontologies developed as part of the Resource Registry project, please see https://github.com/earthcubearchitecture-ecresourcereg.
This mini-ontology contains classes and instances for each version of the licenses that are commonly used in software projects, particularly open source software projects. The URI's for each are the canonical URI's for that license (where they exist).
The Extensible Observation Ontology (OBOE) is a formal ontology for capturing the semantics of scientific observation and measurement. The ontology supports researchers to add detailed semantic annotations to scientific data, thereby clarifying the inherent meaning of scientific observations.
An ontology that allows the description of numerical and categorical bibliometric data (e.g., journal impact factor, author h-index, categories describing research careers) in RDF.
An ontology for describing the administrative information of research projects, e.g., grant applications, funding bodies, project partners, etc.
An ontology based on PRO for describing the contributions that may be made, and the roles that may be held by a person with respect to a journal article or other publication (e.g. the role of article guarantor or illustrator).
An ontology that permits the number of in-text citations of a cited source to be recorded, together with their textual citation contexts, along with the number of citations a cited entity has received globally on a particular date.
An ontology meant to define bibliographic records, bibliographic references, and their compilation into bibliographic collections and bibliographic lists, respectively.
An ontology that enables characterization of the nature or type of citations, both factually and rhetorically.
An ontology for the characterisation of the roles of agents – people, corporate bodies and computational agents in the publication process. These agents can be, e.g. authors, editors, reviewers, publishers or librarians.
TogoID is an ID conversion service implementing unique features with an intuitive web interface and an API for programmatic access. TogoID supports datasets from various biological categories such as gene, protein, chemical compound, pathway, disease, etc. TogoID users can perform exploratory multistep conversions to find a path among IDs. To guide the interpretation of biological meanings in the conversions, we crafted an ontology that defines the semantics of the dataset relations. (from https://togoid.dbcls.jp/)