1 - 33 of 33 results

OBI / Ontology for Biomedical Investigations

Provides terms with precisely defined meanings to describe all aspects of how investigations in the biological and medical domains are conducted. OBI re-uses ontologies that provide a representation of biomedical knowledge from the Open Biological and Biomedical Ontologies (OBO) project and adds the ability to describe how this knowledge was derived. This ontology supports the consistent annotation of biomedical investigations, regardless of the particular field of study. The ontology represents the design of an investigation, the protocols and instrumentation used, the material used, the data generated and the type analysis performed on it. The OBI project is an open cross-disciplinary collaborative effort, encompassing multiple research communities from around the globe. To date, OBI has created 2366 classes and 40 relations along with textual and formal definitions.

OnEX / Ontology Evolution Explorer

A system for exploring ontology changes. Currently, OnEX provides access to about 520 versions of 16 well-known life science ontologies. The system is based on a three-tier architecture including an ontology version repository, a middleware component and the OnEX web application. Interactive workflows allow a systematic and explorative change analysis of ontologies and their concepts as well as the semi-automatic migration of out-dated annotations to the current version of an ontology.

T-GROWLer

An ontology-based workflow pattern extractor. TGROWLeR system abstracts general patterns from workflow sequences previously extracted from texts. It comprises two modules (a workflow extractor and a pattern miner) both relying on a specific domain ontology. TGROWLeR methodology extends classic NLP techniques to extract and disambiguate tasks in texts. Using a graph-based representation of workflows and a domain ontology, the extraction process uses a context-based approach to recognize workflow components: data and control flows.

ODP / Ontology Design Patterns

Offers a collection of well documented and tested ontology design patterns (ODPs), including examples from the biological knowledge domain, implemented in web ontology language (OWL). ODP is a ready-made solution for tackling complex modelling issues when creating and maintaining bio ontologies. It also provides a bridge to rich and rigorous modelling, and offers advantages in design (rich and granular modelling; semantic encapsulation; robustness and modularity; reasoning; alignment), implementation (focused development; tooling; rapid prototyping; re-engineering) and communication (good communication; documented modelling; comprehension of advances in knowledge representation).

OTO / Ontology Term Organizer

A user-friendly, web-based, consensus-promoting, open source application for organizing domain terms by dragging and dropping terms to appropriate locations. The application is designed for users with specific domain knowledge such as biology but not in-depth ontology construction skills. Specifically OTO can be used to establish is_a, part_of, synonym, and order relationships among terms in any domain that reflects the terminology usage in source literature and based on multiple experts' opinions. The organized terms may be fed into formal ontologies to boost their coverage. All datasets organized on OTO are publicly available.

Protégé

Allows creation and edition of ontologies. Protégé is an ontology editor and framework, with support for the OWL 2 Web Ontology Language, that provides a suite of tools for ontology development and use. The tools range from creating the terminology (GUI, visualization, and versioning support) to deployment and application development (user feedback management, API, and application support). The software is also available as WebProtege, a Web-based tool for the collaborative development of OWL 2 ontologies.

IMGT-ONTOLOGY

Allows scientists and clinicians to use, for the first time, identical terms with the same meaning in immunogenetics. IMGT-ONTOLOGY provides a semantic repository that will improve interoperability between specialist and generalist databases. It provides a semantic classification and standardization of the knowledge in the immunogenetics field used to identify the sequences, to describe their detailed composition, to classify Ig and TcR genes, and to define in which experimental, biological or medical context the sequences have been obtained.

SPARQLGraph

A web-based platform for querying biological Semantic Web databases in a graphical way. SPARQLGraph offers an intuitive drag & drop query builder, which converts the visual graph into a query and executes it on a public endpoint. The tool integrates several publicly available Semantic Web databases, including the databases of the just recently released EBI RDF platform. Furthermore, it provides several predefined template queries for answering biological questions. Users can easily create and save new query graphs, which can also be shared with other researchers.

SORTA / System for Ontology-based Re-coding and Technical Annotation

Obsolete
Assists in matching data values in a semi-automatic way with standard codes like local terminologies or ontologies. SORTA facilitates data cleaning and coding and recoding by automatically shortlisting the standard codes via matching. The recoding process offers three features: (1) search and query, (2) reasoning with data and (3) exchange or pooling of data across systems. It exploits the lexical similarity in percentage for building a most relevant standard codes list.

DBonto

Develops next generation semantics-aware data management systems that are based on a synthesis of ontological reasoning and database management principles. DBonto incorporate techniques from many other areas of computer science, particularly those that give a complementary view of "Big Data" management, such as algorithms and machine learning, stream processing, and information retrieval. At the same time, this database aims to make important contributions to the career development of the next generation of research leaders.