Our main product - HYDRA - is a query engine, based on an uprecedentedly powerful open Semantic Web service platform and a scalable proprietary architecture, algorithms and data structures. It can be used both as a powerful data federation engine and for self-service querying of data by non-technical users. Although the technology can be used in many domains, we are currently targeting Bioinformatics and Clinical Informatics as primary applications.
Data federation: query many sources as a single database
HYDRA can be used to query multiple distributed sources of data as a single database. Moreover, the data sources may be completely heterogeneous and include regular relational DB, online DBs, nomenclatures, ontologies, unstructured data such as scientific publication, Web services and various analytical programs. Practically any data that can be processed programmatically may be integrated with other resources. This unprecedented power of integration is achieved by wrapping the data sources as Web services of a special kind, and orchestrating them in the engine to answer queries.
Anyone can be a data scientist!
HYDRA may be also useful in scenarios when only a few or even just one database has to be queried, because it supports semantic querying and is accessible to non-technical users, such as biomedical researchers or physicians. For example, if one has an SQL database, most non-technical users won't be able to run ad hoc queries over it without help from programmers or DBAs, because this requires knowledge of SQL and details of the specific data schema. Semantic queries, in contrast, are formulated in terms of the subject domain and thus are much more accessible to non-technical users. Practically speaking, a database host can wrap his database as a number of SADI services, thus enabling its non-technical users to run multiple self-service ad hoc queries. HYDRA comes with an intelligent graphical user interface that facilitates such self-service query formulation through the use of keywords, similar to how they are used with Web search engines like Google, and simple graphical editing.
Published HYDRA case studies
- Interpreting ecotoxicology experiment data by discovering related information in multiple public databases.
Prior SADI case studies conducted with HYDRA's predecessor - SHARE - include:
- Integrating programs for structural analysis of small molecules with programs for ontology-based classification of molecules.
News and announcements
- June 2014. IPSNP has successfully completed a $158K IRAP-funded project and prototyped an intelligent self-service query composition GUI for HYDRA (some screenshots can be seen in these Clinical Intelligence pitch slides).
- Aug 30, 2013. HYDRA development team reaches another milestone: alpha version of the query engine is finalised.
- ENTREVESTOR: Company seeks testers for software that casts a wide net for information (on TheChronicleHerald.ca)
- Alexandre Riazanov, IPSNP's CTO, presented our technology at DILS'13 in Montreal on July 11: HYDRA - a SPARQL engine for data federation and self-service querying in the Life Sciences [slides].
- Artjom Klein, IPSNP's R&D engineer and UNB researcher, will give a tutorial on SADI at DILS'13 in Montreal on July 12: Semantic Automated Discovery and Integration
- Oct 18, 2012 press release: IPSNP receives private seed funding and financial assistance from NRC-IRAP