On-demand Metadata Management with Ontotext S4

Last week I had a chance to present the Self Service Semantic Suite (S4) at the LT-Accelerate conference in Brussels. LT-Accelerate is a new event focusing on language technology and its applications in various domains: social media analytics, market research, customer service, publishing, emergency response services, etc.

My S4 talk was about elaborating the most important questions – why Ontotext created it, what it is, and how organisations can benefit from it.

Ontotext has been delivering semantic data management solutions to organisations in a variety of verticals – from publishing & media, to digital libraries, life science and healthcare, government and finance. Despite the large differences between the specific verticals, many of the main challenges these organisations are facing are quite similar:

  • getting more insight from text and discovering relevant information
  • interlinking and searching across textual and structured data sources
  • integrating heterogeneous data sources and reducing the impact of schema evolution
  • reusing external Linked / Open Data sources to enrich internal data sources
  • discovering implicit relations between entities and analysing the entity graph

 

Ontotext’s approach for dealing with these challenges has always been based on Semantic Technologies: using RDF for agile data modeling and integration; using ontologies to bridge different schema and vocabularies; interlinking people, locations, organisations, events and topics into a knowledge graph which can then be further extended with external Linked Open Data; inferring new knowledge and using the graph to answer questions based on meaning, instead on structure or keywords.

While Semantic Technology provides a powerful means for smarter data management, it also has to overcome certain adoption challenges typical for technologies positioned in the early phases of the hype cycle: perceived risks, lack of in-house expertise, steep learning curve for mastering the technology, licensing and provisioning costs, and complex processes within the enterprise for evaluating and adopting a new technology.

This is why Ontotext has created the Self Service Semantic Suite (S4), so that the Semantic Technology we have been successfully delivering to enterprises for years, is now more accessible to a larger number of organisations: instantly available, in a pay-per-use manner with no upfront commitments and investments, and via easy to use web services in the Cloud.

S4 is built on top of three pillars: knowledge graphs, text analytics and RDF data management.

LTA2014-S4-MarinDimitrov

Knowledge graphs provide access to large amounts of Linked Open Data, from general purpose datasets such as DBpedia, Freebase and GeoNames, to specific datasets in the field of life sciences and healthcare, finance, government, etc. With S4, users can access such Linked Data in a reliable way via simple web services.

Text analytics services provide means to extract entities of interest from a variety of data sources: news, biomedical documents, or tweets. S4 text analytics services perform the proper disambiguation of the entities detected in text and linking to the specific instance from the knowledge graphs that the entity in text refers to

RDF databases as-a-service provide an easy way to manage RDF data, make publicly available 3rd party Linked Data sets, discover implicit relationships between entities and perform graph analytics.

In addition, all S4 services are running in the cloud and are instantly available via simple RESTful services. There’s no need for upfront licensing commitments, provisioning and maintenance – users can just pay for what they use. S4 offers a generous free tier which makes it possible for organisations to thoroughly test the technology and quickly develop simple prototypes. S4 is also designed in a way that ensures high availability and near real-time responses.

The S4 commitment is to make Semantic Technology easily and instantly available to all types of organisations. Register for your S4 developer account and start using text analytics, RDF databases and knowledge graphs in the Cloud today!

Marin Dimitrov

Marin Dimitrov

CTO at Ontotext
As the technological captain of Ontotext, he is leading the company on the right tech route and reserving our spot on the map of the world. His sharp mind can explain complex things in a simple way, making him an invaluable resource in semantics. Marin is a frequent speaker on semantic conferences and open data meetups at various technology related events.
Marin Dimitrov

Related Posts

  • Open data fosters a culture of creativity and innovation

    Open Data Innovation? Open Your Data And See It Happen.

    As more and more companies and startups are creating business and social value out of open data, the open data trend-setting governments and local authorities are not sitting idle and are opening up data sets and actively encouraging citizens, developers, and firms to innovate with open data.

  • Linked Open Data Sets

    Linked Data Innovation – A Key To Foster Business Growth

      ‘Data is the new oil’, once said Neelie Kroes,  former Vice-President of the European Commission responsible for the Digital Agenda, aptly describing how the growing amounts of data are changing businesses and our lives. The year…

  • featured image

    Linked Open Data for Cultural Heritage and Digital Humanities

    The Galleries, Libraries, Archives and Museums (GLAM) sector deals with complex and varied data. Integrating that data, especially across institutions, has always been a challenge. On the other hand, the value of linked data is especially high in this sector, since culture by its very nature is cross-border and interlinked.

Back to top