Basic facts URL of the live web application: http://tree.datafabric.cc1 (launched on 17.07.2017). Product type: subscription-based commercial web application. Application domains: business intelligence, data analytics. Semantic technologies (ST) employed: RDF, OWL, knowledge graphs, SPARQL. Volume: 2.8 bil. triples, 10 mil. companies, 12 mil. individual entrepreneurs, 27 mil. persons, 333 Gb of raw unstructured data.
Throughout the last 3-4 years Russian authorities have made great volumes of data collected and maintained by government services open and accessible to the people. The knowledge concealed in these data is of a great business value and open a new prominent opportunities for services that o er convenient and e cient ways of nding, exploring and discovering the hidden relations and structures that the data contain. In our case, the published open data required a tremendous e ort in merging various bits, checking and distilling it before it could be used in an application. We demonstrate how the linked data and visual analytics are able to satisfy the information needs for o cial registry data exploration and save the user's time in the process of business investigation. Finally, from the market perspective, despite the existence of well-established tools for business intelligence over the open government data, we observe an unsatised demand for the a ordable, easy-to-use and lightweight services targeted to individuals and small and medium businesses.
Our web service allows users a) to search the registry for the entity of interest b) create a graph and explore visually its connections to other companies, persons, etc. c) produce a user-generated report about entity's background. The service requires subscription fee to be paid up front. To access the full functionality of the service for reviewing purposes please use the following credentials: login: iswc2017review@example.com, password: demo. 1 English version (for demo purposes only): http://tree-i8n.apps.datafabric.cc
ST In The Product
The added value of ST
Expected business value from utilizing ST: a) simpler and cheaper integration of
additional sources of data; b) cheaper custom development; c) richer user
experience - discovery-provoking visual exploration of company context.
The role of ST in the architecture of the application: The application is
comprised of 4 major parts: data extract-transform-load (ETL) pipeline hosted on
google cloud, RDF-triple store deployed on open source version of Blazegraph2,
server-side logic and request handling service running on Kotlin and Node.js and
frontend user interface logic and rendering implemented using ReactJS and open
source Ontodia library3. On all stages of data transformation from storing the
data to visualizing it we employ ST: data is stored in RDF graph with OWL
ontology applied to it in ETL process, data is queried with SPARQL, data is
visualized in the form of a graph by conversion of RDF into nodes and edges.
Advantages of using ST in our application
{ We apply ST standards to explicate the knowledge concealed in the raw data
by transforming the semi-structured XML les into cumulative RDF graph
with well-de ned data schema expressed in a form of OWL ontology .
{ On the basis of ST we align the internal graph-based data structures with
their graph-based diagrammatic visualization in Ontodia library[