A Semantically Enriched Hypercat-enabled
          Internet of Things Data Hub

    Ilias Tachmazidis1 , John Davies2 , Sotiris Batsakis1 , Alistair Duke2 ,
              Grigoris Antoniou1 , and Sandra Stincic Clarke2
                   1
                       University of Huddersfield, Huddersfield, UK
                       2
                        British Telecommunications, Ipswich, UK



       Abstract. A huge amount of information is generated from the rapidly
       increasing number of sensor networks and smart devices, generating and
       publishing information in multiple formats, thus highlighting interop-
       erability as one of the key prerequisites for the success of the Internet
       of Things (IoT). The BT Hypercat Data Hub provides a focal point for
       the sharing and consumption of available datasets from a wide range of
       sources. In this work, we present a semantic enrichment of the data hub,
       using a number of widely-used Semantic Web standards and tools.


1    BT Hypercat Data Hub

Developing successful IoT solutions requires the collection and mainte-
nance of a wide range of heterogeneous IoT data. In this work, we describe
the basic components of the BT Hypercat Data Hub, which aggregates
and catalogues mulitple IoT data sources and exposes them via a uni-
form RESTful API. For more details readers are referred to [1]. Figure 1
presents a high level hierarchy of the developed system, more specifically:
 – The BT Hypercat Ontology enables the publication of an RDF-based
   Hypercat catalogue [2] as well as the translation of data stored in a
   relational database into RDF format.
 – RDF Adapters provide internally stored data in N-Triples format fol-
   lowing a systematic generation of URIs.
 – A SPARQL to SQL endpoint enables the dynamic translation of SPARQL
   queries into SQL queries, using Ontop3 .
 – The BT SPARQL Endpoint queries internally available SPARQL to
   SQL endpoints and combines SPARQL results, using Apache Jena4 .
 – Federated querying is enabled by providing a Jena endpoint that al-
   lows federated queries over the BT SPARQL Endpoint and SPARQL
   endpoints that are available through the Linked Open Data cloud.
3
    http://ontop.inf.unibz.it/
4
    https://jena.apache.org/index.html
                            Fig. 1. High Level Hierarchy.


    The system has been successfully deployed as part of two use cases.
The SimplifAI project is aimed at urban traffic management and control
in order to reduce traffic and improve air quality. The BT Hypercat Data
Hub was utilized for automated semantic enrichment of imported IoT
data. In addition, City Concierge is a use case of the CityVerve project
aiming to increase uptake of walking and cycling as a preferred travel
mode in Greater Manchester. The data hub provides the required infras-
tructure and functionality in order to enable the City Concierge through
the aggregation and exposure of city IoT information.

2    Conclusion
The semantic enrichment of the BT Hypercat Data Hub has been pre-
sented. Future work includes further semantic enrichment by enabling
GeoSPARQL queries. In addition, spatiotemporal reasoning is a promi-
nent direction that could provide richer knowledge by combining data
coming from both the BT Hypercat Data Hub and the LOD cloud.

References
1. Ilias Tachmazidis, Sotiris Batsakis, John Davies, Alistair Duke, Mauro Vallati, Grig-
   oris Antoniou, and Sandra Stincic Clarke. A hypercat-enabled semantic internet of
   things data hub. In The Semantic Web - 14th International Conference, ESWC
   2017, Portorož, Slovenia, May 28 - June 1, 2017, Proceedings, Part II, pages 125–
   137, 2017.
2. Ilias Tachmazidis, John Davies, Sotiris Batsakis, Grigoris Antoniou, Alistair Duke,
   and Sandra Stincic Clarke. Hypercat RDF: Semantic Enrichment for IoT. In Se-
   mantic Technology - 6th Joint International Conference, JIST 2016, Singapore, Sin-
   gapore, November 2-4, 2016, Revised Selected Papers, pages 273–286, 2016.