KE4WoTChallengeWWW2018
Knowledge Extraction for the Web of Things (KE4WoT): Co-located with World Wide Web Conference (WWW 2018)
Description of the KE4WoT Challenge
The Web of Things (WoT) is an extension of the Internet of Things (IoT) to ease the access to data using the benefits of Web technologies. Data is generated by things/devices and then exploited by more and more web-based applications to monitor healthcare or even control home automation devices. There is a growing interest within standardization in designing models to represent devices and produced data as demonstrated by the following standards. Those models should be used to design interoperable smart web-based WoT applications:
- W3C Semantic Sensor Networks (SSN) \cite{compton2012ssn} is the first initiative to address interoperability issues to describe sensor networks through an ontology since devices are required to build WoT applications. A new version of the ontology\footnote{\url{https://www.w3.org/TR/vocab-ssn/}} has been recently released and became a W3C recommendation in October 2017. It is a joint contribution with the Open Geospatial Consortium standard, extending and improving the SSN ontology published in 2011. %Further, the new release of SSN is a joint effort with the OGC Sensor Web Enablement (SWE) standard.
- W3C Web of Things (WoT) Interest Group is designing a vocabulary to describe interactions between objects through the Web, a potential implementation is the WoT ontology\footnote{\url{http://iot.linkeddata.es/def/wot/index-en.html}}. At the current date of writing, WoT ontology is not aligned with W3C SSN ontologies.
A healthcare scenario has been designed "Remote health monitoring system"\footnote{\url{http://w3c.github.io/wot/wot-ucr.html\#domain-healthcare_and_medical}} among several use cases. %his ontology aims to model the Web of Things domain according to the W3C Interest Group .
- OneM2M, an international standard for Machine-to-Machine (M2M) with the development of the [OneM2M ontology]http://www.onem2m.org/technical/developers-corner/tools/onem2m-ontologies. It extends the European \textbf{ETSI M2M} standard. At the current date of writing, OneM2M is not aligned with W3C SSN. The ``MyOntoSens ontology, based on SSN V1 is being standardized as a Technical Specification (TS) within the SmartBAN (Body Area Networks) Technical Committee of the ETSI standardization body \cite{nachabe2015unified}. This ontology is relevant to build health applications based on smart devices.
- Smart Appliances REFerence (SAREF) \footnote{\url{https://ec.europa.eu/digital-single-market/en/blog/new-standard-smart-appliances-smart-home}}, is a European standard supported by ETSI M2M and SmartM2M. It mainly covers the smart building applicative domain. The SAREF ontology has been designed re-using SSN and oneM2M \cite{saref2017ssn}.
- Schema.org is a well-known schema catalogue to structure data on Web pages to describe location, person, etc. \cite{guha2016schema}. The \textbf{IoT Schema.org} extension\footnote{\url{http://iot.schema.org/}} is planned; nothing concrete has been developed yet, but discussions are ongoing.
\item \textbf{Haystack}\footnote{\url{http://project-haystack.org/}} is a project aiming at standardizing semantic data models and web services. It employs SSN V1 ontology.
\end{itemize} It would be interesting to have methodologies enabling answering such questions: (1) What are the sensors designed within the models (e.g. Body Thermometer)?, (2) What are the logical rules (IF THEN ELSE) designed within the models (e.g., if body temperature greater than 38 Degree Celsius than fever)? What is the applicative domain within this model (e.g., healthcare) useful when the ontology covers several domains (e.g., Ambient Assisted Living combines smart homes and healthcare domains).\\
The purpose of this challenge would be to automatically extract the knowledge (e.g. the most common concepts and properties) in already designed and available Knowledge Bases (e.g., datasets and/or models) released on the Web. We will focus on KBs from standards, and/or ontology-based WoT research projects applied to numerous domains. It will demonstrates that the complementary knowledge is constantly redesigned in different communities. %to tighten the links between the IoT and WoT ontologies and knowledge bases by automatically extracting knowledge related to WoT in available KB and ontologies %connecting data from/to things with concepts and properties form these ontologies and KBs
This research challenge could be solved with knowledge extraction technologies. However, most of the existing extraction techniques are frequently applied to text from document and social networks. The main novelty of this challenge would be to apply web-based extraction techniques to models employed to structure data. Indeed, data can be considered as the new oil, what it is still neglected is the reuse of the models used to structure and/or linking data (e.g., Linked Data) to ease the knowledge extraction from data.
In this challenge, we suggest to focus on the healthcare domain with health ontologies to build domain-specific WoT applications and for challenge evaluation purpose. Ideally, the challenge proposal with designed solutions could be applied to any other applicative domains.
