Network
Latest external collaboration on country level. Dive into details by clicking on the dots.
Publication
Featured researches published by Martin Stephenson.
international semantic web conference | 2012
Vanessa Lopez; Spyros Kotoulas; Marco Luca Sbodio; Martin Stephenson; Aris Gkoulalas-Divanis; Pol Mac Aonghusa
In this paper, we present QuerioCity, a platform to catalog, index and query highly heterogenous information coming from complex systems, such as cities. A series of challenges are identified: namely, the heterogeneity of the domain and the lack of a common model, the volume of information and the number of data sets, the requirement for a low entry threshold to the system, the diversity of the input data, in terms of format, syntax and update frequency (streams vs static data), and the sensitivity of the information. We propose an approach for incremental and continuous integration of static and streaming data, based on Semantic Web technologies. The proposed system is unique in the literature in terms of handling of multiple integrations of available data sets in combination with flexible provenance tracking, privacy protection and continuous integration of streams. We report on lessons learnt from building the first prototype for Dublin.
Journal of Web Semantics | 2014
Spyros Kotoulas; Vanessa Lopez; Raymond Lloyd; Marco Luca Sbodio; Freddy Lécué; Martin Stephenson; Elizabeth M. Daly; Veli Bicer; Aris Gkoulalas-Divanis; Giusy Di Lorenzo; Anika Schumann; Pol Mac Aonghusa
Abstract We present SPUD , a semantic environment for cataloging, exploring, integrating, understanding, processing and transforming urban information. A series of challenges are identified: namely, the heterogeneity of the domain and the impracticality of a common model, the volume of information and the number of data sets, the requirement for a low entry threshold to the system, the diversity of the input data, in terms of format, syntax and update frequency (streams vs static data), the complex data dependencies and the sensitivity of the information. We propose an approach for the incremental and continuous integration of static and streaming data, based on Semantic Web technologies and apply our technology to a traffic diagnosis scenario. We demonstrate our approach through a system operating on real data in Dublin and we show that semantic technologies can be used to obtain business results in an environment with hundreds of heterogeneous datasets coming from distributed data sources and spanning multiple domains.
pervasive computing and communications | 2012
Martin Stephenson; Giusy Di Lorenzo; Pol Mac Aonghusa
In recent years, many agencies and government authorities have been moving toward opening up their datasets, allowing external parties to create applications that can mash up this data. As the amount and the variety of data is increasing, it is important to create good metadata (descriptions, geographical boundaries, limitations, etc.) in order to allow individuals, who may not be domain experts, to easily search and consume data. In this paper we propose the Open Innovation Portal (OIP), a collaborative platform that allows Cities to annotate, publish and provide access to urban data from multiple sources in an intuitive, consistent and scalable way through open standards. In collaboration with Dublin City authorities and National University of Ireland Maynooth, we implemented a first prototype for Dublin. In the demo, we show how the collaborative metadata creation process works, from the raw data to the publishable information, and how the collaborative platform can be implemented both for a mobile-phone and web application.
international semantic web conference | 2015
Vanessa Lopez; Martin Stephenson; Spyros Kotoulas; Pierpaolo Tommasi
DALI is a practical system that exploits Linked Data to provide federated entity search and spatial exploration across hundreds of information sources containing Open and Enterprise data pertaining to cities, which are stored in tabular files or in their original enterprise systems. Our system is able to lift data into a meaningful linked structure with explicit semantics, and support novel contextual search and retrieval tasks by identifying related entities across models and data sources. We evaluate in two pilot scenarios. In the first, data-engineers bring together public and enterprise datasets about public safety. In the second, knowledge-engineers and domain-experts, build a view of health and social care providers for vulnerable populations. We show that our approach can re-use data assets and provides better results than pure text-based approaches in finding relevant information, as well as satisfying specific information needs.
intelligent user interfaces | 2014
Spyros Kotoulas; Vanessa Lopez; Marco Luca Sbodio; Pierpaolo Tommasi; Martin Stephenson; Pol Mac Aonghusa
We present an approach to access and consolidate complex information spanning multiple specialist domains and make it available to non-experts. We are using a combination of business rules and contextual exploration to reduce interface complexity and improve consumability. We present a use case and a prototype on top of a real-world enterprise solution for coordinating Social care and Health care. We evaluate our system through a user study. Our results indicate that our approach reduces the time required to obtain business results compared to a baseline graph exploration approach.
acm conference on hypertext | 2014
Vanessa Lopz Garcia; Martin Stephenson; Spyros Kotoulas; Pierpaolo Tommasi
More and more urban data is published every day, and consequently, consumers want to take advantage of this body of knowledge. Unfortunately, metadata and schema information around this content is sparse. To effectively fulfill user information needs, systems must be able to capture user intent and context in order to evolve beyond current search and exploration techniques. A Linked Data approach is uniquely positioned to surface information and provide interoperability across a diversity of information sources, from consumer data residing in the original enterprise systems, to relevant open city data in tabular form. We present a prototype for contextual knowledge mining that enables federated access and querying of entities across hundreds of enterprise and open datasets pertaining to cities. The proposed system is able to (1) lift raw tabular data into a connected and meaningful structure, contextualized within the Web of Data, and (2) support novel search and exploration tasks, by identifying closely related entities across datasets and models. Our user experiments and prototype show how semantics, used to consolidate city information and reuse assets from the Web of Data, improve dataset search and provide users effective means to explore related entities and content to fit their information needs.
metadata and semantics research | 2015
Nuno Lopes; Martin Stephenson; Vanessa Lopez; Pierpaolo Tommasi; Pol Mac Aonghusa
This paper introduces an extension of DALI, a framework for data integration and visualisation. When integrating new data, DALI automatically tries to recognise the schema and contents of the file, semantically lift them, and annotate them with existing ontologies. The extension presented in this paper allows users to import data from external data portals, namely portals using CKAN or Socrata, based on the results of a search query or by selecting individual datasets. Furthermore, we perform a semantic expansion of the search terms provided by the user in order to identify datasets that might still be relevant while not containing the exact search terms.
acm conference on hypertext | 2014
Spyros Kotoulas; Vanessa Lopez; Marco Luca Sbodio; Martin Stephenson; Pierpaolo Tommasi; Pol Mac Aonghusa
The success of a society is often judged by its ability to support the most vulnerable. Supporting the most vulnerable individuals is extremely challenging from an information needs perspective, since it requires data from numerous domains and systems, including Social Care, Healthcare, Public Safety and Juridical systems. Information sharing on this scale gives rise to scientific and technical challenges with regard to data representation, access, integration and retrieval granularity. This is a practice-oriented paper presenting a Linked Data-based approach that is uniquely positioned to access and surface information across domains and data sources using a combination of vulnerability indexes and contextual exploration. We apply this approach on a set of enterprise systems from IBM to develop an information sharing architecture and prototype for Care Coordination with a focus on Social Care and Healthcare. We report on expert feedback and user studies that indicate that our approach indeed reduces the time required to gain some business insight while maintaining the flexibility of a Linked Data-based integration approach.
international semantic web conference | 2013
Spyros Kotoulas; Vanessa Lopez; Martin Stephenson; Pierpaolo Tommasi; Weijia Shen; Gang Hu; Marco Luca Sbodio; Veli Bicer; Anastasios Kementsietsidis; M. Mustafa Rafique; Jason B. Ellis; Thomas Erickson; Kavitha Srinivas; Kevin P. McAuliffe; Guo Tong Xie; Pol Mac Aonghusa
medical informatics europe | 2014
Spyros Kotoulas; Walter Sedlazek; Vanessa Lopez; Marco Luca Sbodio; Martin Stephenson; Pierpaolo Tommasi; Pol Mac Aonghusa