Tope Omitola

Put in your postcode, out comes the data: a case study

Article describes the UK Open Government Data project which the two authors have been leading and the planned launch of data.gov.uk a single point of access for all public non-personal government datasets. It outlines the benefits that will flow from more accessible and open data. The article first appeared in The Times 18th Nov 2009 http://www.thetimes.co.uk/tto/law/columnists/article2049543.ece

Capturing Interactive Data Transformation Operations Using Provenance Workflows

The ready availability of data is leading to the increased opportunity of their re-use for new applications and for analyses. Most of these data are not necessarily in the format users want, are usually heterogeneous, and highly dynamic, and this necessitates data transformation efforts to re-purpose them. Interactive data transformation (IDT) tools are becoming easily available to lower these barriers to data transformation efforts. This paper describes a principled way to capture data lineage of interactive data transformation processes. We provide a formal model of IDT, its mapping to a provenance representation, and its implementation and validation on Google Refine. Provision of the data transformation process sequences allows assessment of data quality and ensures portability between IDT and other data transformation platforms. The proposed model showed a high level of coverage against a set of requirements used for evaluating systems that provide provenance management solutions.

Leveraging social network analysis with topic models and the Semantic Web extended

Research in the Semantic Web, especially in modeling virtual communities, has provided models useful to represent the richness of these social network interactions. The SIOC Semantically-Interlinked Online Communities vocabulary provides concepts and properties that can be used to describe information from online communities e.g., message boards, wikis, weblogs, etc.. However, the SIOC ontology does not consider social aspects nor the higher order semantics hidden in linkages between community members. This paper describes SIOC-SNA-DM, an extension of the SIOC vocabulary. SIOC-SNA-DMs model is tri-partite, consisting of People, Policies, and Purposes which are social aspects observable in most social communities. A challenge to using our model is how to populate these aspects, since higher order semantics from interactions need to be extracted. Thus, we explain how this population is done with advanced text mining using a latent semantic technique over a large virtual community called Plexilandia.cl with more than 2500 musicians working on the site.Our previous work, in this area, has shown how including these social aspects help to outperform results generated by state-of-the-art techniques. One of the novelties of this present work is the introduction and the elucidation of SIOC-SNA-DM, and how to populate the ontology in order to support the social aspects needed to enhance results of Social Network Mining techniques.

Towards Mapping the Security Challenges of the Internet of Things (IoT) Supply Chain

Abstract The flow complexity in today’s IoT supply chain is enormous. To produce an item in a global network of suppliers requires a delicate dance of people, assets, systems, information, companies, and even governments. The opportunities for security vulnerabilities abound. In this paper, we describe the security challenges facing an IoT supply chain. We first start by describing what an IoT endpoint is, their various types together with their concomitant security challenges. An IoT endpoint is an output of an IoT supply chain, and the enumeration of its security challenges is then used to describe what IoT attack surfaces are, together with the threats and vulnerabilities facing a typical IoT supply chain. We use the iPhone/Apple supply chain as an exemplar, creating a map, and using that map to depict likely vulnerabilities and attacks. We conclude by discussing the mitigations against potential vulnerabilities in such a supply chain.