A visual exploration workflow as enabler for the exploitation of Linked Open Data

Abstract. Semantically annotating and interlinking Open Data results in Linked Open Data which concisely and unambiguously describes a knowledge domain. However, the uptake of the Linked Data depends on its usefulness to non-Semantic Web experts. Failing to support data consumers to understand the added-value of Linked Data and possible exploitation opportunities could inhibit its diffusion. In this paper, we propose an interactive visual workflow for discovering and ex-ploring Linked Open Data. We implemented the workflow considering academic library metadata and carried out a qualitative evaluation. We assessed the work-flow’s potential impact on data consumers which bridges the offer: published Linked Open Data; and the demand as requests for: (i) higher quality data; and (ii) more applications that re-use data. More than 70 % of the 34 test users agreed that the workflow fulfills its goal: it facilitates non-Semantic Web experts to un-derstand the potential of Linked Open Data.

Adding Value to Statistics in the Data Revolution Age

As many statistical offices in accordance with the European Statistical System commitment to Vision 2020, since the second half of 2014 Istat has implemented its internal standardisation and industrialisation process within the framework of a common Business Architecture. Istat modernisation programme aims at building services and infrastructures within a plug-and-play framework to foster innovation, promote reuse and move towards full integration and interoperability of statistical process, consistent with a service-oriented architecture. This is expected to lead to higher effectiveness and productivity by improving the quality of statistical information and reducing the response burden. This paper addresses the strategy adopted by Istat which is focused on exploiting administrative data and new data sources in order to achieve its key goals enhancing value to users. The strategy is based on some priorities that consider services centred on users and stakeholders as well as Linked Open Data, to allow Machine-to-Machine data and metadata integration through definition of common statistical ontologies and semantics

Co-evolution of RDF Datasets

Linking Data initiatives have fostered the publication of large number of RDF datasets in the Linked Open Data (LOD) cloud, as well as the development of query processing infrastructures to access these data in a federated fashion. However, different experimental studies have shown that availability of LOD datasets cannot be always ensured, being RDF data replication required for envisioning reliable federated query frameworks. Albeit enhancing data availability, RDF data replication requires synchronization and conflict resolution when replicas and source datasets are allowed to change data over time, i.e., co-evolution management needs to be provided to ensure consistency. In this paper, we tackle the problem of RDF data co-evolution and devise an approach for conflict resolution during co-evolution of RDF datasets. Our proposed approach is property-oriented and allows for exploiting semantics about RDF properties during co-evolution management. The quality of our approach is empirically evaluated in different scenarios on the DBpedia-live dataset. Experimental results suggest that proposed proposed techniques have a positive impact on the quality of data in source datasets and replicas.Comment: 18 pages, 4 figures, Accepted in ICWE, 201

Consuming Linked Closed Data

The growth of the Linked Data corpus will eventually pre- vent all but the most determined of consumers from including every Linked Dataset in a single undertaking. In addition, we anticipate that the need for effective revenue models for Linked Data publishing will spur the rise of Linked Closed Data, where access to datasets is restricted. We argue that these impeding changes necessitate an overhaul of our current practices for consuming Linked Data. To this end, we propose a model for consuming Linked Data, built on the notion of continuous Information Quality assessment, which brings together a range of existing research and highlights a number of avenues for future work

Sustainable Design and Building Information Modelling: Case Study of Energy Plus House, Hieron's Wood, Derbyshire UK

In this paper the method for sustainable design analysis (SDA) integration with building information modelling (BIM) is explored, through the prism of a complex case study based research. BIM model federation and integration challenges are reported, including issues with combining geometry and managing attribute data. The research defines SDA as rapid and quantifiable analysis of multitude of sustainable alternatives and ‘what if’ questions posed by a design team during the early stages of the project, when the benefits of correct decisions can significantly exceed the actual investment required. The SDA concept and BIM integration findings are explained from conceptualisation to calculation stage, emphasising the importance of an iterative over a linear approach. The research approach adopted has led to more informed sustainable solutions at earlier stages of project development, with a generally lower level of development (LOD) and computational/modelling effort required