Edward Curry

Linking building data in the cloud: Integrating cross-domain building data using linked data

Within the operational phase buildings are now producing more data than ever before, from energy usage, utility information, occupancy patterns, weather data, etc. In order to manage a building holistically it is important to use knowledge from across these information sources. However, many barriers exist to their interoperability and there is little interaction between these islands of information. As part of moving building data to the cloud there is a critical need to reflect on the design of cloud-based data services and how they are designed from an interoperability perspective. If new cloud data services are designed in the same manner as traditional building management systems they will suffer from the data interoperability problems. Linked data technology leverages the existing open protocols and W3C standards of the Web architecture for sharing structured data on the web. In this paper we propose the use of linked data as an enabling technology for cloud-based building data services. The objective of linking building data in the cloud is to create an integrated well-connected graph of relevant information for managing a building. This paper describes the fundamentals of the approach and demonstrates the concept within a Small Medium sized Enterprise (SME) with an owner-occupied office building.

XBRL and open data for global financial ecosystems: A linked data approach

Information professionals performing business activity related investigative analysis must routinely associate data from a diverse range of Web based general-interest business and financial information sources. XBRL has become an integral part of the financial data landscape. At the same time, Open Data initiatives have contributed relevant financial, economic, and business data to the pool of publicly available information on the Web but the use of XBRL in combination with Open Data remains at an early state of realisation. In this paper we argue that Linked Data technology, created for Web scale information integration, can accommodate XBRL data and make it easier to combine it with open datasets. This can provide the foundations for a global data ecosystem of interlinked and interoperable financial and business information with the potential to leverage XBRL beyond its current regulatory and disclosure role. We outline the uses of Linked Data technologies to facilitate XBRL consumption in conjunction with non-XBRL Open Data, report on current activities and highlight remaining challenges in terms of information consolidation faced by both XBRL and Web technologies.

Querying linked data using semantic relatedness: a vocabulary independent approach

Linked Data brings the promise of incorporating a new dimension to the Web where the availability of Web-scale data can determine a paradigmatic transformation of the Web and its applications. However, together with its opportunities, Linked Data brings inherent challenges in the way users and applications consume the available data. Users consuming Linked Data on the Web, or on corporate intranets, should be able to search and query data spread over potentially a large number of heterogeneous, complex and distributed datasets. Ideally, a query mechanism for Linked Data should abstract users from the representation of data. This work focuses on the investigation of a vocabulary independent natural language query mechanism for Linked Data, using an approach based on the combination of entity search, a Wikipediabased semantic relatedness measure and spreading activation. The combination of these three elements in a query mechanism for Linked Data is a new contribution in the space. Wikipedia-based relatedness measures address existing limitations of existing works which are based on similarity measures/term expansion based on WordNet. Experimental results using the query mechanism to answer 50 natural language queries over DBPedia achieved a mean reciprocal rank of 61.4%, an average precision of 48.7% and average recall of 57.2%, answering 70% of the queries.

A Capability Maturity Framework for Sustainable Information and Communication Technology

Researchers estimate that information and communication technology (ICT) is responsible for at least 2 percent of global greenhouse gas (GHG) emissions. Furthermore, in any individual business, ICT is responsible for a much higher percentage of that businesss GHG footprint. Yet researchers also estimate that ICT can provide business solutions to reduce its GHG footprint fivefold. However, because the field is new and evolving, few guidelines and best practices are available. To address this issue, a consortium of leading organizations from industry, the nonprofit sector, and academia has developed and tested a framework for systematically assessing and improving SICT capabilities. The Innovation Value Institute (IVI; http://ivi.nuim.ie) consortium used an open-innovation model of collaboration, engaging academia and industry in scholarly work to create the SICT-Capability Maturity Framework (SICT-CMF), which is discussed in this paper.

Approximate semantic matching of heterogeneous events

Event-based systems have loose coupling within space, time and synchronization, providing a scalable infrastructure for information exchange and distributed workflows. However, event-based systems are tightly coupled, via event subscriptions and patterns, to the semantics of the underlying event schema and values. The high degree of semantic heterogeneity of events in large and open deployments such as smart cities and the sensor web makes it difficult to develop and maintain event-based systems. In order to address semantic coupling within event-based systems, we propose vocabulary free subscriptions together with the use of approximate semantic matching of events. This paper examines the requirement of event semantic decoupling and discusses approximate semantic event matching and the consequences it implies for event processing systems. We introduce a semantic event matcher and evaluate the suitability of an approximate hybrid matcher based on both thesauri-based and distributional semantics-based similarity and relatedness measures. The matcher is evaluated over a structured representation of Wikipedia and Freebase events. Initial evaluations show that the approach matches events with a maximal combined precision-recall F1 score of 75.89% on average in all experiments with a subscription set of 7 subscriptions. The evaluation shows how a hybrid approach to semantic event matching outperforms a single similarity measure approach.

Approximate Semantic Matching of Events for the Internet of Things

Event processing follows a decoupled model of interaction in space, time, and synchronization. However, another dimension of semantic coupling also exists and poses a challenge to the scalability of event processing systems in highly semantically heterogeneous and dynamic environments such as the Internet of Things (IoT). Current state-of-the-art approaches of content-based and concept-based event systems require a significant agreement between event producers and consumers on event schema or an external conceptual model of event semantics. Thus, they do not address the semantic coupling issue. This article proposes an approach where participants only agree on a distributional statistical model of semantics represented in a corpus of text to derive semantic similarity and relatedness. It also proposes an approximate model for relaxing the semantic coupling dimension via an approximation-enabled rule language and an approximate event matcher. The model is formalized as an ensemble of semantic and top-k matchers along with a probability model for uncertainty management. The model has been empirically validated on large sets of events and subscriptions synthesized from real-world smart city and energy management systems. Experiments show that the proposed model achieves more than 95% F1Score of effectiveness and thousands of events/sec of throughput for medium degrees of approximation while not requiring users to have complete prior knowledge of event semantics. In semantically loosely-coupled environments, one approximate subscription can compensate for hundreds of exact subscriptions to cover all possibilities in environments which require complete prior knowledge of event semantics. Results indicate that approximate semantic event processing could play a promising role in the IoT middleware layer.

Flexible Self-Management Using the Model-View-Controller Pattern

A self-management infrastructure requires a self-representation to model system functionality concerns. The model-view-controller design pattern can improve concern separation in a self-representation. Future computing initiatives such as ubiquitous and pervasive computing, large-scale distribution, and on-demand computing will foster unpredictable and complex environments with challenging demands. Next-generation systems will require flexible system infrastructures that can adapt to both dynamic changes in operational requirements and environmental conditions, while providing predictable behavior in areas such as throughput, scalability, dependability, and security. Successful projects, once deployed, will require skilled administration personnel to install, configure, maintain, and provide 24/7 support. Message-oriented middleware is one of the foundations of distributed systems.

The Role of Community-Driven Data Curation for Enterprises

With increased utilization of data within their operational and strategic processes, enterprises need to ensure data quality and accuracy. Data curation is a process that can ensure the quality of data and its fitness for use. Traditional approaches to curation are struggling with increased data volumes, and near real-time demands for curated data. In response, curation teams have turned to community crowd-sourcing and semi-automatedmetadata tools for assistance. This chapter provides an overview of data curation, discusses the business motivations for curating data and investigates the role of community-based data curation, focusing on internal communities and pre-competitive data collaborations. The chapter is supported by case studies from Wikipedia, The New York Times, Thomson Reuters, Protein Data Bank and ChemSpider upon which best practices for both social and technical aspects of community-driven data curation are described.

System of systems information interoperability using a linked dataspace

System of Systems pose significant technical challenges in terms of information interoperability that require overcoming conceptual barriers (both syntax and semantic) and technological barriers. This paper presents an approach to System of Systems information interoperability based on the Dataspace data management abstraction and the Linked Data approach to sharing information on the web. The paper describes the fundamentals of the approach and demonstrates the concept with a System of Systems for enterprise energy management.

W3P: Building an OPM based provenance model for the Web

The Web is evolving into a complex information space where the unprecedented volume of documents and data will offer to the information consumer a level of information integration and aggregation that has up until now not been possible. Indiscriminate addition of information can, however, come with inherent problems such as the provision of poor quality or fraudulent information. Provenance represents the cornerstone element which will enable information consumers to assess information quality, which will play a fundamental role in the continued evolution of the Web. This paper investigates the characteristics and requirements of provenance on the Web, describing how the Open Provenance Model (OPM) can be used as a foundation for the creation of W3P, a provenance model and ontology designed to meet the core requirements for the Web.