Semantic discovery and reuse of business process patterns

Patterns currently play an important role in modern information systems (IS) development and their use has mainly been restricted to the design and implementation phases of the development lifecycle. Given the increasing significance of business modelling in IS development, patterns have the potential of providing a viable solution for promoting reusability of recurrent generalized models in the very early stages of development. As a statement of research-in-progress this paper focuses on business process patterns and proposes an initial methodological framework for the discovery and reuse of business process patterns within the IS development lifecycle. The framework borrows ideas from the domain engineering literature and proposes the use of semantics to drive both the discovery of patterns as well as their reuse

UK Research Information Shared Service (UKRISS) Final Report, July 2014

The reporting of research information is a complex and expensive activity for research organisations (ROs). There is little alignment between funders of the reporting requests made to institutions and requests made to individual researchers about their research outputs and outcomes. This inevitably results in duplication and increased costs across the sector, whilst limiting the potential sharing and reuse of the information. The UK Research Information Shared Service (UKRISS) project conducted a feasibility and scoping study for the reporting of research information at a national level based on CERIF (Common European Research Information Format), with the objective of increasing efficiency, productivity and quality across the sector. The aim was to define and prototype solutions which are compelling, easy to use, have a low entry barrier, and support innovative information sharing and benchmarking. CERIF has emerged as the preferred format for expressing research information across Europe. To date, CERIF has been piloted for specific applications, but not as a format for reporting requirements across all UK ROs. The final report presents the work carried out by the UKRISS project, including requirements gathering, modelling and prototyping, as well as recommendation for sustainability. UKRISS was divided into two phases. Phase 1, mapping the reporting landscape, ran from March 2012 to December 2012. Phase 2, exploring delivery of potential solutions, began in February 2013 and ended in December 2013

Information modelling for the development of sustainable construction (MINDOC)

In previous decades, controlling the environmental impact through lifecycle analysis has become a topical issue in the building sector. However, there are some problems when trying to exchange information between experts for conducting various studies like the environmental assessment of the building. There is also heterogeneity between construction product databases because they do not have the same characteristics and do not use the same basis to measure the environmental impact of each construction product. Moreover, there are still difficulties to exploit the full potential of linking BIM, SemanticWeb and databases of construction products because the idea of combining them is relatively recent. The goal of this thesis is to increase the flexibility needed to assess the building’s environmental impact in a timely manner. First, our research determines gaps in interoperability in the AEC (Architecture Engineering and Construction) domain. Then, we fill some of the shortcomings encountered in the formalization of building information and the generation of building data in Semantic Web formats. We further promote efficient use of BIM throughout the building life cycle by integrating and referencing environmental data on construction products into a BIM tool. Moreover, semantics has been improved by the enhancement of a well-known building-based ontology (namely ifcOWL for Industry Foundation Classes Web Ontology Language). Finally, we experience a case study of a small building for our methodology

Developing Circular Economy through implementing advanced technologies in Dubai

The UAE and Dubai have made several strides towards sustainability and in recent years Circular Economy started to be recognised in the region. It is crucial to understand that Circular Economy is not only connected to recycling municipal waste. Circular Economy is a strategy that intends to be implemented as a business model across all industries through technological advancements. First, a conceptual and theoretical framework is developed through data analytics to indicates what are the barriers that slows any economy form implementing Circular Economy, how can Circular Economy strategy be developed in Dubai through implementing technological advancements. Secondly, a wide range of selected Circular Economy literature reviews helped in identifying advantages, strategies and implementation plans ranging from international and regional published reports. Missing data points related to Circular Economy strategy, policy and legislation in Dubai were faced while building the research methodology framework. To strengthen the research methodology a framework was built. Starting by collecting relevant Circular Economy data points from a hackathon, conducting a survey and selecting a set of published reports. Then the dataset was cleaned and prepared for data modelling where a machine learning algorithm for unsupervised data set was created, natural language processing, python and IBM Watson Discovery. Finally processing and analysing the data results of the hackathon, survey and reports were linked with the four barriers resulting in a set of twenty-five recommended initiatives linked with Dubai Industrial Strategy 2030 aims

Performance assessment of urban precinct design: a scoping study

Executive Summary: Significant advances have been made over the past decade in the development of scientifically and industry accepted tools for the performance assessment of buildings in terms of energy, carbon, water, indoor environment quality etc. For resilient, sustainable low carbon urban development to be realised in the 21st century, however, will require several radical transitions in design performance beyond the scale of individual buildings. One of these involves the creation and application of leading edge tools (not widely available to built environment professions and practitioners) capable of being applied to an assessment of performance across all stages of development at a precinct scale (neighbourhood, community and district) in either greenfield, brownfield or greyfield settings. A core aspect here is the development of a new way of modelling precincts, referred to as Precinct Information Modelling (PIM) that provides for transparent sharing and linking of precinct object information across the development life cycle together with consistent, accurate and reliable access to reference data, including that associated with the urban context of the precinct. Neighbourhoods are the ‘building blocks’ of our cities and represent the scale at which urban design needs to make its contribution to city performance: as productive, liveable, environmentally sustainable and socially inclusive places (COAG 2009). Neighbourhood design constitutes a major area for innovation as part of an urban design protocol established by the federal government (Department of Infrastructure and Transport 2011, see Figure 1). The ability to efficiently and effectively assess urban design performance at a neighbourhood level is in its infancy. This study was undertaken by Swinburne University of Technology, University of New South Wales, CSIRO and buildingSMART Australasia on behalf of the CRC for Low Carbon Living

Data sharing and ontology use among agricultural genetics, genomics, and breeding databases and resources of the AgBioData Consortium

Over the last several decades, there has been rapid growth in the number and scope of agricultural genetics, genomics and breeding (GGB) databases and resources. The AgBioData Consortium (https://www.agbiodata.org/) currently represents 44 databases and resources covering model or crop plant and animal GGB data, ontologies, pathways, genetic variation and breeding platforms (referred to as 'databases' throughout). One of the goals of the Consortium is to facilitate FAIR (Findable, Accessible, Interoperable, and Reusable) data management and the integration of datasets which requires data sharing, along with structured vocabularies and/or ontologies. Two AgBioData working groups, focused on Data Sharing and Ontologies, conducted a survey to assess the status and future needs of the members in those areas. A total of 33 researchers responded to the survey, representing 37 databases. Results suggest that data sharing practices by AgBioData databases are in a healthy state, but it is not clear whether this is true for all metadata and data types across all databases; and that ontology use has not substantially changed since a similar survey was conducted in 2017. We recommend 1) providing training for database personnel in specific data sharing techniques, as well as in ontology use; 2) further study on what metadata is shared, and how well it is shared among databases; 3) promoting an understanding of data sharing and ontologies in the stakeholder community; 4) improving data sharing and ontologies for specific phenotypic data types and formats; and 5) lowering specific barriers to data sharing and ontology use, by identifying sustainability solutions, and the identification, promotion, or development of data standards. Combined, these improvements are likely to help AgBioData databases increase development efforts towards improved ontology use, and data sharing via programmatic means.Comment: 17 pages, 8 figure