The CitySPIN Platform: A CPSS Environment for City-Wide Infrastructures

Cyber-physical Social System (CPSS) are complex systems that span the boundaries of the cyber, physical and social spheres. They play an important role in a variety of domains ranging from industry to smart city applications. As such, these systems necessarily need to take into account, combine and make sense of heterogeneous data sources from legacy systems, from the physical layer and also the social groups that are part of/use the system. The collection, cleansing and integration of these data sources represents a major effort not only during the operation of the system, but also during its engineering and design. Indeed, while ongoing efforts are concerned primarily with the operation of such systems, limited focus has been put on supporting the engineering phase of CPSS. To address this shortcoming, within the CitySPIN project we aim to create a platform that supports stakeholders involved in the design of these systems especially in terms of support for data management. To that end, we develop methods and techniques based on Semantic Web and Linked Data technologies for the acquisition and integration of heterogeneous data from disparate structured, semi-structured and unstructured sources, including open data and social data. In this paper we present the overall system architecturewith a core focus on data acquisition and integration.We demon-strate our approach through a prototypical implementation of an adaptive planning use case for public transportation scheduling

I have two homes: an investigation into the transnational identity of Kenyan migrants in the United Kingdom (UK) and how this relates to their wellbeing.

Background:- The incorporation of migrants in the host country is an on-going debate in many countries. While assimilation theories were prevalent in earlier times before the era of what is commonly referred to as globalization as explanations of migrants’ integration, ethnic pluralist theories including multiculturalism are currently being employed. These theories, however present challenges for current migrants’ incorporation in the host country because they do not regard migrants’ transnationalism. Transnational identity and how it relates to migrants’ wellbeing in the host country remain under-researched and it is the concern of this study.- Aims of the study:- The aims of this study were to: ¨ Investigate the impact of transnational identity on the subjective wellbeing of Kenyan migrants in the UK. This is achieved through a critical examination of the relationship between the support they provide to their chronically ill relatives in Kenya and how this impacts on their wellbeing. ¨ Identify indicators of subjective wellbeing related to transnational identity- Methodology:- A mixed method approach was used and data was collected through two stages. The first stage used a survey, carried out to map out the study by establishing the occurrence of support provision among Kenyans. Survey questionnaires were used for this stage. The second stage employed the use of semi-structured interviews and participant observation as data collection instruments.- Participants:- During the survey, 96 participants (n=96) participated. The semi-structured interviews were conducted with 20 participants. Three community events were observed, two of them were ‘harambees’, which are fundraising events organised to raise money for an ill relative in Kenya and one was a ‘ngwataniro’, which is a prayer meeting organized to pray for an ill relative in Kenya.- Results and data analysis:- The survey data was analyzed using computer software, Statistical Package for Social Sciences (SPSS) and a report was compiled. Colaizzi’s framework was used for the initial analysis of the semi-structured interviews’ data and participant observation data. The data was sorted out and major categories and sub-categories were identified using computer software(NUD*IST), and these were then examined further. The major themes were; transnational identity; belonging; giving; and wellbeing. The results highlighted that migrants construct, nurture and maintain transnational identity thorough provision of support to their chronically ill relatives in Kenya. This enables them to maintain links with their friends and relatives, further enhancing their wellbeing in their country of settlement, the UK.- Discussion:- Transnational identity which is practiced by migrants and reflected among other things through maintenance of links with their families and friends in their home country is linked to migrants’ wellbeing in the host country.- Conclusion:- The results from this study have generated an understanding of how migrants construct, nurture and maintain transnational identity, which is explored in this study through provision of support to their chronically ill relatives in Kenya. The evidence in this research that transnational identity leads to enhanced wellbeing of migrants is a good base for policy makers to consider including transnational perspectives in social integration policies. Recommended research areas should allow additional investigation in transnational identity and how it impacts on health among migrants

Processamento analítico espacial e exploratório integrando dados estruturados e semiestruturados.

Tecnologias de Business Intelligence (BI) têm sido utilizadas com sucesso para fins de análise de dados. Tradicionalmente, essa análise é realizada em um contexto restrito e bem controlado, onde as fontes de dados são estruturadas, periodicamente carregadas, estáticas e totalmente materializadas. Atualmente, há uma diversidade de dados nos mais diversos formatos, a exemplo de RDF (Resource Description Framework), um formato semiestruturado, semanticamente rico e externo à infraestrutura de BI. Embora tal formato seja enriquecido semanticamente, e muitas vezes possua um componente espacial, realizar a análise é um desafio. Nessa perspectiva, uma nova categoria de ferramentas analíticas vem surgindo. As ferramentas exploratórias (Exploratory OLAP), como são conhecidas, se caracterizam pela descoberta, aquisição e integração de dados externos em ambientes comuns de análise. Do nosso conhecimento, até a presente data, existem apenas duas ferramentas exploratórias propostas na literatura e elas apresentam duas grandes limitações: exploram apenas fontes de dados estruturadas; e não há exploração do componente espacial dos dados integrados. São ferramentas exploratórias OLAP, e não ferramentas exploratórias SOLAP. Baseando-se nessas ferramentas, este trabalho propõe uma abordagem exploratória SOLAP que integra dados semiestruturados espaciais semânticos com fontes de dados estruturados espaciais tradicionais. Um sistema, denominado ExpSOLAP, que dá suporte a consultas SOLAP on-line sob as duas fontes de dados foi desenvolvido. Por fim, o sistema ExpSOLAP é avaliado através de um exemplo prático, no contexto da base de dados obtida no Linked Movie Data Base, utilizando RDF e banco de dados relacional. Foram formuladas consultas que validaram a análise convencional e espacial na exploração de ambas fontes de dados.Business Intelligence (BI) technologies have been successfully applied for data analysis purposes. Traditionally, such analysis is performed in well-controlled and restricted context, where data sources are structured, periodically loaded, static and fully materialized. Nowadays, there is a plenty of data in different formats such as the Resource Description Framework (RDF), a semi-structured and semantically rich format external to the BI infrastructure. Although such data formats are enriched by semantics and contains a spatial data component, performing data analysis is challenging. As a result, the Exploratory OLAP field has emerged for discovery, acquisition, integration and query such data, aiming at performing a complete and effective analysis on both internal and external data. To the best of our knowledge, there are only two exploratory tools proposed in the literature and they have two major limitations due to only structured data sources can be explored and there is no exploration of the spatial component of the integrated data. While they are exploratory OLAP tools, they are not exploratory SOLAP tools. Based on these tools, this work proposes an Exploratory SOLAP approach that integrates semantic spatial semi-structured data with traditional spatial structured data sources. A system named ExpSOLAP, which supports online SOLAP queries on both data sources, was developed. Finally, a case study was carried out in order to evaluate the ExpSOLAP system based on a dataset originating from the Linked Movie Data Base and using RDF and relational datasets. The formulated queries enabled to validate the conventional and spatial analysis from both data sources.CNP

Improving root cause analysis through the integration of PLM systems with cross supply chain maintenance data

The purpose of this paper is to demonstrate a system architecture for integrating Product Lifecycle Management (PLM) systems with cross supply chain maintenance information to support root-cause analysis. By integrating product-data from PLM systems with warranty claims, vehicle diagnostics and technical publications, engineers were able to improve the root-cause analysis and close the information gaps. Data collection was achieved via in-depth semi-structured interviews and workshops with experts from the automotive sector. Unified Modelling Language (UML) diagrams were used to design the system architecture proposed. A user scenario is also presented to demonstrate the functionality of the system

Designing a resource-efficient data structure for mobile data systems

Designing data structures for use in mobile devices requires attention on optimising data volumes with associated benefits for data transmission, storage space and battery use. For semi-structured data, tree summarisation techniques can be used to reduce the volume of structured elements while dictionary compression can efficiently deal with value-based predicates. This project seeks to investigate and evaluate an integration of the two approaches. The key strength of this technique is that both structural and value predicates could be resolved within one graph while further allowing for compression of the resulting data structure. As the current trend is towards the requirement for working with larger semi-structured data sets this work would allow for the utilisation of much larger data sets whilst reducing requirements on bandwidth and minimising the memory necessary both for the storage and querying of the data

A Survey of Volunteered Open Geo-Knowledge Bases in the Semantic Web

Over the past decade, rapid advances in web technologies, coupled with innovative models of spatial data collection and consumption, have generated a robust growth in geo-referenced information, resulting in spatial information overload. Increasing 'geographic intelligence' in traditional text-based information retrieval has become a prominent approach to respond to this issue and to fulfill users' spatial information needs. Numerous efforts in the Semantic Geospatial Web, Volunteered Geographic Information (VGI), and the Linking Open Data initiative have converged in a constellation of open knowledge bases, freely available online. In this article, we survey these open knowledge bases, focusing on their geospatial dimension. Particular attention is devoted to the crucial issue of the quality of geo-knowledge bases, as well as of crowdsourced data. A new knowledge base, the OpenStreetMap Semantic Network, is outlined as our contribution to this area. Research directions in information integration and Geographic Information Retrieval (GIR) are then reviewed, with a critical discussion of their current limitations and future prospects