A JBI Information Object Engineering Environment Utilizing Metadata Fragments for Refining Searches on Semantically-Related Object Types

The Joint Battlespace Infosphere (JBI) architecture defines the Information Object (IO) as its basic unit of data. This research proposes an IO engineering methodology that will introduce componentized IO type development. This enhancement will improve the ability of JBI users to create and store IO type schemas, and query and subscribe to information objects, which may be semantically related by their inclusion of common metadata elements. Several parallel efforts are being explored to enable efficient storage and retrieval of IOs. Utilizing relational database access methods, applying a component-based IO type development concept, and exploiting XML inclusion mechanisms, this research improves the means by which a JBI can deliver related IO types to subscribers from a single query or subscription. The proposal of this new IO type architecture also integrates IO type versioning, type coercion, and namespacing standards into the methodology. The combined proposed framework provides a better means by which a JBI can deliver the right information to the right users at the right time

Discovery Mechanisms for the Sensor Web

This paper addresses the discovery of sensors within the OGC Sensor Web Enablement framework. Whereas services like the OGC Web Map Service or Web Coverage Service are already well supported through catalogue services, the field of sensor networks and the according discovery mechanisms is still a challenge. The focus within this article will be on the use of existing OGC Sensor Web components for realizing a discovery solution. After discussing the requirements for a Sensor Web discovery mechanism, an approach will be presented that was developed within the EU funded project “OSIRIS”. This solution offers mechanisms to search for sensors, exploit basic semantic relationships, harvest sensor metadata and integrate sensor discovery into already existing catalogues

Development of a spatial data infrastructure for precision agriculture applications

Precision agriculture (PA) is the technical answer to tackling heterogeneous conditions in a field. It works through site specific operations on a small scale and is driven by data. The objective is an optimized agricultural field application that is adaptable to local needs. The needs differ within a task by spatial conditions. A field, as a homogenous-planted unit, exceeds by its size the scale units of different landscape ecological properties, like soil type, slope, moisture content, solar radiation etc. Various PA-sensors sample data of the heterogeneous conditions in a field. PA-software and Farm Management Information Systems (FMIS) transfer the data into status information or application instructions, which are optimized for the local conditions. The starting point of the research was the determination that the process of PA was only being used in individual environments without exchange between different users and to other domains. Data have been sampled regarding specific operations, but the model of PA suffers from these closed data streams and software products. Initial sensors, data processing and controlled implementations were constructed and sold as monolithic application. An exchange of hard- or software as well as of data was not planned. The design was focused on functionality in a fixed surrounding and conceived as being a unit. This has been identified as a disadvantage for ongoing developments and the creation of added value. Influences from the outside that may be innovative or even inspired cannot be considered. To make this possible, the underlying infrastructure must be flexible and optimized for the exchange of data. This thesis explores the necessary data handling, in terms of integrating knowledge of other domains with a focus on the geo-spatial data processing. As PA is largely dependent on geographical data, this work develops spatial data infrastructure (SDI) components and is based on the methods and tools of geo-informatics. An SDI provides concepts for the organization of geospatial components. It consists of spatial- and metadata in geospatial workflows. The SDI in the center of these workflows is implemented by technologies, policies, arrangements, and interfaces to make the data accessible for various users. Data exchange is the major aim of the concept. As previously stated, data exchange is necessary for PA operations, and it can benefit from defined components of an SDI. Furthermore, PA-processes gain access to interchange with other domains. The import of additional, external data is a benefit. Simultaneously, an export interface for agricultural data offers new possibilities. Coordinated communication ensures understanding for each participant. From the technological point of view, standardized interfaces are best practice. This work demonstrates the benefit of a standardized data exchange for PA, by using the standards of the Open Geospatial Consortium (OGC). The OGC develops and publishes a wide range of relevant standards, which are widely adopted in geospatially enabled software. They are practically proven in other domains and were implemented partially in FMIS in the recent years. Depending on their focus, they could support software solutions by incorporating additional information for humans or machines into additional logics and algorithms. This work demonstrates the benefits of standardized data exchange for PA, especially by the standards of the OGC. The process of research follows five objectives: (i) to increase the usability of PA-tools in order to open the technology for a wider group of users, (ii) to include external data and services seamlessly through standardized interfaces to PA-applications, (iii) to support exchange with other domains concerning data and technology, (iv) to create a modern PA-software architecture, which allows new players and known brands to support processes in PA and to develop new business segments, (v) to use IT-technologies as a driver for agriculture and to contribute to the digitalization of agriculture.Precision agriculture (PA) ist die technische Antwort, um heterogenen Bedingungen in einem Feld zu begegnen. Es arbeitet mit teilflächenspezifischen Handlungen kleinräumig und ist durch Daten angetrieben. Das Ziel ist die optimierte landwirtschaftliche Feldanwendung, welche an die lokalen Gegebenheiten angepasst wird. Die Bedürfnisse unterscheiden sich innerhalb einer Anwendung in den räumlichen Bedingungen. Ein Feld, als gleichmäßig bepflanzte Einheit, überschreitet in seiner Größe die räumlichen Einheiten verschiedener landschaftsökologischer Größen, wie den Bodentyp, die Hangneigung, den Feuchtigkeitsgehalt, die Sonneneinstrahlung etc. Unterschiedliche Sensoren sammeln Daten zu den heterogenen Bedingungen im Feld. PA-Software und farm management information systems (FMIS) überführen die Daten in Statusinformationen oder Bearbeitungsanweisungen, die für die Bedingungen am Ort optimiert sind. Ausgangspunkt dieser Dissertation war die Feststellung, dass der Prozess innerhalb von PA sich nur in einer individuellen Umgebung abspielte, ohne dass es einen Austausch zwischen verschiedenen Nutzern oder anderen Domänen gab. Daten wurden gezielt für Anwendungen gesammelt, aber das Modell von PA leidet unter diesen geschlossenen Datenströmen und Softwareprodukten. Ursprünglich wurden Sensoren, die Datenverarbeitung und die Steuerung von Anbaugeräten konstruiert und als monolithische Anwendung verkauft. Ein Austausch von Hard- und Software war ebenso nicht vorgesehen wie der von Daten. Das Design war auf Funktionen in einer festen Umgebung ausgerichtet und als eine Einheit konzipiert. Dieses zeigte sich als Nachteil für weitere Entwicklungen und bei der Erzeugung von Mehrwerten. Äußere innovative oder inspirierende Einflüsse können nicht berücksichtigt werden. Um dieses zu ermöglichen muss die darunterliegende Infrastruktur flexibel und auf einen Austausch von Daten optimiert sein. Diese Dissertation erkundet die notwendige Datenverarbeitung im Sinne der Integration von Wissen aus anderen Bereichen mit dem Fokus auf der Verarbeitung von Geodaten. Da PA sehr abhängig von geographischen Daten ist, werden in dieser Arbeit die Bausteine einer Geodateninfrastruktur (GDI) entwickelt, die auf den Methoden undWerkzeugen der Geoinformatik beruhen. Eine GDI stellt Konzepte zur Organisation räumlicher Komponenten. Sie besteht aus Geodaten und Metadaten in raumbezogenen Arbeitsprozessen. Die GDI, als Zentrum dieser Arbeitsprozesse, wird mit Technologien, Richtlinien, Regelungen sowie Schnittstellen, die den Zugriff durch unterschiedliche Nutzer ermöglichen, umgesetzt. Datenaustausch ist das Hauptziel des Konzeptes. Wie bereits erwähnt, ist der Datenaustausch wichtig für PA-Tätigkeiten und er kann von den definierten Komponenten einer GDI profitieren. Ferner bereichert der Austausch mit anderen Gebieten die PA-Prozesse. Der Import zusätzlicher Daten ist daher ein Gewinn. Gleichzeitig bietet eine Export-Schnittstelle für landwirtschaftliche Daten neue Möglichkeiten. Koordinierte Kommunikation sichert das Verständnis für jeden Teilnehmer. Aus technischer Sicht sind standardisierte Schnittstellen die beste Lösung. Diese Arbeit zeigt den Gewinn durch einen standardisierten Datenaustausch für PA, indem die Standards des Open Geospatial Consortium (OGC) genutzt wurden. Der OGC entwickelt und publiziert eine Vielzahl von relevanten Standards, die eine große Reichweite in Geo-Software haben. Sie haben sich in der Praxis anderer Bereiche bewährt und wurden in den letzten Jahren teilweise in FMIS eingesetzt. Abhängig von ihrer Ausrichtung könnten sie Softwarelösungen unterstützen, indem sie zusätzliche Informationen für Menschen oder Maschinen in zusätzlicher Logik oder Algorithmen integrieren. Diese Arbeit zeigt die Vorzüge eines standardisierten Datenaustauschs für PA, insbesondere durch die Standards des OGC. Die Ziele der Forschung waren: (i) die Nutzbarkeit von PA-Werkzeugen zu erhöhen und damit die Technologie einer breiteren Gruppe von Anwendern verfügbar zu machen, (ii) externe Daten und Dienste ohne Unterbrechung sowie über standardisierte Schnittstellen für PA-Anwendungen einzubeziehen, (iii) den Austausch mit anderen Bereichen im Bezug auf Daten und Technologien zu unterstützen, (iv) eine moderne PA-Softwarearchitektur zu erschaffen, die es neuen Teilnehmern und bekannten Marken ermöglicht, Prozesse in PA zu unterstützen und neue Geschäftsfelder zu entwickeln, (v) IT-Technologien als Antrieb für die Landwirtschaft zu nutzen und einen Beitrag zur Digitalisierung der Landwirtschaft zu leisten

Location- and keyword-based querying of geo-textual data: a survey

With the broad adoption of mobile devices, notably smartphones, keyword-based search for content has seen increasing use by mobile users, who are often interested in content related to their geographical location. We have also witnessed a proliferation of geo-textual content that encompasses both textual and geographical information. Examples include geo-tagged microblog posts, yellow pages, and web pages related to entities with physical locations. Over the past decade, substantial research has been conducted on integrating location into keyword-based querying of geo-textual content in settings where the underlying data is assumed to be either relatively static or is assumed to stream into a system that maintains a set of continuous queries. This paper offers a survey of both the research problems studied and the solutions proposed in these two settings. As such, it aims to offer the reader a first understanding of key concepts and techniques, and it serves as an “index” for researchers who are interested in exploring the concepts and techniques underlying proposed solutions to the querying of geo-textual data.Agency for Science, Technology and Research (A*STAR)Ministry of Education (MOE)Nanyang Technological UniversityThis research was supported in part by MOE Tier-2 Grant MOE2019-T2-2-181, MOE Tier-1 Grant RG114/19, an NTU ACE Grant, and the Singtel Cognitive and Artificial Intelligence Lab for Enterprises (SCALE@NTU), which is a collaboration between Singapore Telecommunications Limited (Singtel) and Nanyang Technological University (NTU) that is funded by the Singapore Government through the Industry Alignment Fund Industry Collaboration Projects Grant, and by the Innovation Fund Denmark centre, DIREC

Geospatial Information Research: State of the Art, Case Studies and Future Perspectives

Geospatial information science (GI science) is concerned with the development and application of geodetic and information science methods for modeling, acquiring, sharing, managing, exploring, analyzing, synthesizing, visualizing, and evaluating data on spatio-temporal phenomena related to the Earth. As an interdisciplinary scientific discipline, it focuses on developing and adapting information technologies to understand processes on the Earth and human-place interactions, to detect and predict trends and patterns in the observed data, and to support decision making. The authors – members of DGK, the Geoinformatics division, as part of the Committee on Geodesy of the Bavarian Academy of Sciences and Humanities, representing geodetic research and university teaching in Germany – have prepared this paper as a means to point out future research questions and directions in geospatial information science. For the different facets of geospatial information science, the state of art is presented and underlined with mostly own case studies. The paper thus illustrates which contributions the German GI community makes and which research perspectives arise in geospatial information science. The paper further demonstrates that GI science, with its expertise in data acquisition and interpretation, information modeling and management, integration, decision support, visualization, and dissemination, can help solve many of the grand challenges facing society today and in the future

A Data-driven Methodology Towards Mobility- and Traffic-related Big Spatiotemporal Data Frameworks

Human population is increasing at unprecedented rates, particularly in urban areas. This increase, along with the rise of a more economically empowered middle class, brings new and complex challenges to the mobility of people within urban areas. To tackle such challenges, transportation and mobility authorities and operators are trying to adopt innovative Big Data-driven Mobility- and Traffic-related solutions. Such solutions will help decision-making processes that aim to ease the load on an already overloaded transport infrastructure. The information collected from day-to-day mobility and traffic can help to mitigate some of such mobility challenges in urban areas. Road infrastructure and traffic management operators (RITMOs) face several limitations to effectively extract value from the exponentially growing volumes of mobility- and traffic-related Big Spatiotemporal Data (MobiTrafficBD) that are being acquired and gathered. Research about the topics of Big Data, Spatiotemporal Data and specially MobiTrafficBD is scattered, and existing literature does not offer a concrete, common methodological approach to setup, configure, deploy and use a complete Big Data-based framework to manage the lifecycle of mobility-related spatiotemporal data, mainly focused on geo-referenced time series (GRTS) and spatiotemporal events (ST Events), extract value from it and support decision-making processes of RITMOs. This doctoral thesis proposes a data-driven, prescriptive methodological approach towards the design, development and deployment of MobiTrafficBD Frameworks focused on GRTS and ST Events. Besides a thorough literature review on Spatiotemporal Data, Big Data and the merging of these two fields through MobiTraffiBD, the methodological approach comprises a set of general characteristics, technical requirements, logical components, data flows and technological infrastructure models, as well as guidelines and best practices that aim to guide researchers, practitioners and stakeholders, such as RITMOs, throughout the design, development and deployment phases of any MobiTrafficBD Framework. This work is intended to be a supporting methodological guide, based on widely used Reference Architectures and guidelines for Big Data, but enriched with inherent characteristics and concerns brought about by Big Spatiotemporal Data, such as in the case of GRTS and ST Events. The proposed methodology was evaluated and demonstrated in various real-world use cases that deployed MobiTrafficBD-based Data Management, Processing, Analytics and Visualisation methods, tools and technologies, under the umbrella of several research projects funded by the European Commission and the Portuguese Government.A população humana cresce a um ritmo sem precedentes, particularmente nas áreas urbanas. Este aumento, aliado ao robustecimento de uma classe média com maior poder económico, introduzem novos e complexos desafios na mobilidade de pessoas em áreas urbanas. Para abordar estes desafios, autoridades e operadores de transportes e mobilidade estão a adotar soluções inovadoras no domínio dos sistemas de Dados em Larga Escala nos domínios da Mobilidade e Tráfego. Estas soluções irão apoiar os processos de decisão com o intuito de libertar uma infraestrutura de estradas e transportes já sobrecarregada. A informação colecionada da mobilidade diária e da utilização da infraestrutura de estradas pode ajudar na mitigação de alguns dos desafios da mobilidade urbana. Os operadores de gestão de trânsito e de infraestruturas de estradas (em inglês, road infrastructure and traffic management operators — RITMOs) estão limitados no que toca a extrair valor de um sempre crescente volume de Dados Espaciotemporais em Larga Escala no domínio da Mobilidade e Tráfego (em inglês, Mobility- and Traffic-related Big Spatiotemporal Data —MobiTrafficBD) que estão a ser colecionados e recolhidos. Os trabalhos de investigação sobre os tópicos de Big Data, Dados Espaciotemporais e, especialmente, de MobiTrafficBD, estão dispersos, e a literatura existente não oferece uma metodologia comum e concreta para preparar, configurar, implementar e usar uma plataforma (framework) baseada em tecnologias Big Data para gerir o ciclo de vida de dados espaciotemporais em larga escala, com ênfase nas série temporais georreferenciadas (em inglês, geo-referenced time series — GRTS) e eventos espacio- temporais (em inglês, spatiotemporal events — ST Events), extrair valor destes dados e apoiar os RITMOs nos seus processos de decisão. Esta dissertação doutoral propõe uma metodologia prescritiva orientada a dados, para o design, desenvolvimento e implementação de plataformas de MobiTrafficBD, focadas em GRTS e ST Events. Além de uma revisão de literatura completa nas áreas de Dados Espaciotemporais, Big Data e na junção destas áreas através do conceito de MobiTrafficBD, a metodologia proposta contem um conjunto de características gerais, requisitos técnicos, componentes lógicos, fluxos de dados e modelos de infraestrutura tecnológica, bem como diretrizes e boas práticas para investigadores, profissionais e outras partes interessadas, como RITMOs, com o objetivo de guiá-los pelas fases de design, desenvolvimento e implementação de qualquer pla- taforma MobiTrafficBD. Este trabalho deve ser visto como um guia metodológico de suporte, baseado em Arqui- teturas de Referência e diretrizes amplamente utilizadas, mas enriquecido com as característi- cas e assuntos implícitos relacionados com Dados Espaciotemporais em Larga Escala, como no caso de GRTS e ST Events. A metodologia proposta foi avaliada e demonstrada em vários cenários reais no âmbito de projetos de investigação financiados pela Comissão Europeia e pelo Governo português, nos quais foram implementados métodos, ferramentas e tecnologias nas áreas de Gestão de Dados, Processamento de Dados e Ciência e Visualização de Dados em plataformas MobiTrafficB

European Handbook of Crowdsourced Geographic Information

This book focuses on the study of the remarkable new source of geographic information that has become available in the form of user-generated content accessible over the Internet through mobile and Web applications. The exploitation, integration and application of these sources, termed volunteered geographic information (VGI) or crowdsourced geographic information (CGI), offer scientists an unprecedented opportunity to conduct research on a variety of topics at multiple scales and for diversified objectives. The Handbook is organized in five parts, addressing the fundamental questions: What motivates citizens to provide such information in the public domain, and what factors govern/predict its validity?What methods might be used to validate such information? Can VGI be framed within the larger domain of sensor networks, in which inert and static sensors are replaced or combined by intelligent and mobile humans equipped with sensing devices? What limitations are imposed on VGI by differential access to broadband Internet, mobile phones, and other communication technologies, and by concerns over privacy? How do VGI and crowdsourcing enable innovation applications to benefit human society? Chapters examine how crowdsourcing techniques and methods, and the VGI phenomenon, have motivated a multidisciplinary research community to identify both fields of applications and quality criteria depending on the use of VGI. Besides harvesting tools and storage of these data, research has paid remarkable attention to these information resources, in an age when information and participation is one of the most important drivers of development. The collection opens questions and points to new research directions in addition to the findings that each of the authors demonstrates. Despite rapid progress in VGI research, this Handbook also shows that there are technical, social, political and methodological challenges that require further studies and research

Spatial and Temporal Sentiment Analysis of Twitter data

The public have used Twitter world wide for expressing opinions. This study focuses on spatio-temporal variation of georeferenced Tweets’ sentiment polarity, with a view to understanding how opinions evolve on Twitter over space and time and across communities of users. More specifically, the question this study tested is whether sentiment polarity on Twitter exhibits specific time-location patterns. The aim of the study is to investigate the spatial and temporal distribution of georeferenced Twitter sentiment polarity within the area of 1 km buffer around the Curtin Bentley campus boundary in Perth, Western Australia. Tweets posted in campus were assigned into six spatial zones and four time zones. A sentiment analysis was then conducted for each zone using the sentiment analyser tool in the Starlight Visual Information System software. The Feature Manipulation Engine was employed to convert non-spatial files into spatial and temporal feature class. The spatial and temporal distribution of Twitter sentiment polarity patterns over space and time was mapped using Geographic Information Systems (GIS). Some interesting results were identified. For example, the highest percentage of positive Tweets occurred in the social science area, while science and engineering and dormitory areas had the highest percentage of negative postings. The number of negative Tweets increases in the library and science and engineering areas as the end of the semester approaches, reaching a peak around an exam period, while the percentage of negative Tweets drops at the end of the semester in the entertainment and sport and dormitory area. This study will provide some insights into understanding students and staff ’s sentiment variation on Twitter, which could be useful for university teaching and learning management

Farm 2.0 Using Wordpress to Manage Geocontent and Promote Regional Food Products

Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies.Recent innovations in geospatial technology have dramatically increased the utility and ubiquity of cartographic interfaces and spatially-referenced content on the web. Capitalizing on these developments, the Farm2.0 system demonstrates an approach to manage user-generated geocontent pertaining to European protected designation of origin (PDO) food products.Wordpress, a popular open-source publishing platform, supplies the framework for a geographic content management system, or GeoCMS, to promote PDO products in the Spanish province of Valencia. The Wordpress platform is modified through a suite of plug-ins and customizations to create an extensible application that could be easily deployed in other regions and administrated cooperatively by distributed regulatory councils. Content, either regional recipes or map locations for vendors and farms, is available for syndication as a GeoRSS feed and aggregated with outside feeds in a dynamic web map

Management and Services

Management in all business areas and organisational activities are the acts of getting people together to accomplish desired goals and objectives. Service is intangible, therefore, it is not too easy to define the theory application in varieties of service industries. Service Management usually incorporates automated systems along with skilled labour; it also provides service development. Due to enormous demand of service industries and management development, the book under the title "Management and Services" would create a milestone in management arena for all categories of readers including Business Administration, Engineering and Architecture. This book covers educational service development, service-oriented-architecture and case research analysis, including theory application in network security, GRID technology, integrated circuit application. The book is comprised of five chapters and has been divided into two parts. Part A contains chapters on service development in educational institutions and it depicts the application of supply chain management concept in service industries like tertiary educational institutions and multiple ways of web 2.0 applications transforming learning patterns and pathways. To understand the subject in a practical manner, Part B of this book consists of noteworthy case studies and research papers on management and services and represents theory application of Data mining, Fuzzy Cluster, Game theory, GRID Technology, simulation of Operational Amplifier and Current Controlled Conveyor II in network security, architecture, and integrated circuit application