A contribuição deste trabalho é um framework conceitual para a inserção de dados diretos de rocha em modelos de grid de reservatório, através da calibragem de logs de poço. Este tipo de dado é frequentemente ignorado ou processado manualmente nas modelagens atuais, seja por custos elevados para sua obtenção, seja pelo alto grau de complexidade para a modelagem, interpretação e extrapolação dos dados. O framework busca definir os requisitos para um projeto de software que inclua os componentes necessários para o processamento automático ou supervisionado dos dados de rocha desde sua geração até sua utilização final, em modelos de simulação de fluxo, suportando a interoperabilidade dos dados e o rastreamento da informação de rochas. A proposta é embasada na combinação de ontologias de domínio para a petrografia, o conceito geológico de petrofácies de reservatório, um algoritmo de reconhecimento de padrões em logs de poço que podem corresponder a camadas homogêneas na rocha e um algoritmo para extrapolação de padrões baseado em algoritmos de alinhamento de sequências de DNA. A combinação das abordagens utilizadas neste trabalho é inédita e fornece suporte para o uso de petrofácies de reservatório durante a modelagem de reservatório. O levantamento de informações foi realizado em forma de aquisição de conhecimento, através de entrevistas com cinco profissionais de Geologia, Geofísica e Geoquímica, com diferentes formações na indústria do petróleo, além de extensa revisão da literatura. Esta aquisição nos possibilitou mapear as grandes atividades durante o processo de exploração, bem como os dados resultantes de cada etapa. Um modelo conceitual ontologicamente bem fundamentado permite mapear e integrar os dados de rocha nas diferentes etapas de processamento desde sua aquisição, como descrições de amostras de poços, descrições microscópicas e logs geofísicos até a identificação e inserção das propriedades relevantes em grids 3D utilizando padrões de trocas de dados da indústria. / A Conceptual Framework to insert direct rock data into reservoir models trough well logs calibration is the contribution of this work. This kind of data is often ignored or manually processed in the current modeling process, due to its high costs or due to the complexity for the modeling, interpretation and extrapolation of the data. The framework aims to define a software project requirements that includes the necessary components for automated or supervised process of the rock data from its generation until its final use in the flow simulation models, supporting the interoperability of the data and the tracking of the rock information. The proposal is based in the combination of domain ontology for petrography, the geological concept of reservoir petrofacies, a pattern recognition algorithm on well logs that can correspond to homogeneous rock layers and an algorithm to extrapolate patterns based on algorithms for the alignment of DNA sequences. The combination of the approaches used in this work is novel and provides support for the use of reservoir petrofacies during reservoir modeling. Five different professionals from the Geology, Geophysics and Geochemistry fields, with different backgrounds in the oil industry, were interviewed in order to acquire the necessary knowledge, and an extensive review of the literature. This acquisition enabled us to map the major activities during the process of exploration, as well as the data resulting from each step. A ontological well-grounded conceptual model allows mapping and integrating rock data in the different processing steps from its acquisition, such as descriptions of sample wells, microscopic descriptions and geophysical logs, to the identification and insertion of the relevant properties on 3D grids using standards of industry data exchange.

Terrorist attacks can cause massive casualties and severe property damage, resulting in terrorism crises surging across the world; accordingly, counter-terrorism analytics that take advantage of big data have been attracting increasing attention. The knowledge and clues essential for analyzing terrorist activities are often spread across heterogeneous data sources, which calls for an effective data integration solution. In this study, employing the goal definition template in the Goal-Question-Metric approach, we design and implement an automated goal-driven data integration framework for counter-terrorism analytics. The proposed design elicits and ontologizes an input user goal of counter-terrorism analytics; recognizes goal-relevant datasets; and addresses semantic heterogeneity in the recognized datasets. Our proposed design, following the design science methodology, presents a theoretical framing for on-demand data integration designs that can accommodate diverse and dynamic user goals of counter-terrorism analytics and output integrated data tailored to these goals.

The leading effort for creating a standard semantic basis for business documents to solve the electronic business document interoperability problem came from the UN/CEFACT (United Nations Centre for Trade Facilitation and Electronic Business) Core Components Technical Specification (CCTS) through a conceptual document modeling methodology. Currently, the main challenge in using UN/CEFACT CCTS based approaches is that the document artifacts are stored in spreadsheets and this makes it very difficult to discover the previously defined components and to check their consistency. Furthermore, businesses need to customize standard documents according to their specific needs. The first XML implementation of UN/CEFACT CCTS, namely, Universal Business Language (UBL) provides detailed text-based descriptions of customization mechanisms. However, without automated tool support, it is difficult to apply the customization and to maintain the consistency of the customizations. In this thesis, these problems are addressed by providing an online e-business document design and customization environment, i.e. iSURF eDoCreator, which integrates the machine processable versions of paper-based UN/CEFACT CCTTS modeling methodology and UBL customization guidelines, accompanied with an online common UN/CEFACT CCTS based document component repository. In this way, iSURF eDoCreator environment aims to maximize re-use of available document building blocks and minimize the tedious document design and customization efforts. The environment also performs the gap analysis between different customizations of UBL to show how interoperable is the compared document models. The research leading to these results has received funding from the European Community&#039 / s FP7/2007-2013 under grant agreement n&deg / 213031, the iSURF Project.

A contribuição deste trabalho é um framework conceitual para a inserção de dados diretos de rocha em modelos de grid de reservatório, através da calibragem de logs de poço. Este tipo de dado é frequentemente ignorado ou processado manualmente nas modelagens atuais, seja por custos elevados para sua obtenção, seja pelo alto grau de complexidade para a modelagem, interpretação e extrapolação dos dados. O framework busca definir os requisitos para um projeto de software que inclua os componentes necessários para o processamento automático ou supervisionado dos dados de rocha desde sua geração até sua utilização final, em modelos de simulação de fluxo, suportando a interoperabilidade dos dados e o rastreamento da informação de rochas. A proposta é embasada na combinação de ontologias de domínio para a petrografia, o conceito geológico de petrofácies de reservatório, um algoritmo de reconhecimento de padrões em logs de poço que podem corresponder a camadas homogêneas na rocha e um algoritmo para extrapolação de padrões baseado em algoritmos de alinhamento de sequências de DNA. A combinação das abordagens utilizadas neste trabalho é inédita e fornece suporte para o uso de petrofácies de reservatório durante a modelagem de reservatório. O levantamento de informações foi realizado em forma de aquisição de conhecimento, através de entrevistas com cinco profissionais de Geologia, Geofísica e Geoquímica, com diferentes formações na indústria do petróleo, além de extensa revisão da literatura. Esta aquisição nos possibilitou mapear as grandes atividades durante o processo de exploração, bem como os dados resultantes de cada etapa. Um modelo conceitual ontologicamente bem fundamentado permite mapear e integrar os dados de rocha nas diferentes etapas de processamento desde sua aquisição, como descrições de amostras de poços, descrições microscópicas e logs geofísicos até a identificação e inserção das propriedades relevantes em grids 3D utilizando padrões de trocas de dados da indústria. / A Conceptual Framework to insert direct rock data into reservoir models trough well logs calibration is the contribution of this work. This kind of data is often ignored or manually processed in the current modeling process, due to its high costs or due to the complexity for the modeling, interpretation and extrapolation of the data. The framework aims to define a software project requirements that includes the necessary components for automated or supervised process of the rock data from its generation until its final use in the flow simulation models, supporting the interoperability of the data and the tracking of the rock information. The proposal is based in the combination of domain ontology for petrography, the geological concept of reservoir petrofacies, a pattern recognition algorithm on well logs that can correspond to homogeneous rock layers and an algorithm to extrapolate patterns based on algorithms for the alignment of DNA sequences. The combination of the approaches used in this work is novel and provides support for the use of reservoir petrofacies during reservoir modeling. Five different professionals from the Geology, Geophysics and Geochemistry fields, with different backgrounds in the oil industry, were interviewed in order to acquire the necessary knowledge, and an extensive review of the literature. This acquisition enabled us to map the major activities during the process of exploration, as well as the data resulting from each step. A ontological well-grounded conceptual model allows mapping and integrating rock data in the different processing steps from its acquisition, such as descriptions of sample wells, microscopic descriptions and geophysical logs, to the identification and insertion of the relevant properties on 3D grids using standards of industry data exchange.

A contribuição deste trabalho é um framework conceitual para a inserção de dados diretos de rocha em modelos de grid de reservatório, através da calibragem de logs de poço. Este tipo de dado é frequentemente ignorado ou processado manualmente nas modelagens atuais, seja por custos elevados para sua obtenção, seja pelo alto grau de complexidade para a modelagem, interpretação e extrapolação dos dados. O framework busca definir os requisitos para um projeto de software que inclua os componentes necessários para o processamento automático ou supervisionado dos dados de rocha desde sua geração até sua utilização final, em modelos de simulação de fluxo, suportando a interoperabilidade dos dados e o rastreamento da informação de rochas. A proposta é embasada na combinação de ontologias de domínio para a petrografia, o conceito geológico de petrofácies de reservatório, um algoritmo de reconhecimento de padrões em logs de poço que podem corresponder a camadas homogêneas na rocha e um algoritmo para extrapolação de padrões baseado em algoritmos de alinhamento de sequências de DNA. A combinação das abordagens utilizadas neste trabalho é inédita e fornece suporte para o uso de petrofácies de reservatório durante a modelagem de reservatório. O levantamento de informações foi realizado em forma de aquisição de conhecimento, através de entrevistas com cinco profissionais de Geologia, Geofísica e Geoquímica, com diferentes formações na indústria do petróleo, além de extensa revisão da literatura. Esta aquisição nos possibilitou mapear as grandes atividades durante o processo de exploração, bem como os dados resultantes de cada etapa. Um modelo conceitual ontologicamente bem fundamentado permite mapear e integrar os dados de rocha nas diferentes etapas de processamento desde sua aquisição, como descrições de amostras de poços, descrições microscópicas e logs geofísicos até a identificação e inserção das propriedades relevantes em grids 3D utilizando padrões de trocas de dados da indústria. / A Conceptual Framework to insert direct rock data into reservoir models trough well logs calibration is the contribution of this work. This kind of data is often ignored or manually processed in the current modeling process, due to its high costs or due to the complexity for the modeling, interpretation and extrapolation of the data. The framework aims to define a software project requirements that includes the necessary components for automated or supervised process of the rock data from its generation until its final use in the flow simulation models, supporting the interoperability of the data and the tracking of the rock information. The proposal is based in the combination of domain ontology for petrography, the geological concept of reservoir petrofacies, a pattern recognition algorithm on well logs that can correspond to homogeneous rock layers and an algorithm to extrapolate patterns based on algorithms for the alignment of DNA sequences. The combination of the approaches used in this work is novel and provides support for the use of reservoir petrofacies during reservoir modeling. Five different professionals from the Geology, Geophysics and Geochemistry fields, with different backgrounds in the oil industry, were interviewed in order to acquire the necessary knowledge, and an extensive review of the literature. This acquisition enabled us to map the major activities during the process of exploration, as well as the data resulting from each step. A ontological well-grounded conceptual model allows mapping and integrating rock data in the different processing steps from its acquisition, such as descriptions of sample wells, microscopic descriptions and geophysical logs, to the identification and insertion of the relevant properties on 3D grids using standards of industry data exchange.

no / Smart Sustainable Cities (SSC) consist of multiple stakeholders, who must cooperate in order for SSCs to be successful. Housing is an important challenge and in many cities, therefore, a key stakeholder are social housing organisations. This paper introduces a qualitative case study of a social housing provider in the UK who implemented a business intelligence project (a method to assess data networks within an organisation) to increase data quality and data interoperability. Our analysis suggests that creating pathways for different information systems within an organisation to ‘talk to’ each other is the first step. Some of the issues during the project implementation include the lack of training and development, organisational reluctance to change, and the lack of a project plan. The challenges faced by the organisation during this project can be helpful for those implementing SSCs. Currently, many SSC frameworks and models exist, yet most seem to neglect localised challenges faced by the different stakeholders. This paper hopes to help bridge this gap in the SSC research agenda.

Previous research has studied the use of Building Performance Simulations (BPS) tools withBuilding Information Modeling (BIM). BPS can be used to visualize and evaluate the designof buildings. Virtual Reality (VR) can be used as a BPS tool for designing indoor lighting.The problem is that previous research still has difficulties with data interoperability. That isthe integration of VR with BIM. Many studies suggest using the file format IFC to mitigatethis problem.The aim of this study is to investigate how to increase data interoperability by using a fileformat IFC. A prototype system will be developed to test this. The research question is if openBIM formats can improve the quality of design solutions? The study will try to answer howVR can be integrated with BIM and how VR can be used for indoor lighting design.The result from this thesis is in part a prototype system called FooBar. FooBar shows how VRcan be integrated with BIM. However, the file format IFC was not used throughout the wholedesign process. Instead, IFC is only used at the beginning and the end of the process. Thisstudy shows how VR can be used as an alternative BPS tool. Users can manipulate lights inthe building model. These changes are then updated in the original BIM model.This means that VR can be used to improve the quality of design solutions. In other words,FooBar can help to cope with multidisciplinary design processes. Users can immersethemselves into the virtual environment and see different design alternatives for themselves.Different design alternatives can easily be rendered in VR. With a system like FooBar, userscan easily define, propose, and analyze different design ideas to reach design goals. / Tidigare forskning har studerat hur simuleringsverktyg (Building Performance Simulations,BPS) kan användas med byggnadsinformationsmodellering (Building Information Modeling,BIM).Simuleringsverktyg kan dels användas för att visualisera design och användas somdesignutvärdering. Virtual Reality (VR), eller virtuell verklighet, kan användas som ettsimuleringsverktyg för design av inomhusbelysning. Problemet är att tidigare forskning harproblem med datakompatibilitet, d.v.s. integrationen av VR med BIM. Många studier föreslåratt filformatet IFC används för att lösa detta problem.Syftet med denna studie är att undersöka hur man ökar datakompatibiliteten genom attanvända ett IFC. Ett prototypsystem kommer att utvecklas för att testa detta. Forskningsfråganhandlar om huruvida öppna BIM-format kan förbättra kvaliteten på designlösningarna.Studien ska även försöka svara på hur VR kan integreras med BIM och hur VR kan användasför inomhusbelysningsdesign.Resultatet av detta arbete är en del av ett prototypsystem kallat FooBar. FooBar visar hur VRkan integreras med BIM. Filformatet IFC användes emellertid inte under heladesignprocessen. Istället används IFC endast i början och slutet av processen. Det andraresultatet är att denna studie visar hur VR kan användas som ett alternativ till andrasimuleringsverktyg. Med FooBar kan användare flytta, rotera och skala om ljus ibyggnadsmodellen. Dessa ändringar uppdateras sedan i den ursprungliga BIM-modellen.Det betyder att VR kan användas för att förbättra kvaliteten på designlösningarna. FooBar kanmed andra ord bidra till att underlätta multidisciplinära designprocesser. Användare kan självakliva in i den virtuella miljön (i VR) och se olika designalternativ framför sig. Således kanolika designalternativ enkelt göras i VR. Med ett system som FooBar kan användarna enkeltdefiniera, föreslå och analysera olika designidéer för att nå de designmål som finns i projektet.

No / Smart Sustainable Cities (SSC) consist of multiple stakeholders, who must cooperate in order for SSCs to be successful. Housing is an important challenge and in many cities, therefore, a key stakeholder are social housing organisations. This paper introduces a qualitative case study of a social housing provider in the UK who implemented a business intelligence project (a method to assess data networks within an organisation) to increase data quality and data interoperability. Our analysis suggests that creating pathways for different information systems within an organisation to ‘talk to’ each other is the first step. Some of the issues during the project implementation include the lack of training and development, organisational reluctance to change, and the lack of a project plan. The challenges faced by the organisation during this project can be helpful for those implementing SSCs. Currently, many SSC frameworks and models exist, yet most seem to neglect localised challenges faced by the different stak

Efficient data integration is one of the most challenging problems in data management, interoperation and analysis. The Earth science data which are heterogeneous are collected at various geographical locations for scientific studies and operational uses. The intrinsic problem of archiving, distributing and searching such huge scientific datasets is compounded by the heterogeneity of data and queries, thus limiting scientific analysis, and generation/validation of hydrologic forecast models. The data models of hydrologic research communities such as National Weather Service (NWS), National Oceanic and Atmospheric Administration (NOAA), and US Geological Survey (USGS) are diverse and complex. A complete derivation of any useful hydrological models from data integrated from all these sources is often a time consuming process. One of the current trends of data harvesting in scientific community is towards a distributed digital library initiative. However, these approaches may not be adequate for data sources / entities who do not want to "upload" the data into a "data pool." In view of this, we present here an effective architecture to address the issues of data integration in such a diverse environment for hydrological studies. The heterogeneities in these datasets are addressed based on the autonomy of data source in terms of design, communication, association and execution using a hierarchical integration model. A metadata model is also developed for defining data as well as the data sources, thus providing a uniform view of the data for different kind of users. An implementation of the model using web based system that integrates widely varied hydrology datasets from various data sources is also being developed. / Master of Science

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