GeoExpert - An Expert System Based Framework for Data Quality in Spatial Databases

Usage of very large sets of historical spatial data in knowledge discovery process became a common trend, and in order to obtain better results from this knowledge discovery process the data should be of high quality. In this thesis we proposed a framework \u27GeoExpert\u27 for data quality assessment and cleansing tool for spatial data that integrates the spatial data visualization and analysis capabilities of the ARCGIS, the reason and inference capability of an expert system. In this thesis we implemented the proposed framework both stand-alone and web versions using ArcGIS Engine and ArcGIS Server, respectively. We used JESS expert system shell for the expert system part of the GeoExpert. Use of expert system shell separates the application logic from the actual framework which makes the framework easily updatable and domain independent. In this thesis we implemented the GeoExpert on the spatially referenced water quality data

Integrating Expert System and Geographic Information System for Spatial Decision Making

Spatial decision making is a process of providing an effective solution for a problem that encompasses semi-structured spatial data. It is a challenging task which involves various factors to consider. For example, in order to build a new industry, an appropriate site must be selected for which several factors have to be taken into consideration. Some of the factors, which can affect the decision in this particular case, are air pollution, noise pollution, and distance from living areas, which makes the decision difficult. The geographic information systems (GIS) and the expert systems (ES) have many advantages in solving problems in their prospective areas. Integrating these two systems will benefit in solving spatial decision making problems. In the past, many researchers have proposed integrating systems which extracts the data from the GIS and saves it in the database for decision making. Most of the frameworks which have been developed were system dependent and are not properly structured. So it is difficult to search the data. This thesis proposes a framework which extracts the GIS data and processes it with the help of ES decision making capabilities to solve the spatial decision making problem. This framework is named GeoFilter. This research classifies various types of mechanisms that can be used to integrate these two systems

24th International Conference on Information Modelling and Knowledge Bases

In the last three decades information modelling and knowledge bases have become essentially important subjects not only in academic communities related to information systems and computer science but also in the business area where information technology is applied. The series of European – Japanese Conference on Information Modelling and Knowledge Bases (EJC) originally started as a co-operation initiative between Japan and Finland in 1982. The practical operations were then organised by professor Ohsuga in Japan and professors Hannu Kangassalo and Hannu Jaakkola in Finland (Nordic countries). Geographical scope has expanded to cover Europe and also other countries. Workshop characteristic - discussion, enough time for presentations and limited number of participants (50) / papers (30) - is typical for the conference. Suggested topics include, but are not limited to: 1. Conceptual modelling: Modelling and specification languages; Domain-specific conceptual modelling; Concepts, concept theories and ontologies; Conceptual modelling of large and heterogeneous systems; Conceptual modelling of spatial, temporal and biological data; Methods for developing, validating and communicating conceptual models. 2. Knowledge and information modelling and discovery: Knowledge discovery, knowledge representation and knowledge management; Advanced data mining and analysis methods; Conceptions of knowledge and information; Modelling information requirements; Intelligent information systems; Information recognition and information modelling. 3. Linguistic modelling: Models of HCI; Information delivery to users; Intelligent informal querying; Linguistic foundation of information and knowledge; Fuzzy linguistic models; Philosophical and linguistic foundations of conceptual models. 4. Cross-cultural communication and social computing: Cross-cultural support systems; Integration, evolution and migration of systems; Collaborative societies; Multicultural web-based software systems; Intercultural collaboration and support systems; Social computing, behavioral modeling and prediction. 5. Environmental modelling and engineering: Environmental information systems (architecture); Spatial, temporal and observational information systems; Large-scale environmental systems; Collaborative knowledge base systems; Agent concepts and conceptualisation; Hazard prediction, prevention and steering systems. 6. Multimedia data modelling and systems: Modelling multimedia information and knowledge; Contentbased multimedia data management; Content-based multimedia retrieval; Privacy and context enhancing technologies; Semantics and pragmatics of multimedia data; Metadata for multimedia information systems. Overall we received 56 submissions. After careful evaluation, 16 papers have been selected as long paper, 17 papers as short papers, 5 papers as position papers, and 3 papers for presentation of perspective challenges. We thank all colleagues for their support of this issue of the EJC conference, especially the program committee, the organising committee, and the programme coordination team. The long and the short papers presented in the conference are revised after the conference and published in the Series of “Frontiers in Artificial Intelligence” by IOS Press (Amsterdam). The books “Information Modelling and Knowledge Bases” are edited by the Editing Committee of the conference. We believe that the conference will be productive and fruitful in the advance of research and application of information modelling and knowledge bases. Bernhard Thalheim Hannu Jaakkola Yasushi Kiyok

THE DEVELOPMENT OF A HOLISTIC EXPERT SYSTEM FOR INTEGRATED COASTAL ZONE MANAGEMENT

Coastal data and information comprise a massive and complex resource, which is vital to the practice of Integrated Coastal Zone Management (ICZM), an increasingly important application. ICZM is just as complex, but uses the holistic paradigm to deal with the sophistication. The application domain and its resource require a tool of matching characteristics, which is facilitated by the current wide availability of high performance computing. An object-oriented expert system, COAMES, has been constructed to prove this concept. The application of expert systems to ICZM in particular has been flagged as a viable challenge and yet very few have taken it up. COAMES uses the Dempster- Shafer theory of evidence to reason with uncertainty and importantly introduces the power of ignorance and integration to model the holistic approach. In addition, object orientation enables a modular approach, embodied in the inference engine - knowledge base separation. Two case studies have been developed to test COAMES. In both case studies, knowledge has been successfully used to drive data and actions using metadata. Thus a holism of data, information and knowledge has been achieved. Also, a technological holism has been proved through the effective classification of landforms on the rapidly eroding Holderness coast. A holism across disciplines and CZM institutions has been effected by intelligent metadata management of a Fal Estuary dataset. Finally, the differing spatial and temporal scales that the two case studies operate at implicitly demonstrate a holism of scale, though explicit means of managing scale were suggested. In all cases the same knowledge structure was used to effectively manage and disseminate coastal data, information and knowledge

Contribuição das poeiras do deserto para o aerossol atmosférico em Cabo Verde e em Portugal

Doutoramento em Ciências e engenharia do ambienteAtravés de processos de erosão são introduzidas na atmosfera grandes quantidades de partículas com origem no solo e transportadas a longa distância, afetando a qualidade do ar e o balanço radiativo da Terra. Este estudo, que se desenvolve no âmbito da interação entre os sistemas terraatmosfera, tem como objetivo principal caracterizar o transporte de poeiras dos desertos de África, focando a análise em Cabo Verde e Portugal. Para atingir este objetivo, recorre-se à modelação de poeiras do deserto, conjugada com observações, incluindo concentrações distribuídas por tamanho de partículas e características óticas das poeiras. Ao longo da Tese, utilizam-se três sistemas de modelos: BSC-DREAM8b, NMMB/BSC-Dust e WRF-CHIMERE, considerando diferentes modelos de produção de poeiras do deserto. Para melhorar a modelação da distribuição por tamanhos das partículas, é implementada e testada uma nova parametrização nas emissões, conduzindo a uma diminuição da fração fina e a um aumento da fração grosseira das emissões. Esta alteração tem impacte nas concentrações e parâmetros óticos modelados a jusante das emissões. Os ciclos temporais dos aerossóis são caracterizados neste trabalho, e são implementados e avaliados diferentes métodos para estimar a contribuição das poeiras do Sahara para os níveis regionais de matéria particulada. Durante o inverno, várias intrusões significativas de poeiras com origem no Noroeste de África influenciam as concentrações de matéria particulada à superfície em Cabo Verde. Durante o verão, as poeiras são transportadas a elevadas altitudes, dando origem a elevados valores de espessura ótica do aerossol. Em termos médios anuais, e de acordo com a metodologia aplicada, cerca de 42% da massa de PM10 observada em Cabo Verde está relacionada com o transporte das poeiras do deserto. Embora os episódios de poeiras do deserto sejam menos severos em Portugal, durante 2016, verificaram-se pelo menos duas situações de transporte de poeiras do deserto, que ocorreram em Fevereiro e em Outubro, responsáveis por excedências regionais ao valor limite diário definido para PM10 na Diretiva Quadro da Qualidade do Ar. Este estudo contribui para a caracterização dos processos e fontes responsáveis pela intrusão de poeiras minerais na atmosfera e apresenta novas abordagens e informação importante para transmitir aos agentes envolvidos em processos de tomada de decisão.Due to erosion processes, huge quantities of soil-derived particles are entrained into the atmosphere and transported away from the source, impacting air quality and affecting the Earth’s radiative budget. This Thesis addresses those land-atmosphere interactions, dealing with atmospheric mineral aerosol, with a main objective of improving the assessment of longrange transport of African dust focusing on Cape Verde and Portugal. To achieve the objective, dust modelling is employed and combined with observations, including size distributed particle concentrations and optical properties. Three different modelling systems are used, namely BSCDREAM8b, the NMMB/BSC-Dust model and WRF-CHIMERE, with distinct dust production models. In order to improve characterization of the dust size distribution at emission, a new parametrization is tested in this work, leading to a decrease in the emission fine fractions and an increase in the coarser ones, which has an impact in modelled downwind concentrations and optical parameters. Aerosol cycles are characterized and different methods to estimate the contribution of Saharan dust to regional PM levels are implemented and assessed. Significant dust intrusions from North West Africa severely affect Cape Verde PM surface concentrations during winter. In the summer dust is transported towards the region at higher altitudes, yielding high aerosol optical depths. On a yearly basis, and according to the methodology employed, roughly 42% of the PM10 mass observed in Cape Verde is associated with dust transported from North African deserts. Desert dust outbreaks are less severe in Portugal. Nevertheless, during 2016, at least two dust episodes, occurring in February and October, are responsible for regional exceedances of the PM10 daily limit value defined in the Air Quality Directive. This study intends to improve the scientific knowledge on processes and sources responsible for mineral dust loading into the atmosphere and to provide new means and valuable information for science-based decision making