Specification of high-level application programming interfaces (SemSorGrid4Env)

This document defines an Application Tier for the SemsorGrid4Env project. Within the Application Tier we distinguish between Web Applications - which provide a User Interface atop a more traditional Service Oriented Architecture - and Mashups which are driven by a REST API and a Resource Oriented Architecture. A pragmatic boundary is set to enable initial development of Web Applications and Mashups; as the project progresses an evaluation and comparison of the two paradigms may lead to a reassessment of where each can be applied within the project, with the experience gained providing a basis for general guidelines and best practice. Both Web Applications and Mashups are designed and delivered through an iterative user-centric process; requirements generated by the project case studies are a key element of this approach

Automatic integration of spatial data in viewing services

Geoportals are increasingly used for searching viewing and downloading spatial data. This study concerns methods to improve the visual presentation in viewing services. When spatial data in a viewing service are taken from more than one source there are often syntactic semantic topological and geometrical conflicts that prevent maps being fully consistent. In this study we extend a standard view service with methods to solve these conflicts. The methods are based on: (1) semantic labels of data in basic services (2) a rule-base in the portal layer and (3) integration methods in the portal layer. To evaluate the methodology we use a case study for adding historical borders on top of a base-map. The results show that the borders are overlaid on top of the map without conflicts and that a consistent map is generated automatically as an output. The methodology can be generalized to add other types of data on top of a base-map

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

Innovative approaches to urban data management using emerging technologies

Many characteristics of Smart cities rely on a sufficient quantity and quality of urban data. Local industry and developers can use this data for application development that improves life of all citizens. Therefore, the handling and usability of this data is a big challenge for smart cities. In this paper we investigate new approaches to urban data management using emerging technologies and give an insight on further research conducted within the EC-funded smarticipate project. Geospatial data cannot be handled well in classical relational database environments. Either they are just put in as binary large objects or have to be broken down into elementary types which can be handled by the database, in many cases resulting in a slow system, since the database technology is not really tuned for delivery on mass data as classical relational databases are optimized for online transaction processing and not analytic processing. Document-based databases provide a better performance, but still struggle with the challenge of large binary objects. Also the heterogeneity of data requires a lot of mapping and data cleansing, in some cases replication can’t be avoided. Another approach is to use Semantic Web technologies to enhance the data and build up relations and connections between entities. However, data formats such as RDF use a different approach and are not suitable for geospatial data leading to a lack on usability. Search engines are a good example of web applications with a high usability. The users must be able to find the right data and get information of related or close matches. This allows information retrieval in an easy to use fashion. The same principles should be applied to geospatial data, which would improve the usability of open data. Combined with data mining and big data technologies those principles would improve the usability of open geospatial data and even lead to new ways to use it. By helping with the interpretation of data in a certain context data is transformed into useful information. In this paper we analyse key features of open geodata portals such as linked data and machine learning in order to show ways of improving the user experience. Based on the Smarticipate projects we show afterwards as open data and geo data online and see the practical application. We also give an outlook on piloting cases where we want to evaluate, how the technologies presented in this paper can be combined to a usefull open data portal. In contrast to the previous EC-funded project urbanapi, where participative processes in smart cities where created with urban data, we go one step further with semantic web and open data. Thereby we achieve a more general approach on open data portals for spatial data and how to improve their usability. The envisioned architecture of the smarticipate project relies on file based storage and a no-copy strategy, which means that data is mostly kept in its original format, a conversion to another format is only done if necessary (e.g. the current format has limitations on domain specific attributes or the user requests a specific format). A strictly functional approach and architecture is envisioned which allows a massively parallel execution and therefore is predestined to be deployed in a cloud environment. The actual search interface uses a domain specific vocabulary which can be customised for special purposes or for users that consider their context and expertise, which should abstract from technology specific peculiarities. Also application programmers will benefit form this architecture as linked data principles will be followed extensively. For example, the JSON and JSON-LD standards will be used, so that web developers can use results of the data store directly without the need for conversion. Also links to further information will be provided within the data, so that a drill down is possible for more details. The remainder of this paper is structured as follows. After the introduction about open data and data in general we look at related work and existing open data portals. This leads to the main chapter about the key technology aspects for an easy-to-use open data portal. This is followed by Chapter five, an introduction of the EC-funded project smarticipate, in which the key technology aspects of chapter four will be included

Spatiotemporal data as the foundation of an archaeological stratigraphy extraction and management system

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Multimodal and multidimensional geodata interaction and visualization

This PhD proposes the development of a Science Data Visualization System, SdVS, that analyzes and presents different kinds of visualizing and interacting techniques with Geo-data, in order to deal with knowledge about Geo-data using GoogleEarth. After that, we apply the archaeological data as a case study, and, as a result, we develop the Archaeological Visualization System, ArVS, using new visualization paradigms and Human-Computer-Interaction techniques based on SdVS. Furthermore, SdVS provides guidelines for developing any other visualization and interacting applications in the future, and how the users can use SdVS system to enhance the understanding and dissemination of knowledge

Methods to Improve and Evaluate Spatial Data Infrastructures

This thesis mainly focuses on methods for improving and evaluating Spatial Data Infrastructures (SDIs). The aim has been threefold: to develop a framework for the management and evaluation of an SDI, to improve the accessibility of spatial data in an SDI, and to improve the cartography in view services in an SDI. Spatial Data Infrastructure has been identified as an umbrella covering spatial data handling procedures. The long-term implementation of SDI increases the need for short/middle term feedbacks from different perspectives. Thus, a precise strategic plan and accurate objectives have to be defined for the implementation of an efficient environment for spatial data collection and exchange in a region. In this thesis, a comprehensive study was conducted to review the current methods in the business management literature to approach to an integrated framework for the implementation and evaluation of SDIs. In this context, four techniques were described and the usability of each technique in several aspects of SDI implementation was discussed. SDI evaluation has been considered as one of the main challenges in recent years. Lack of a general goal oriented framework to assess an SDI from different perspectives was one of the main concerns of this thesis. Among a number of the current methods in this research area, we focused on the Balanced Scorecard (BSC) as a general evaluation framework covering all perspectives in an SDI. The assessment study opened a window to a number of important issues that ranged from the technical to the cartographic aspects of spatial data exchange in an SDI. To access the required datasets in an SDI, clearinghouse networks have been developed as a gateway to the data repositories. However, traditional clearinghouse networks do not satisfy the end user requirements. By adding a number of functionalities, we proposed a methodology to increase the percentage of accessing required data. These methods were based on predefined rules and additional procedures within web processing services and service composition subjects to develop an expert system based clearinghouses. From the cartography viewpoint, current methods for spatial data presentation do not satisfy the user requirements in an SDI environment. The main presentation problem occurs when spatial data are integrated from different sources. For appropriate cartography, we propose a number of methods, such as the polygon overlay method, which is an icon placement approach, to emphasize the more important layers and the color saturation method to decrease the color saturation of the unimportant layers and emphasize the foreground layer according to the visual hierarchy concept. Another cartographic challenge is the geometrical and topological conflicts in data shown in view services. The geometrical inconsistency is due to the artificial discrepancy that occurs when displaying connected information from different sources, which is caused by inaccuracies and different levels of details in the datasets. The semantic conflict is related to the definition of the related features, i.e., to the information models of the datasets. To overcome these conflicts and to fix the topological and geometric conflicts we use a semantic based expert system by utilizing an automatic cartography core containing a semantic rule based component. We proposed a system architecture that has an OWL (Web Ontology Language) based expert system to improve the cartography by adjusting and resolving topological and geometrical conflicts in geoportals

Web-based Spatial Decision Support Systems (WebSDSS): Evolution, Architecture, Examples and Challenges

Spatial Decision Support Systems (SDSS), which support spatial analysis and decision making, are currently receiving much attention. Research on SDSS originated from two distinct sources, namely, the GIS community and the DSS community. The synergy between these two research groups has lead to the adoption of state of the art technical solutions and the development of sophisticated SDSS that satisfy the needs of geographers and top-level decision makers. Recently, the Web has added a new dimension to SDSS and Web-based SDSS (WebSDSS) that are being developed in a number of application domains. This article provides an overview of the emergence of SDSS, its architecture and applications, and discusses some of the enabling technologies and research challenges for future SDSS development and deployment