Archived project

PESCaDO

Goal: There is an increasing need to orchestrate environmental services located on the Web in order to enable personalised decision support or to provide tailored environmental information. The reasons are multi-fold. For instance, there is only a partial coverage of the environmental conditions given by one provider, however, the environmental information provided must be of high-quality standard. Furthermore, there are often contractual restrictions to provide complementary external data for the top parameters. Users also face contradictory information from several sources and difficulties in information assessment for decision making. Based upon recent works and the application of innovative technologies, PESCaDO significantly advances the state-of-the-art and aims at the following five objectives: 1. Consider alternative services on the Web or the best complementary service to be chained to their own service or to be used as a decision support service. 2. Assess the confidence in the service’s data and offer reliable metrics of the degradation of data uncertainty in complex service node constellations 3. Enable dynamic selection and connection of nodes based on quality, content or the service chain configurations. 4. Integrate the user into the process of service orchestration and information delivery. 5. Treat service orchestration in connection with user decision support. PESCaDO develops environmental node discovery techniques based on advanced domain-specific Web search engines and multilingual analysis to derive the functional and qualitative coverage of the nodes. The reliability of the services and the uncertainty of the direct or propagated data will be assessed by confidence and data uncertainty metrics, among others derived from Fuzzy Theory. PESCaDO targets service orchestration, guided by the quality and content of service nodes and context criteria for decision support. Users are involved in the entire process. Their output is personalized in form and language.

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Project log

Simon Mille
added a research item
Data on observed and forecasted environmental conditions, such as weather, air quality and pollen, are offered in a great variety in the web and serve as basis for decisions taken by a wide range of the population. However, the value of these data is limited because their quality varies largely and because the burden of their interpretation in the light of a specific context and in the light of the specific needs of a user is left to the user herself. To remove this burden from the user, we propose an environmental Decision Support System (DSS) model with an ontology-based knowledge base as its integrative core. The availability of an ontological knowledge representation allows us to encode in a uniform format all knowledge that is involved (environmental background knowledge, the characteristic features of the profile of the user, the formal description of the user request, measured or forecasted environmental data, etc.) and apply advanced reasoning techniques on it. The result is an advanced DSS that provides high quality environmental information for personalized decision support.
Jürgen Moßgraber
added 9 research items
Analysis of environmental information is considered of utmost importance for humans, since environmental conditions are strongly related to health issues and to a variety of everyday activities. Despite the fact that there are already many free on-line services providing environmental information, there are several cases, in which the presentation format complicates the extraction and processing of such data. A very characteristic example is the air quality forecasts, which are usually encoded in image maps of heterogeneous formats, while the initial (numerical) pollutant concentrations, calculated and predicted by a relevant model, remain unavailable. This work addresses the task of semi-automatic extraction of such information based on a template configuration tool, on methodologies for data reconstruction from images, as well as on Optical Character Recognition (OCR) techniques. The framework is tested with a number of air quality forecast heatmaps demonstrating satisfactory results.
Many kinds of environmental data are nowadays publicly available, but spread over the web. This paper discusses using the Sensor Observation Service (SOS) standard of the Open Geospatial Consortium (OGC) as a common interface for providing data from heterogeneous sources which can be integrated to a user tailored environmental information system. In order to allow for providing user-tailored and problem-specific information the adjusted SOS is augmented by a semantic layer which maps the environmental information to ontology concepts. The necessary information fusion from different domains and data types lead to several specific requirements for the SOS. Addressing these requirements we have implemented a SOS which still conforms to the OGC SOS 1.0.0 standard specification. The developed SOS has been integrated in a publicly available demonstrator of our personalized environmental information system. Additionally this paper discusses future consequences for the SOS, caused by the recently published SOS 2.0 specification.
Extraction and analysis of environmental information is very important, since it strongly affects everyday life. Nowadays there are already many free services providing environmental information in several formats including multimedia (e.g. map images). Although such presentation formats might be very informative for humans, they complicate the automatic extraction and processing of the underlying data. A characteristic example is the air quality and pollen forecasts, which are usually encoded in image maps, while the initial (numerical) pollutant concentrations remain unavailable. This work proposes a framework for the semi-automatic extraction of such information based on a template configuration tool, on Optical Character Recognition (OCR) techniques and on methodologies for data reconstruction from images. The system is tested with a different air quality and pollen forecast heatmaps demonstrating promising results.
Désirée Hilbring
added a research item
Citizens are increasingly aware of the influence of environmental and meteorological conditions on the quality of their life. This results in an increasing demand for personalized environmental information, i.e., information that is tailored to citizens’ specific context and background. In this demonstration, we present an environmental information system that addresses this demand in its full complexity in the context of the PESCaDO EU project. Specifically, we will show a system that supports submission of user generated queries related to environmental conditions. From the technical point of view, the system is tuned to discover reliable data in the web and to process these data in order to convert them into knowledge, which is stored in a dedicated repository. At run time, this information is transferred into an ontology-based knowledge base, from which then information relevant to the specific user is deduced and communicated in the language of their preference.
Désirée Hilbring
added a research item
Environmental and meteorological conditions are of utmost importance for the population, as they are strongly related to the quality of life. Citizens are increasingly aware of this importance. This awareness results in an increasing demand for environmental information tailored to their specific needs and background. We present an environmental information platform that supports submission of user queries related to environmental conditions and orchestrates results from complementary services to generate personalized suggestions. From the technical viewpoint, the system discovers and processes reliable data in the web in order to convert them into knowledge. At run time, this information is transferred into an ontology-structured knowledge base, from which then information relevant to the specific user is deduced and communicated in the language of their preference. The platform is demonstrated with real world use cases in the south area of Finland showing the impact it can have on the quality of everyday life. © 2012 IFIP International Federation for Information Processing.
Jürgen Moßgraber
added 11 project references
Jürgen Moßgraber
added a project goal
There is an increasing need to orchestrate environmental services located on the Web in order to enable personalised decision support or to provide tailored environmental information. The reasons are multi-fold. For instance, there is only a partial coverage of the environmental conditions given by one provider, however, the environmental information provided must be of high-quality standard. Furthermore, there are often contractual restrictions to provide complementary external data for the top parameters. Users also face contradictory information from several sources and difficulties in information assessment for decision making. Based upon recent works and the application of innovative technologies, PESCaDO significantly advances the state-of-the-art and aims at the following five objectives: 1. Consider alternative services on the Web or the best complementary service to be chained to their own service or to be used as a decision support service. 2. Assess the confidence in the service’s data and offer reliable metrics of the degradation of data uncertainty in complex service node constellations 3. Enable dynamic selection and connection of nodes based on quality, content or the service chain configurations. 4. Integrate the user into the process of service orchestration and information delivery. 5. Treat service orchestration in connection with user decision support. PESCaDO develops environmental node discovery techniques based on advanced domain-specific Web search engines and multilingual analysis to derive the functional and qualitative coverage of the nodes. The reliability of the services and the uncertainty of the direct or propagated data will be assessed by confidence and data uncertainty metrics, among others derived from Fuzzy Theory. PESCaDO targets service orchestration, guided by the quality and content of service nodes and context criteria for decision support. Users are involved in the entire process. Their output is personalized in form and language.
 
Jürgen Moßgraber
added a research item
Environmental and meteorological conditions are of utmost importance for the population, as they are strongly related to the quality of life. Citizens are increasingly aware of this importance. This awareness results in an increasing demand for environmental information tailored to their specific needs and background. We present an environmental information platform that supports submission of user queries related to environmental conditions and orchestrates results from complementary services to generate personalized suggestions. The system discovers and processes reliable data in the Web in order to convert them into knowledge. At runtime, this information is transferred into an ontology-structured knowledge base, from which then information relevant to the specific user is deduced and communicated in the language of their preference. The platform is demonstrated with real world use cases in the south area of Finland, showing the impact it can have on the quality of everyday life.