42 research outputs found

    Geographica: A Benchmark for Geospatial RDF Stores

    Full text link
    Geospatial extensions of SPARQL like GeoSPARQL and stSPARQL have recently been defined and corresponding geospatial RDF stores have been implemented. However, there is no widely used benchmark for evaluating geospatial RDF stores which takes into account recent advances to the state of the art in this area. In this paper, we develop a benchmark, called Geographica, which uses both real-world and synthetic data to test the offered functionality and the performance of some prominent geospatial RDF stores

    Sextant: Visualizing time-evolving linked geospatial data

    Get PDF
    The linked open data cloud is constantly evolving as datasets get continuously updated with newer versions. As a result, representing, querying, and visualizing the temporal dimension of linked data is crucial. This is especially important for geospatial datasets that form the backbone of large scale open data publication efforts in many sectors of the economy (e.g., the public sector, the Earth Observation sector). Although there has been some work on the representation and querying of linked geospatial data that change over time, to the best of our knowledge, there is currently no tool that offers spatio-temporal visualization of such data. This is in contrast with the existence of many tools for the visualization of the temporal evolution of geospatial data in the GIS area. In this article, we present Sextant, a Web-based system for the visualization and exploration of time-evolving linked geospatial data and the creation, sharing, and collaborative editing of “temporally-enriched” thematic maps which are produced by combining different sources of such data. We present the architecture of Sextant, give examples of its use and present applications in which we have deployed it

    Wildfire monitoring using satellite images, ontologies and linked geospatial data

    Get PDF
    Advances in remote sensing technologies have allowed us to send an ever-increasing number of satellites in orbit around Earth. As a result, Earth Observation data archives have been constantly increasing in size in the last few years, and have become a valuable source of data for many scientific and application domains. When Earth Observation data is coupled with other data sources many pioneering applications can be developed. In this paper we show how Earth Observation data, ontologies, and linked geospatial data can be combined for the development of a wildfire monitoring service that goes beyond applications currently deployed in various Earth Observation data centers. The service has been developed in the context of European project TELEIOS that faces the challenges of extracting knowledge from Earth Observation data head-on, capturing this knowledge by semantic annotation encoded using Earth Observation ontologies, and combining these annotations with linked geospatial data to allow the development of interesting applications

    Polycystic Ovary Syndrome and Insulin Physiology: An Observational Quantitative Serum Proteomics Study in adolescent, Normal-Weight Females

    Get PDF
    Background: Polycystic ovary syndrome (PCOS) is a common endocrine disorder associated with insulin resistance, even in the absence of overweight/obesity. The aim of the present study is to examine the global serum proteomic profile of adolescent, normal‐weight females with PCOS in order to gain novel insight in the association of this endocrine disorder with insulin physiology and to identify novel circulating markers that can guide intervention protocols. Methods: Non‐depleted serum from normal‐weight (BMI: 18–23 kg m^(−2)), adolescent females (13–21 years old) with PCOS (n = 20) is compared to BMI‐ and age‐matched healthy controls (n = 20) using our 3D quantitative proteomics methodology. Serum samples from study participants are randomly pooled to form four biological replicates of females with PCOS and four of healthy controls (n = 5 per sample pool). Results: One‐hundred and twenty‐six proteins are differentially expressed in females with PCOS compared to controls. Gene ontology analysis shows significant enrichment for terms related to inflammatory immune response, metabolism and insulin‐like growth factor receptor signaling pathway. Circulating levels of IGF‐1 and ‐2 and IGFBP‐2, ‐3, and ‐4 are found to be lower in females with PCOS compared to healthy controls. Conclusions: The present serum proteomics study provides insight into the pro‐inflammatory status and insulin dysregulation in young females with PCOS and identifies potential serological markers that can guide early intervention protocols

    Polycystic Ovary Syndrome and Insulin Physiology: An Observational Quantitative Serum Proteomics Study in adolescent, Normal-Weight Females

    Get PDF
    Background: Polycystic ovary syndrome (PCOS) is a common endocrine disorder associated with insulin resistance, even in the absence of overweight/obesity. The aim of the present study is to examine the global serum proteomic profile of adolescent, normal‐weight females with PCOS in order to gain novel insight in the association of this endocrine disorder with insulin physiology and to identify novel circulating markers that can guide intervention protocols. Methods: Non‐depleted serum from normal‐weight (BMI: 18–23 kg m^(−2)), adolescent females (13–21 years old) with PCOS (n = 20) is compared to BMI‐ and age‐matched healthy controls (n = 20) using our 3D quantitative proteomics methodology. Serum samples from study participants are randomly pooled to form four biological replicates of females with PCOS and four of healthy controls (n = 5 per sample pool). Results: One‐hundred and twenty‐six proteins are differentially expressed in females with PCOS compared to controls. Gene ontology analysis shows significant enrichment for terms related to inflammatory immune response, metabolism and insulin‐like growth factor receptor signaling pathway. Circulating levels of IGF‐1 and ‐2 and IGFBP‐2, ‐3, and ‐4 are found to be lower in females with PCOS compared to healthy controls. Conclusions: The present serum proteomics study provides insight into the pro‐inflammatory status and insulin dysregulation in young females with PCOS and identifies potential serological markers that can guide early intervention protocols

    Improving knowledge discovery from synthetic aperture radar images using the linked open data cloud and Sextant

    Get PDF
    In the last few years, thanks to projects like TELEIOS, the linked open data cloud has been rapidly populated with geospatial data some of it describing Earth Observation products (e.g., CORINE Land Cover, Urban Atlas). The abundance of this data can prove very useful to the new missions (e.g., Sentinels) as a means to increase the usability of the millions of images and EO products that are expected to be produced by these missions. In this paper, we explain the relevant opportunities by demonstrating how the process of knowledge discovery from TerraSAR-X images can be improved using linked open data and Sextant, a tool for browsing and exploration of linked geospatial data, as well as the creation of thematic maps

    Wildfire monitoring via the integration of remote sensing with innovative information technologies

    Get PDF
    In the Institute for Space Applications and Remote Sensing of the National Observatory of Athens (ISARS/NOA) volumes of Earth Observation images of different spectral and spatial resolutions are being processed on a systematic basis to derive thematic products that cover a wide spectrum of applications during and after wildfire crisis, from fire detection and fire-front propagation monitoring, to damage assessment in the inflicted areas. The processed satellite imagery is combined with auxiliary geo-information layers, including land use/land cover, administrative boundaries, road and rail network, points of interest, and meteorological data to generate and validate added-value fire-related products. The service portfolio has become available to institutional End Users with a mandate to act on natural disasters and that have activated Emergency Support Services at a European level in the framework of the operational GMES projects SAFER and LinkER. Towards the goal of delivering integrated services for fire monitoring and management, ISARS/NOA employs observational capacities which include the operation of MSG/SEVIRI and NOAA/AVHRR receiving stations, NOA's in-situ monitoring networks for capturing meteorological parameters to generate weather forecasts, and datasets originating from the European Space Agency and third party satellite operators. The qualified operational activity of ISARS/NOA in the domain of wildfires management is highly enhanced by the integration of state-of-the-art Information Technologies that have become available in the framework of the TELEIOS (EC/ICT) project. TELEIOS aims at the development of fully automatic processing chains reliant on a) the effective storing and management of the large amount of EO and GIS data, b) the post-processing refinement of the fire products using semantics, and c) the creation of thematic maps and added-value services. The first objective is achieved with the use of advanced Array Database technologies, such as MonetDB, to enable efficiency in accessing large archives of image data and metadata in a fully transparent way, without worrying for their format, size, and location, as well as efficiency in processing such data using state-of-the-art implementations of image processing algorithms expressed in a high-level Scientific Query Language (SciQL). The product refinement is realized through the application of update operations that incorporate human evidence and human logic, with semantic content extracted from thematic information coming from auxiliary geo-information layers and sources, for reducing considerably the number of false alarms in fire detection, and improving the credibility of the burnt area assessment. The third objective is approached via the combination of the derived fire-products with Linked Geospatial Data, structured accordingly and freely available in the web, using Semantic Web technologies. These technologies are built on top of a robust and modular computational environment, to facilitate several wildfire applications to run efficiently, such as real-time fire detection, fire-front propagation monitoring, rapid burnt area mapping, after crisis detailed burnt scar mapping, and time series analysis of burnt areas. The approach adopted allows ISARS/NOA to routinely serve requests from the end-user community, irrespective of the area of interest and its extent, the observation time period, or the data volume involved, granting the opportunity to combine innovative IT solutions with remote sensing techniques and

    Operational Wildfire Monitoring and Disaster Management Support Using State-of-the-art EO and Information Technologies

    Get PDF
    Fires have been one of the main driving forces in the evolution of plants and ecosystems, determining the current structure and composition of the Landscapes. However, significant alterations in the fire regime have occurred in the recent decades, primarily as a result of socioeconomic changes, increasing dramatically the catastrophic impacts of wildfires as it is reflected in the increase during the 20th century of both, number of fires and the annual area burnt. Therefore, the establishment of a permanent robust fire monitoring system is of paramount importance to implement an effective environmental management policy. Such an integrated system has been developed in the Institute for Space Applications and Remote Sensing of the National Observatory of Athens (ISARS/NOA). Volumes of Earth Observation images of different spectral and spatial resolutions are being processed on a systematic basis to derive thematic products that cover a wide spectrum of applications during and after wildfire crisis, from fire detection and fire-front propagation monitoring, to damage assessment in the inflicted areas. The processed satellite imagery is combined with auxiliary geo-information layers and meteorological data to generate and validate added-value fire-related products. The service portfolio has become available to institutional End Users with a mandate to act on natural disasters in the framework of the operational GMES projects SAFER and LinkER addressing fire emergency response and emergency support needs for the entire European Union. Towards the goal of delivering integrated services for fire monitoring and management, ISARS/NOA employs observational capacities which include the operation of MSG/SEVIRI and NOAA/AVHRR receiving stations, NOA’s in-situ monitoring networks for capturing meteorological parameters to generate weather forecasts, and datasets originating from the European Space Agency and third party satellite operators. The qualified operational activity of ISARS/NOA in the domain of wildfires management is highly enhanced by the integra
    corecore