1,827 research outputs found

    Sextant: Visualizing time-evolving linked geospatial data

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    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

    Smart Environmental Data Infrastructures: Bridging the Gap between Earth Sciences and Citizens

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    The monitoring and forecasting of environmental conditions is a task to which much effort and resources are devoted by the scientific community and relevant authorities. Representative examples arise in meteorology, oceanography, and environmental engineering. As a consequence, high volumes of data are generated, which include data generated by earth observation systems and different kinds of models. Specific data models, formats, vocabularies and data access infrastructures have been developed and are currently being used by the scientific community. Due to this, discovering, accessing and analyzing environmental datasets requires very specific skills, which is an important barrier for their reuse in many other application domains. This paper reviews earth science data representation and access standards and technologies, and identifies the main challenges to overcome in order to enable their integration in semantic open data infrastructures. This would allow non-scientific information technology practitioners to devise new end-user solutions for citizen problems in new application domainsThis research was co-funded by (i) the TRAFAIR project (2017-EU-IA-0167), co-financed by the Connecting Europe Facility of the European Union, (ii) the RADAR-ON-RAIA project (0461_RADAR_ON_RAIA_1_E) co-financed by the European Regional Development Fund (ERDF) through the Iterreg V-A Spain-Portugal program (POCTEP) 2014-2020, and (iii) the Consellería de Educación, Universidade e Formación Profesional of the regional government of Galicia (Spain), through the support for research groups with growth potential (ED431B 2018/28)S

    K-Space at TRECVID 2008

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    In this paper we describe K-Space’s participation in TRECVid 2008 in the interactive search task. For 2008 the K-Space group performed one of the largest interactive video information retrieval experiments conducted in a laboratory setting. We had three institutions participating in a multi-site multi-system experiment. In total 36 users participated, 12 each from Dublin City University (DCU, Ireland), University of Glasgow (GU, Scotland) and Centrum Wiskunde and Informatica (CWI, the Netherlands). Three user interfaces were developed, two from DCU which were also used in 2007 as well as an interface from GU. All interfaces leveraged the same search service. Using a latin squares arrangement, each user conducted 12 topics, leading in total to 6 runs per site, 18 in total. We officially submitted for evaluation 3 of these runs to NIST with an additional expert run using a 4th system. Our submitted runs performed around the median. In this paper we will present an overview of the search system utilized, the experimental setup and a preliminary analysis of our results

    K-Space at TRECVid 2008

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    In this paper we describe K-Space’s participation in TRECVid 2008 in the interactive search task. For 2008 the K-Space group performed one of the largest interactive video information retrieval experiments conducted in a laboratory setting. We had three institutions participating in a multi-site multi-system experiment. In total 36 users participated, 12 each from Dublin City University (DCU, Ireland), University of Glasgow (GU, Scotland) and Centrum Wiskunde & Informatica (CWI, the Netherlands). Three user interfaces were developed, two from DCU which were also used in 2007 as well as an interface from GU. All interfaces leveraged the same search service. Using a latin squares arrangement, each user conducted 12 topics, leading in total to 6 runs per site, 18 in total. We officially submitted for evaluation 3 of these runs to NIST with an additional expert run using a 4th system. Our submitted runs performed around the median. In this paper we will present an overview of the search system utilized, the experimental setup and a preliminary analysis of our results

    Archaeological data management and analysis at Blandwood mansion.

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    This thesis involves the creation, organization, and analysis of digital archaeological data within a site Geographic Information System and Microsoft Access relational database. The data were the result of excavations at the Blandwood Mansion property in downtown Greensboro, NC, during the summer of 2008. The creation and implementation of the site GIS and custom relational database were discussed with a focus placed on increasing the efficiency of data storage and the speed at which data can be analyzed. The archaeological database was developed for the project and its creation and purpose were discussed with reference to the user experience. The specific methods of data analysis performed within the study include artifact dating via mean ceramic dating, equation based flat window glass dating, artifact distribution analysis using density mapping, and 3D soil layer modeling using statistical kriging. A number of other historical resources including Sanborn Fire Insurance maps and photos were integrated into the GIS to better understand the results obtained by the methods stated above. The final chapter briefly discusses some key insights provided by the study and recommendations of future archaeological exploration within the site

    Ontology of core concept data types for answering geo-analytical questions

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    In geographic information systems (GIS), analysts answer questions by designing workflows that transform a certain type of data into a certain type of goal. Semantic data types help constrain the application of computational methods to those that are meaningful for such a goal. This prevents pointless computations and helps analysts design effective workflows. Yet, to date it remains unclear which types would be needed in order to ease geo-analytical tasks. The data types and formats used in GIS still allow for huge amounts of syntactically possible but nonsensical method applications. Core concepts of spatial information and related geo-semantic distinctions have been proposed as abstractions to help analysts formulate analytic questions and to compute appropriate answers over geodata of different formats. In essence, core concepts reflect particular interpretations of data which imply that certain transformations are possible. However, core concepts usually remain implicit when operating on geodata, since a concept can be represented in a variety of forms. A central question therefore is: Which semantic types would be needed to capture this variety and its implications for geospatial analysis? In this article, we propose an ontology design pattern of core concept data types that help answer geo-analytical questions. Based on a scenario to compute a liveability atlas for Amsterdam, we show that diverse kinds of geo-analytical questions can be answered by this pattern in terms of valid, automatically constructible GIS workflows using standard sources

    Building Complex and Site Categorization Using Similarity to a Prototypical Site

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    This project presents an assessment tool for classifying building complexes using sitebased relationships as calculated from ArcGIS 9.2 using model builder and Python scripting. Anthropogenic features extracted from imagery often form the foundation of spatial databases. These data are in turn used to inform situational awareness for relief, law enforcement, and military agencies among many others. Buildings and the complexes they form are critical features within the landscape. The categorization of complexes requires an understanding of the relationships of the buildings within the site. In this study, building complexes in California were assessed for similarity to a prototypical California high school defined with a training set of known high schools and compared to a set of uncategorized sites. Eighty-eight percent of the high schools were correctly classified as being highly similar to the control data set
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