GeoEtypes: Harmonizing Diversity in Geospatial Data (Short Paper)

Das, Subhashis; Giunchiglia, Fausto

doi:10.1007/978-3-319-48472-3_38

Cited by 5 publications

(4 citation statements)

References 8 publications

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“…The development of merging methodologies, scales, and heterogeneity in remotesensing data allows data fusion on a global scale [48]. At the European level, harmonization models have been developed for geospatial data to be made compatible with the European INSPIRE Directive [49]. More specialized models for soil data have been developed for harmonization at both the global [50,51] and European scales [52,53].…”

Section: Data Harmonizationmentioning

confidence: 99%

Challenges in the Geo-Processing of Big Soil Spatial Data

Liakos

Panagos

2022

Land

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This study addressed a critical resource—soil—through the prism of processing big data at the continental scale. Rapid progress in technology and remote sensing has majorly improved data processing on extensive spatial and temporal scales. Here, the manuscript presents the results of a systematic effort to geo-process and analyze soil-relevant data. In addition, the main highlights include the difficulties associated with using data infrastructures, managing big geospatial data, decentralizing operations through remote access, mass processing, and automating the data-processing workflow using advanced programming languages. Challenges to this study included the reproducibility of the results, their presentation in a communicative way, and the harmonization of complex heterogeneous data in space and time based on high standards of accuracy. Accuracy was especially important as the results needed to be identical at all spatial scales (from point counts to aggregated countrywide data). The geospatial modeling of soil requires analysis at multiple spatial scales, from the pixel level, through multiple territorial units (national or regional), and river catchments, to the global scale. Advanced mapping methods (e.g., zonal statistics, map algebra, choropleth maps, and proportional symbols) were used to convey comprehensive and substantial information that would be of use to policymakers. More specifically, a variety of cartographic practices were employed, including vector and raster visualization and hexagon grid maps at the global or European scale and in several cartographic projections. The information was rendered in both grid format and as aggregated statistics per polygon (zonal statistics), combined with diagrams and an advanced graphical interface. The uncertainty was estimated and the results were validated in order to present the outputs in the most robust way. The study was also interdisciplinary in nature, requiring large-scale datasets to be integrated from different scientific domains, such as soil science, geography, hydrology, chemistry, climate change, and agriculture.

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Section: Data Harmonizationmentioning

confidence: 99%

Challenges in the Geo-Processing of Big Soil Spatial Data

Liakos

Panagos

2022

Land

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“…This leads to the generation of a flexible entity graph which allows the user to query different types of content with various level of detail or to look for very specific information. The knowledge layer explicitly separates schema, vocabulary, and entity [11] which tackles the language based diversity.…”

Section: A Knowledge Layermentioning

confidence: 99%

SemUI: A Knowledge Driven Visualization of Diversified Data

Giunchiglia

Ojha

Das

2017

2017 IEEE 11th International Conference on Semantic Computing (ICSC)

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The intrinsic diversity in Open Data affects its intuitiveness and acceptance from the end users' perspective. Existing tools lack efficient and effective mechanisms for handling diversified data, both in terms of content and presentation. Furthermore, users face difficulties in managing a large variety of data on their own. Thus, a standard methodology for data modeling, presentation and interaction is imperative in order to ease access and manage Open Data. We propose a solution and a tool named SemUI based on an integrated multi-tiered approach where: 1) a semantic layer integrates the data using the notion of real world entity and categorizes them according to their similarities and differences and, 2) a visualization layer which simultaneously shows multiple views based on the different properties of entities. Our evaluation result shows the feasibility of our approach by successfully accommodating the diversity in the data and thus providing a positive experience to the end users.

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“…We preserve this type of semantic relations in our model which facilitates easy inference of the model. We categorize all the man made a structure like a busStation, railwayStartion, airport etc under the class transportationBuilding [2]. Moreover, to make our model comprehensible with more datasets, we gave major attention to not to use conflicting terms such as 'subways', 'underground' and 'tube'.…”

Section: Atommentioning

confidence: 99%

ATOM: Ontology Aware Transportation Model

Das

Ojha

Giunchiglia

2017

2017 IEEE 11th International Conference on Semantic Computing (ICSC)

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The freely available transportation data in different Open Data portals contains both spatially and temporally related features. However, the data providers publish this data following a different set of standards, use numerous formats, language, and schema. These variations create complication while integrating multiple datasets into one place to create knowledge. This further creates a hindrance to cater the need of a wider set of audience for the decision-making process. In this paper, we propose ATOM, an ontology based schema for diversified transportation data which is flexible for data integration and is aligned with an upper-level ontology.

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GeoEtypes: Harmonizing Diversity in Geospatial Data (Short Paper)

Cited by 5 publications

References 8 publications

Challenges in the Geo-Processing of Big Soil Spatial Data

Challenges in the Geo-Processing of Big Soil Spatial Data

SemUI: A Knowledge Driven Visualization of Diversified Data

ATOM: Ontology Aware Transportation Model

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