A Holistic, Semantics-aware Approach to Spatial Data Infrastructures

Fugazza, Cristiano; Pepe, Monica; Oggioni, Alessandro; Pavesi, Fabio; Carrara, Paola

doi:10.5220/0004997603490356

Cited by 6 publications

(4 citation statements)

References 6 publications

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“…This study uses Resource Description Framework (RDF) repositories applied to the SDI context to support the discussion. Based on an ontology, Janowicz et al [40] and Fugazza et al [41] investigated how to incorporate semantic information into SDI search engines to improve data retrieval. Henriques [42] defined a method of automatic semantic annotation of geographical data based on open data for information recovery in SDI.…”

Section: Semantic Sdi and Semantic Annotationmentioning

confidence: 99%

Towards the Semantic Enrichment of Trajectories Using Spatial Data Infrastructures

Vidal-Filho

Times

Filho

et al. 2021

IJGI

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The term Semantic Trajectories of Moving Objects (STMO) corresponds to a sequence of spatial-temporal points with associated semantic information (for example, annotations about locations visited by the user or types of transportation used). However, the growth of Big Data generated by users, such as data produced by social networks or collected by an electronic equipment with embedded sensors, causes the STMO to require services and standards for enabling data documentation and ensuring the quality of STMOs. Spatial Data Infrastructures (SDI), on the other hand, provide a shared interoperable and integrated environment for data documentation. The main challenge is how to lead traditional SDIs to evolve to an STMO document due to the lack of specific metadata standards and services for semantic annotation. This paper presents a new concept of SDI for STMO, named SDI4Trajectory, which supports the documentation of different types of STMO—holistic trajectories, for example. The SDI4Trajectory allows us to propose semi-automatic and manual semantic enrichment processes, which are efficient in supporting semantic annotations and STMO documentation as well. These processes are hardly found in traditional SDIs and have been developed through Web and semantic micro-services. To validate the SDI4Trajectory, we used a dataset collected by voluntary users through the MyTracks application for the following purposes: (i) comparing the semi-automatic and manual semantic enrichment processes in the SDI4Trajectory; (ii) investigating the viability of the documentation processes carried out by the SDI4Trajectory, which was able to document all the collected trajectories.

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Section: Semantic Sdi and Semantic Annotationmentioning

confidence: 99%

Towards the Semantic Enrichment of Trajectories Using Spatial Data Infrastructures

Vidal-Filho

Times

Filho

et al. 2021

IJGI

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“…Standard interoperable Web sharing of geodata can be conceived at two distinct levels. Firstly, at the semantic level, using the standard metadata formats, such as INSPIRE and its Italian extension RNDT, enriched with thesauri and ontologies, have been proposed to enable the discovery of geodata (Fugazza et al, 2014). As far as time series of geodata values (i.e., sequence of data values ordered in time with a common georeference) is concerned, an OGC standard exchange data In the following, we describe the technologies adopted for interoperable sharing of DInSAR measurements targeting experts and non-experts.…”

Section: Basic Notions Of Web Service Interoperabilitymentioning

confidence: 99%

Visualization of Big Geodata: An Experiment With Dinsar Deformation Time Series

Kilsedar¹,

Frigerio²,

Bonano³

et al. 2019

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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<p><strong>Abstract.</strong> This paper describes an experiment carried out within the project “URBAN GEOmatics for Bulk data Generation, Data Assessment and Technology Awareness (URBAN GEO BIG DATA)” on novel technological solutions for encouraging the use of time series of big geodata by scientists, public administrators, and the citizens of urban areas. In this experiment, we focus on fostering the use of ground deformation time series derived through the Differential Synthetic Aperture Radar Interferometry (DInSAR) measurements in urban areas (i.e., Naples, Milan, and Turin) through visualization. Two visualization applications are developed within the project. First, mean deformation velocity maps are visualized; second, the cumulative deformation time series is animated to enable the comprehension of deformation of eighteen years at a glance. The experiment allows experts and non-experts to discover spatio-temporal patterns of deformation. The paper focuses on the characteristics and implementation details of this experiment. Both visualizations are overlaid on a three-dimensional map, i.e., a virtual globe. We use open standards and free and open source software (FOSS) for Web to enable interoperability, replicability, and reusability.</p>

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“…Also, the service-based deployment strategy allows users to retain full control on the data structures that are produced. Further details on EDI's role can be found in [1,3] EDI's main goals are depicted in Figure 1 and listed here: EDI was developed as part of sub-project 7 (http:// www.ritmare.it/en/articolazione/sottoprogetto-7.html) of the Italian Flagship Project RITMARE (http://www.ritmare.it/).…”

Section: Introductionmentioning

confidence: 99%

EDI – A Template-Driven Metadata Editor for Research Data

Pavesi

Basoni

Fugazza

et al. 2016

JORS

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EDI is a general purpose, template-driven metadata editor for creating XML-based descriptions. Originally aimed at defining rich and standard metadata for geospatial resources, It can be easily customised in order to comply with a broad range of schemata and domains. EDI creates HTML5 [9] metadata forms with advanced assisted editing capabilities and compiles them into XML files. The examples included in the distribution implement profiles of the ISO 19139 standard for geographic information [14], such as core INSPIRE metadata [10], as well as the OGC [8] standard for sensor description, SensorML [11]. Templates (the blueprints for a specific metadata format) drive form behaviour by element data types and provide advanced features like codelists 1 underlying combo boxes or autocompletion functionalities. Virtually, the editing of any metadata format can be supported by creating a specific template.

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A Holistic, Semantics-aware Approach to Spatial Data Infrastructures

Cited by 6 publications

References 6 publications

Towards the Semantic Enrichment of Trajectories Using Spatial Data Infrastructures

Towards the Semantic Enrichment of Trajectories Using Spatial Data Infrastructures

Visualization of Big Geodata: An Experiment With Dinsar Deformation Time Series

EDI – A Template-Driven Metadata Editor for Research Data

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