Integrating Streaming Data into Semantic Mashups

Tjoa, A. Min; Wetz, Peter; Kiesling, Elmar; Trinh, Tuan-Dat; Do, Ba-Lam

doi:10.1016/j.procs.2015.12.098

Cited by 3 publications

(3 citation statements)

References 7 publications

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“…Purss et al [64] proposed a novel OGC standard in the form of discrete global grid system to offer a homogeneous medium for integration and visualization of vector geometry and raster-based geospatial data sources in a similar manner to the conversion of information in a computer graphics workflow to computer screen pixels. The construct of linked widgets for streaming the data domain is expanded in [65] to facilitate the creation of mashups on the linked widgets platform in real time. The underlying principle of this construct is the representation of the entire data processing workflow and the provision of user assistance in developing semantic data streams and end-user mashups as well as the visualization of processed data flows to obtain knowledge in real time.…”

Section: ) Semantic Integration A: Linked Datamentioning

confidence: 99%

Review on Integrating Geospatial Big Datasets and Open Research Issues

et al. 2021

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Big data and geographic information systems (GIS) are two technologies that have increasingly influenced many areas in the last 10 years and will continue to improve and help solve serious global problems, such as consequences of climate change or global pandemics. A wide spectrum of GIS applications interacts with the continuous growth of geospatial big data sources to drive precise and informed decisions. Geospatial big data integration is designed to accomplish the compatibility of distinct geospatial datasets regardless of their spatial coverage. The large number of geospatial big data sources demand effective data integration for storing and handling such datasets, which will be used for geospatial data analysis and visualization. For instance, risk management datasets related to healthcare and the environment are heterogeneous and disparate. Obtaining a unified view of such geospatial big datasets is complicated and challenging, especially if we consider problems related to healthcare pandemics and environmental disasters. Hence, before we can attempt to predict and mitigate processes occurring in these domains, we must realize that geospatial big data integration is crucial in consolidating datasets. We explore and discuss issues involved in integrating geospatial big datasets in this study. We then classify big data integration processes into three categories, namely, data warehousing, data transformation and integration methods. Furthermore, several research challenges focused on geospatial big data, big earth data, data warehousing, data transformation and linked data are presented. Lastly, open research issues and emerging trends that require in-depth investigations in the near future are highlighted in this study.INDEX TERMS Big data integration, geographic information system (GIS), geospatial big data.

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Section: ) Semantic Integration A: Linked Datamentioning

confidence: 99%

Review on Integrating Geospatial Big Datasets and Open Research Issues

et al. 2021

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“…Developers can develop RML mapping for the target data sources using RMLx front-end (RMLx Editor) with the assistance of vocabularies from LOV 4 . As an output, users can directy acquire data as RDF or as a data widget -that can be exported from RDFx Editor-in the Linked Widget Platform (LWP 5 ).…”

Section: Rmlx System Architecturementioning

confidence: 99%

“…In the case of Linked Streaming Widgets [4], which represent an extension of the Linked Widgets Platform [5], we use RMLx to create streaming RDF data. The lack of ready to use RDF streams on the web created the need to have a means for generating data which can be used as streaming data to feed RDF Stream Processing engines.…”

Section: A Linked Streaming Widgetsmentioning

confidence: 99%

RMLx: Mapping interface for integrating open data with linked data exploration environment

Aryan

Ekaputra

Kiesling

et al. 2017

2017 1st International Conference on Informatics and Computational Sciences (ICICoS)

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Abstract-Recent advances in linked data generation through mapping such as RML (RDF mapping language) allows for providing large-scale RDF data in a more automatic way. However, considerable amount of data in open data portals remain inaccessible as linked data. This is due to the nature of data portals having large number of small-size dataset which makes writing mapping description becomes tedious and error-prone. Moreover, these data sources requires additional preprocessing before To solve this challenge, We introduce extensions to RML to support required tasks and developed RMLx, a visual webinterface to create RML mappings. Using this interface, the process of creating mapping description can become faster and less error-prone. Furthermore, the process of linked data generation can be wrapped as to enable integration with other data in a linked data exploration environment. We explore on four different use cases to identify the requirements followed by describing how these are solved.

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Integrating Heterogeneous Services for Semantic Mashup Construction

Bencherif

Bensaber²,

Malki³

2018

Advances in Computer and Electrical Engineering

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Semantic mashup applications allow automating the process of services and data integration to create a composite application with a new user interface. Nevertheless, existing mashup applications need to improve the matching methods for discovering semantic services. Moreover, they have to create or modify workflows in mashup applications without the assistance of the original developers. Automating the combination of user interfaces is another challenge in the context of semantic mashups construction. In this chapter, the authors propose an approach that allows automating the combination of data, services, and user interfaces to provide a composite application with an enhanced user interface. The construction of the semantic mashup application is based on the use of domain ontology, a matching tool, and a collection of patterns. In order to demonstrate the effectiveness of this proposal, the authors present a use case to construct a semantic mashup application for a travel agency.

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Integrating Streaming Data into Semantic Mashups

Cited by 3 publications

References 7 publications

Review on Integrating Geospatial Big Datasets and Open Research Issues

Review on Integrating Geospatial Big Datasets and Open Research Issues

RMLx: Mapping interface for integrating open data with linked data exploration environment

Integrating Heterogeneous Services for Semantic Mashup Construction

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