Although declarative data transformation functions defined in RML-FNML were implemented in KG materialization systems, they have not yet been studied or implemented in virtualknowledge graph systems. In this work we ...
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ISBN:
(纸本)9783031623615;9783031623622
Although declarative data transformation functions defined in RML-FNML were implemented in KG materialization systems, they have not yet been studied or implemented in virtualknowledge graph systems. In this work we propose to translate RML-FNML mapping to RML Views, which can be transparently used by virtualknowledge graph systems without modifying them. We implemented a research prototype of RML-FNML to RML Views unfolding and applied it to GTFS data to show the feasibility of the approach.
With the active development of ICT and Internet technologies in climate research, individuals often need to gather different and disparate datasets and preprocess them in preparation for downstream data analysis in or...
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ISBN:
(数字)9781665427920
ISBN:
(纸本)9781665427920
With the active development of ICT and Internet technologies in climate research, individuals often need to gather different and disparate datasets and preprocess them in preparation for downstream data analysis in order to have a more full understanding of the challenges. This preparatory procedure is often lengthy due to the primary issue that data providers cannot ensure a homogeneous data format for data integration purposes. To overcome this problem, this study proposes enhancing existing relational climate data by layering a virtualknowledge graph on top of the original databases provided by various data vendors. The primary benefit of doing this is that data consumers are able to simply integrate climate data with other data sources using Linked Data principles, and climate data producers do not have to modify their data to conform to standard knowledge graph protocols.
virtual knowledge graphs (VKGs) constitute one of the most promising paradigms for integrat-ing and accessing legacy data sources. A critical bottleneck in the integration process involves the definition, validation, ...
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virtual knowledge graphs (VKGs) constitute one of the most promising paradigms for integrat-ing and accessing legacy data sources. A critical bottleneck in the integration process involves the definition, validation, and maintenance of mapping assertions that link data sources to a domain ontology. To support the management of mappings throughout their entire lifecycle, we identify a comprehensive catalog of sophisticated mapping patterns that emerge when linking databases to ontologies. To do so, we build on well-established methodologies and patterns studied in data management, data analysis, and conceptual modeling. These are extended and refined through the analysis of concrete VKG benchmarks and real-world use cases, and considering the inherent impedance mismatch between data sources and ontologies. We validate our catalog on the considered VKG scenarios, showing that it covers the vast majority of mappings present therein.
Semantic web technologies are widely recognized for their utility in facilitating data integration tasks. While theoretical foundations have been extensively explored, few studies have displayed their practical implem...
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ISBN:
(数字)9783031627002
ISBN:
(纸本)9783031626999;9783031627002
Semantic web technologies are widely recognized for their utility in facilitating data integration tasks. While theoretical foundations have been extensively explored, few studies have displayed their practical implementation on real-world use cases and provided feedback on their scalability. This papers aims to address this gap by introducing a complete data integration framework tailored for Bimedia, a retail company. The framework is based on an integrated architecture of semantic layers and knowledgegraphs (KGs), aiming to enhance data interoperability and provide a deeper understanding of retail dynamics by unveiling hidden relationships captured by the data. We present empirical evaluations of various architectural implementations, supported by quantitative analyses, to guide industry practitioners in effective decision-making. Furthermore, the case study of Bimedia showcases the practical application of knowledgegraphs and semantic layers in the retail sector, bridging the gap between theory and practice. This study not only tackles Bimedia's specific challenges but also provides broader insights into the evolving landscape of retail technology.
The virtualknowledge Graph (VKG) paradigm facilitates access to large heterogeneous data sources by leveraging an OWL 2 QL ontology representing the domain knowledge and a set of declarative R2RML mapping assertions....
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ISBN:
(纸本)9783031724060;9783031724077
The virtualknowledge Graph (VKG) paradigm facilitates access to large heterogeneous data sources by leveraging an OWL 2 QL ontology representing the domain knowledge and a set of declarative R2RML mapping assertions. We are interested in heterogeneous data sources consisting of relational data together with spatial geometrical data (a.k.a. vector data) and large multidimensional raster data. The latter forms of data pose a significant challenge for traditional DBMSs to manage effectively and are instead efficiently processed by tailored array database management systems (ArrayDBMSs). To query such data within the VKG paradigm, we propose a novel framework, called ONTORASTER, that allows for integrated query processing of relational, raster, and vector data, by keeping each type of data in the system tailored for their efficient processing, while minimising costly data-transfer operations. In OntoRaster, we devised custom raster functions extending SPARQL to query raster data efficiently and developed mechanisms for delegating their computation to the ArrayDBMS. We have implemented the whole framework as an extension of the state-of-the-art VKG system Ontop and have demonstrated its effectiveness and efficiency through a curated case study.
Climate data is a valuable resource for understanding past weather patterns, assessing long-term climate trends, and conducting climate-related research. However, most existing knowledgegraphs for climate data rely h...
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ISBN:
(纸本)9798350320107
Climate data is a valuable resource for understanding past weather patterns, assessing long-term climate trends, and conducting climate-related research. However, most existing knowledgegraphs for climate data rely heavily on the standardized (per W3C recommendations) SOSA/SSN ontology, which can help improve general data accessibility, but typically overlooks the analytical applications of multisource climate data. To further enhance the accessibility of heterogeneous data for climate data analytics, this paper extends the CA ontology and implements a virtualknowledge graph for analytical applications. We emphasize the importance of incorporating observation metadata and geospatial representation into analytical applications. Through our study, we demonstrate the applicability of the proposed ontological model in deriving the ETCCDI indices. An example of the formation of the annual maximum daily temperature is given. Furthermore, we showcase the potential of LinkedGeoData in providing a more comprehensive geographical context for accessing climate data within the knowledge graph, leveraging the proposed ontological modeling and linked data principles.
Process mining is a family of techniques that support the analysis of operational processes based on event logs. Among the existing event log formats, the IEEE standard eXtensible Event Stream (XES) is the most widely...
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ISBN:
(纸本)9783031278143;9783031278150
Process mining is a family of techniques that support the analysis of operational processes based on event logs. Among the existing event log formats, the IEEE standard eXtensible Event Stream (XES) is the most widely adopted. In XES, each event must be related to a single case object, which may lead to convergence and divergence problems. To solve such issues, object-centric approaches become promising, where objects are the central notion and one event may refer to multiple objects. In particular, the Object-Centric Event Logs (OCEL) standard has been proposed recently. However, the crucial problem of extracting OCEL logs from external sources is still largely unexplored. In this paper, we try to fill this gap by leveraging the virtualknowledge Graph (VKG) approach to access data in relational databases. We have implemented this approach in the OnProm system, extending it to support both XES and OCEL standards. We have carried out an experiment with OnProm over the Dolibarr system. The evaluation results confirm that OnProm can effectively extract OCEL logs and the performance is scalable.
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