A First Step Towards a Streaming Linked Data Life-Cycle

Tommasini, Riccardo; Ragab, Mohamed; Falcetta, Alessandro; Valle, Emanuele Della; Sakr, Sherif

doi:10.1007/978-3-030-62466-8_39

Cited by 9 publications

(3 citation statements)

References 21 publications

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“…In the mid term, we would like to abstract RSP4J specification and provide access in other languages, e.g., Python. In the long-term, we would like to include abstraction to control the stream publication lifecycle [29]. Moreover, we would like to investigate how to combine RSP4J with other stream reasoning framework [6].…”

Section: Conclusion Discussion and Roadmapmentioning

confidence: 99%

RSP4J: An API for RDF Stream Processing

Tommasini

Bonte

Ongenae

et al. 2021

Lecture Notes in Computer Science

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The RDF Stream Processing (RSP) community has proposed several models and languages for continuously querying and reasoning over RDF streams over the last decade. They each have their semantics, making them hard to compare. The variety of approaches has fostered both empirical and theoretical research and led to the design of RSPQL, i.e., a unifying model for RSP. However, an RSP API for the development under RSPQL semantics was still missing. RSP community would benefit from an RSP API because it can foster comparable and reproducible research by providing programming abstractions based on RSPQL semantics. Moreover, it can encourage further development and in-use research. Finally, it can stimulate practical activities such as tutorials, lectures, and challenges, e.g., during the Stream Reasoning Workshop.In this paper, we present RSP4J, a flexible API for the development of RSP engines and applications under RSPQL semantics. RSP4J offers all the necessary abstractions required for fast-prototyping of RSP engines under the proposed RSPQL semantics. Users can configure it to reproduce the variety of RSP engine behaviors in a comparable software environment. To promote systematic and comparative research, RSP4J is open-source, provides canonical citation, permanent web identifiers, and a comprehensive user guide for developers.

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Section: Conclusion Discussion and Roadmapmentioning

confidence: 99%

RSP4J: An API for RDF Stream Processing

Tommasini

Bonte

Ongenae

et al. 2021

Lecture Notes in Computer Science

Self Cite

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“…There are numerous tasks and activities that are giving access to libraries over the web, some of which are utilizing the semantic web legitimately, and others in the background. Some significant ones include: The Open Archive Initiative [50], which gives direct access to organized metadata through its metadata reaping convention; the Simile Project, which utilizes the semantic web to upgrade between operability among computerized resources, schemata/vocabularies/ontologies, metadata, and administrations; and DELOS, a European Network of Excellence on Digital Libraries whose site gives a lot more connections to digital library ventures [45].…”

Section: Some Other Projectsmentioning

confidence: 99%

A Contemporary Review on Utilizing Semantic Web Technologies in Healthcare, Virtual Communities, and Ontology-Based Information Processing Systems

Narayanasamy

Srinivasan

et al. 2022

Electronics

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The semantic web is an emerging technology that helps to connect different users to create their content and also facilitates the way of representing information in a manner that can be made understandable for computers. As the world is heading towards the fourth industrial revolution, the implicit utilization of artificial-intelligence-enabled semantic web technologies paves the way for many real-time application developments. The fundamental building blocks for the overwhelming utilization of semantic web technologies are ontologies, and it allows sharing as well as reusing the concepts in a standardized way so that the data gathered from heterogeneous sources receive a common nomenclature, and it paves the way for disambiguating the duplicates very easily. In this context, the right utilization of ontology capabilities would further strengthen its presence in many web-based applications such as e-learning, virtual communities, social media sites, healthcare, agriculture, etc. In this paper, we have given the comprehensive review of using the semantic web in the domain of healthcare, some virtual communities, and other information retrieval projects. As the role of semantic web is becoming pervasive in many domains, the demand for the semantic web in healthcare, virtual communities, and information retrieval has been gaining huge momentum in recent years. To obtain the correct sense of the meaning of the words or terms given in the textual content, it is deemed necessary to apply the right ontology to fix the ambiguity and shun any deviations that persist on the concepts. In this review paper, we have highlighted all the necessary information for a good understanding of the semantic web and its ontological frameworks.

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“…The increasing adoption of Knowledge Graphs (KGs) in industry and academia requires scalable systems for taming linked data at large volumes and velocity [15,29,30]. In absence of a scalable native graph system for querying large (RDF) graphs [25], most approaches fall back to using relational Big Data (BD) frameworks (e.g., Apache Spark or Impala) for handling large graph query workloads [27,28].…”

Section: Introductionmentioning

confidence: 99%

PAPAYA: A library for performance analysis of SQL-based RDF processing systems

Ragab,

Adidarma,

Tommasini

2024

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Prescriptive Performance Analysis (PPA) has shown to be more useful than traditional descriptive and diagnostic analyses for making sense of Big Data (BD) frameworks’ performance. In practice, when processing large (RDF) graphs on top of relational BD systems, several design decisions emerge and cannot be decided automatically, e.g., the choice of the schema, the partitioning technique, and the storage formats. PPA, and in particular ranking functions, helps enable actionable insights on performance data, leading practitioners to an easier choice of the best way to deploy BD frameworks, especially for graph processing. However, the amount of experimental work required to implement PPA is still huge. In this paper, we present PAPAYA,11 https://github.com/DataSystemsGroupUT/PAPyA a library for implementing PPA that allows (1) preparing RDF graphs data for a processing pipeline over relational BD systems, (2) enables automatic ranking of the performance in a user-defined solution space of experimental dimensions; (3) allows user-defined flexible extensions in terms of systems to test and ranking methods. We showcase PAPAYA on a set of experiments based on the SparkSQL framework. PAPAYA simplifies the performance analytics of BD systems for processing large (RDF) graphs. We provide PAPAYA as a public open-source library under an MIT license that will be a catalyst for designing new research prescriptive analytical techniques for BD applications.

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A First Step Towards a Streaming Linked Data Life-Cycle

Cited by 9 publications

References 21 publications

RSP4J: An API for RDF Stream Processing

RSP4J: An API for RDF Stream Processing

A Contemporary Review on Utilizing Semantic Web Technologies in Healthcare, Virtual Communities, and Ontology-Based Information Processing Systems

PAPAYA: A library for performance analysis of SQL-based RDF processing systems

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