Redundancy analysis on linked data #cold2014 #ISWC2014
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Wu, Honghan, Boris Villazon-Terrazas, Jeff Z. Pan, and Jose Manuel Gomez-Perez. “How Redundant Is It? – An Empirical Analysis on Linked Datasets.” In ISWC COLD Workshop. 2014. http://ceur-ws.org/Vol-1264/cold2014_WuVPG.pdf
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IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.Design of a usb based data acquisition system
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
Performance bounds for unequally punctured
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
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IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.IVT Företagspresentation
Vi på IVT Center Hjelms Rör har marknadens bredaste sortiment. Hos oss hittar du bergvärmepumpar, jordvärmepumpar, sjövärmepumpar, grundvattenvärmepumpar, luft/vattenvärmepumpar, luft/luftvärmepumpar och solvärmelösningar för både villor och fastigheter.
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IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.Solentive / InRule AADI Gartner Summit 2014
InRule - The premier business rule management system for the Microsoft platform – empowers business and subject matter experts to take greater control over business rule management. We hope you enjoy it.
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IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.Road map of development for pull system in thailand small and medium automoti...
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IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and TechnologyGa based dynamic routing in wdm optical networks
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
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The document contains 3 briefs for different clients.
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Similar to Redundancy analysis on linked data #cold2014 #ISWC2014
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The web of interlinked data and knowledge stripped
Linked Data approaches can help solve enterprise information integration (EII) challenges by complementing text on web pages with structured, linked open data from different sources. This allows for intelligently combining, integrating, and joining structured information across heterogeneous systems. A distributed, iterative, bottom-up integration approach using Linked Data may help solve the EII problem in large companies by taking a pay-as-you-go approach.
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Efficient Query Answering against Dynamic RDF Databases
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Democratizing Big Semantic Data management
... or how to query an RDF graph with 28 billion triples in a standard laptop
These slides correspond to my talk at the Stanford Center for Biomedical Informatics, on 25th April 2018
Efficient Distributed In-Memory Processing of RDF Datasets - PhD Viva
Over the past decade, vast amounts of machine-readable structured information have become available through the automation of research processes as well as the increasing popularity of knowledge graphs and semantic technologies.
Today, we count more than 10,000 datasets made available online following Semantic Web standards.
A major and yet unsolved challenge that research faces today is to perform scalable analysis of large-scale knowledge graphs in order to facilitate applications in various domains including life sciences, publishing, and the internet of things.
The main objective of this thesis is to lay foundations for efficient algorithms performing analytics, i.e. exploration, quality assessment, and querying over semantic knowledge graphs at a scale that has not been possible before.
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Many applications such as data integration, search, and interlinking, may take full advantage of the data when having a priori statistical information about its internal structure and coverage.
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Based on the knowledge of the internal statistics of a dataset and its quality, users typically want to query and retrieve large amounts of information.
As a result, it has become difficult to efficiently process these large RDF datasets.
Indeed, these processes require, both efficient storage strategies and query-processing engines, to be able to scale in terms of data size.
Therefore, we propose a scalable approach to evaluate SPARQL queries over distributed RDF datasets by translating SPARQL queries into Spark executable code.
We conducted several empirical evaluations to assess the scalability, effectiveness, and efficiency of our proposed approaches.
More importantly, various use cases i.e. Ethereum analysis, Mining Big Data Logs, and Scalable Integration of POIs, have been developed and leverages by our approach.
The empirical evaluations and concrete applications provide evidence that our methodology and techniques proposed during this thesis help to effectively analyze and process large-scale RDF datasets.
All the proposed approaches during this thesis are integrated into the larger SANSA framework.
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‘Facilitating User Engagement by Enriching Library Data using Semantic Techno...
The ADAPT Centre is funded under the SFI Research Centres Programme and is co-funded under the European Regional Development Fund. The document discusses two demonstrators that were developed to facilitate user engagement with library data from Trinity College Dublin by enriching the data with semantic technologies. The first demonstrator was a mobile application that used linked library data and geospatial information. The second demonstrator interlinked the library metadata with a dataset of Irish churches using spatial relationships and functions defined in GeoSPARQL.
Sem facet paper
The document discusses faceted search over ontology-enhanced RDF data. It formalizes faceted interfaces for querying RDF graphs that capture ontological information. It studies the expressivity and complexity of queries represented by faceted interfaces, and algorithms for generating and updating interfaces based on the underlying RDF and ontology information. The goal is to provide rigorous theoretical foundations for faceted search in the context of RDF and OWL 2 ontologies.
SemFacet paper
Abstract:
An increasing number of applications rely on RDF, OWL 2, and SPARQL for storing and querying data. SPARQL, however, is not targeted towards end-users, and suitable query interfaces are needed. Faceted search is a prominent approach for end-user data access, and several RDF-based faceted search systems have been developed. There is, however, a lack of rigorous theoretical underpinning for faceted search in the context of RDF and OWL 2. In this paper, we provide such solid foundations. We formalise faceted interfaces for this context, identify a fragment of first-order logic capturing the underlying queries, and study the complexity of answering such queries for RDF and OWL 2 profiles. We then study interface generation and update, and devise efficiently implementable algorithms. Finally, we have implemented and tested our faceted search algorithms for scalability, with encouraging results.
Fedbench - A Benchmark Suite for Federated Semantic Data Processing
(1) FedBench is a benchmark suite for evaluating federated semantic data processing systems.
(2) It includes parameterized benchmark drivers, a variety of RDF datasets and SPARQL queries, and an evaluation framework to measure system performance.
(3) An initial evaluation was conducted to demonstrate FedBench's flexibility in comparing centralized and federated query processing using different systems and scenarios.
Data Integration at the Ontology Engineering Group
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Quantifying the bias in data links
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RDF4U: RDF Graph Visualization by Interpreting Linked Data as Knowledge
RDF4U: RDF Graph Visualization by Interpreting Linked Data as KnowledgeNational Institute of Informatics
Presented in : JIST2015, Yichang, China
Prototype: http://rc.lodac.nii.ac.jp/rdf4u/
Video: https://www.youtube.com/watch?v=z3roA9-Cp8g
Abstract: It is known that Semantic Web and Linked Open Data (LOD) are powerful technologies for knowledge management, and explicit knowledge is expected to be presented by RDF format (Resource Description Framework), but normal users are far from RDF due to technical skills required. As we learn, a concept-map or a node-link diagram can enhance the learning ability of learners from beginner to advanced user level, so RDF graph visualization can be a suitable tool for making users be familiar with Semantic technology. However, an RDF graph generated from the whole query result is not suitable for reading, because it is highly connected like a hairball and less organized. To make a graph presenting knowledge be more proper to read, this research introduces an approach to sparsify a graph using the combination of three main functions: graph simplification, triple ranking, and property selection. These functions are mostly initiated based on the interpretation of RDF data as knowledge units together with statistical analysis in order to deliver an easily-readable graph to users. A prototype is implemented to demonstrate the suitability and feasibility of the approach. It shows that the simple and flexible graph visualization is easy to read, and it creates the impression of users. In addition, the attractive tool helps to inspire users to realize the advantageous role of linked data in knowledge management.RDF4U: RDF Graph Visualization by Interpreting Linked Data as Knowledge
Presented in : JIST2015, Yichang, China
Prototype: http://rc.lodac.nii.ac.jp/rdf4u/
Video: https://www.youtube.com/watch?v=z3roA9-Cp8g
Abstract: It is known that Semantic Web and Linked Open Data (LOD) are powerful technologies for knowledge management, and explicit knowledge is expected to be presented by RDF format (Resource Description Framework), but normal users are far from RDF due to technical skills required. As we learn, a concept-map or a node-link diagram can enhance the learning ability of learners from beginner to advanced user level, so RDF graph visualization can be a suitable tool for making users be familiar with Semantic technology. However, an RDF graph generated from the whole query result is not suitable for reading, because it is highly connected like a hairball and less organized. To make a graph presenting knowledge be more proper to read, this research introduces an approach to sparsify a graph using the combination of three main functions: graph simplification, triple ranking, and property selection. These functions are mostly initiated based on the interpretation of RDF data as knowledge units together with statistical analysis in order to deliver an easily-readable graph to users. A prototype is implemented to demonstrate the suitability and feasibility of the approach. It shows that the simple and flexible graph visualization is easy to read, and it creates the impression of users. In addition, the attractive tool helps to inspire users to realize the advantageous role of linked data in knowledge management.
Timbuctoo 2 EASY
This document discusses Timbuctoo, an application designed for academic research that allows for complex and heterogeneous data. It explores archiving RDF datasets from Timbuctoo instances, including handling RDF graphs and triples, versioning datasets, and verifying dataset integrity and resolving links. A potential pipeline is proposed to ingest datasets from Timbuctoo into the EASY archive, but current Timbuctoo instances and datasets have obscure URIs and insufficient metadata, and the prototype pipeline lacks specifications. Archiving linked data from Timbuctoo could change the nature of preservation for archives.
RDF Stream Processing and the role of Semantics
This document discusses RDF stream processing and the role of semantics. It begins by outlining common sources of streaming data on the internet of things. It then discusses challenges of querying streaming data and existing approaches like CQL. Existing RDF stream processing systems are classified based on their query capabilities and use of time windows and reasoning. The role of linked data principles and HTTP URIs for representing streaming sensor data is discussed. Finally, requirements for reactive stream processing systems are outlined, including keeping data moving, integrating stored and streaming data, and responding instantaneously. The document argues that building relevant RDF stream processing systems requires going beyond existing requirements to address data heterogeneity, stream reasoning, and optimization.
Automatically converting tabular data to
Information residing in relational databases and delimited file systems are inadequate for reuse and sharing over the web. These file systems do not adhere to commonly set principles for maintaining data harmony. Due to these reasons, the resources have been suffering from lack of uniformity, heterogeneity as well as redundancy throughout the web. Ontologies have been widely used for solving such type of problems, as they help in extracting knowledge out of any information system. In this article, we focus on extracting concepts and their relations from a set of CSV files. These files are served as individual concepts and grouped into a particular domain, called the domain ontology. Furthermore, this domain ontology is used for capturing CSV data and represented in RDF format retaining links among files or concepts. Datatype and object properties are automatically detected from header fields. This reduces the task of user involvement in generating mapping files. The detail analysis has been performed on Baseball tabular data and the result shows a rich set of semantic information.
semantic web & natural language
a system called natural language interface which transforms user's natural language question into SPARQL query
find related papers here https://sites.google.com/site/fadhlinams81/publication
Reasoning with Big Knowledge Graphs: Choices, Pitfalls and Proven Recipes
This presentation will provide a brief introduction to logical reasoning and overview of the most popular semantic schema and ontology languages: RDFS and the profiles of OWL 2.
While automatic reasoning has always inspired the imagination, numerous projects have failed to deliver to the promises. The typical pitfalls related to ontologies and symbolic reasoning fall into two categories:
- Over-engineered ontologies. The selected ontology language and modeling patterns can be too expressive. This can make the results of inference hard to understand and verify, which in its turn makes KG hard to evolve and maintain. It can also impose performance penalties far greater than the benefits.
- Inappropriate reasoning support. There are many inference algorithms and implementation approaches, which work well with taxonomies and conceptual models of few thousands of concepts, but cannot cope with KG of millions of entities.
- Inappropriate data layer architecture. One such example is reasoning with virtual KG, which is often infeasible.
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Efficient Distributed In-Memory Processing of RDF Datasets - PhD Viva
Efficient Distributed In-Memory Processing of RDF Datasets - PhD Viva
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RDF4U: RDF Graph Visualization by Interpreting Linked Data as Knowledge
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- Step-by-step guide on deploying anomaly detection models on edge devices using ArgoCD.
5. Introduction to Apache Kafka and S3
- Explore Apache Kafka for real-time data streaming and Amazon S3 for scalable storage solutions.
6. Viewing Kafka Messages in the Data Lake
- Learn how to view and analyze Kafka messages stored in a data lake for better insights.
7. What is Prometheus?
- Get to know Prometheus, an open-source monitoring and alerting toolkit, and its application in monitoring edge devices.
8. Monitoring Application Metrics with Prometheus
- Detailed instructions on setting up Prometheus to monitor the performance and health of your anomaly detection system.
9. What is Camel K?
- Introduction to Camel K, a lightweight integration framework built on Apache Camel, designed for Kubernetes.
10. Configuring Camel K Integrations for Data Pipelines
- Learn how to configure Camel K for seamless data pipeline integrations in your anomaly detection workflow.
11. What is a Jupyter Notebook?
- Overview of Jupyter Notebooks, an open-source web application for creating and sharing documents with live code, equations, visualizations, and narrative text.
12. Jupyter Notebooks with Code Examples
- Hands-on examples and code snippets in Jupyter Notebooks to help you implement and test anomaly detection models.
TrustArc Webinar - 2024 Global Privacy Survey
How does your privacy program stack up against your peers? What challenges are privacy teams tackling and prioritizing in 2024?
In the fifth annual Global Privacy Benchmarks Survey, we asked over 1,800 global privacy professionals and business executives to share their perspectives on the current state of privacy inside and outside of their organizations. This year’s report focused on emerging areas of importance for privacy and compliance professionals, including considerations and implications of Artificial Intelligence (AI) technologies, building brand trust, and different approaches for achieving higher privacy competence scores.
See how organizational priorities and strategic approaches to data security and privacy are evolving around the globe.
This webinar will review:
- The top 10 privacy insights from the fifth annual Global Privacy Benchmarks Survey
- The top challenges for privacy leaders, practitioners, and organizations in 2024
- Key themes to consider in developing and maintaining your privacy program
HCL Notes and Domino License Cost Reduction in the World of DLAU
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-and-domino-license-cost-reduction-in-the-world-of-dlau/
The introduction of DLAU and the CCB & CCX licensing model caused quite a stir in the HCL community. As a Notes and Domino customer, you may have faced challenges with unexpected user counts and license costs. You probably have questions on how this new licensing approach works and how to benefit from it. Most importantly, you likely have budget constraints and want to save money where possible. Don’t worry, we can help with all of this!
We’ll show you how to fix common misconfigurations that cause higher-than-expected user counts, and how to identify accounts which you can deactivate to save money. There are also frequent patterns that can cause unnecessary cost, like using a person document instead of a mail-in for shared mailboxes. We’ll provide examples and solutions for those as well. And naturally we’ll explain the new licensing model.
Join HCL Ambassador Marc Thomas in this webinar with a special guest appearance from Franz Walder. It will give you the tools and know-how to stay on top of what is going on with Domino licensing. You will be able lower your cost through an optimized configuration and keep it low going forward.
These topics will be covered
- Reducing license cost by finding and fixing misconfigurations and superfluous accounts
- How do CCB and CCX licenses really work?
- Understanding the DLAU tool and how to best utilize it
- Tips for common problem areas, like team mailboxes, functional/test users, etc
- Practical examples and best practices to implement right away
June Patch Tuesday
Ivanti’s Patch Tuesday breakdown goes beyond patching your applications and brings you the intelligence and guidance needed to prioritize where to focus your attention first. Catch early analysis on our Ivanti blog, then join industry expert Chris Goettl for the Patch Tuesday Webinar Event. There we’ll do a deep dive into each of the bulletins and give guidance on the risks associated with the newly-identified vulnerabilities.
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAU
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-und-domino-lizenzkostenreduzierung-in-der-welt-von-dlau/
DLAU und die Lizenzen nach dem CCB- und CCX-Modell sind für viele in der HCL-Community seit letztem Jahr ein heißes Thema. Als Notes- oder Domino-Kunde haben Sie vielleicht mit unerwartet hohen Benutzerzahlen und Lizenzgebühren zu kämpfen. Sie fragen sich vielleicht, wie diese neue Art der Lizenzierung funktioniert und welchen Nutzen sie Ihnen bringt. Vor allem wollen Sie sicherlich Ihr Budget einhalten und Kosten sparen, wo immer möglich. Das verstehen wir und wir möchten Ihnen dabei helfen!
Wir erklären Ihnen, wie Sie häufige Konfigurationsprobleme lösen können, die dazu führen können, dass mehr Benutzer gezählt werden als nötig, und wie Sie überflüssige oder ungenutzte Konten identifizieren und entfernen können, um Geld zu sparen. Es gibt auch einige Ansätze, die zu unnötigen Ausgaben führen können, z. B. wenn ein Personendokument anstelle eines Mail-Ins für geteilte Mailboxen verwendet wird. Wir zeigen Ihnen solche Fälle und deren Lösungen. Und natürlich erklären wir Ihnen das neue Lizenzmodell.
Nehmen Sie an diesem Webinar teil, bei dem HCL-Ambassador Marc Thomas und Gastredner Franz Walder Ihnen diese neue Welt näherbringen. Es vermittelt Ihnen die Tools und das Know-how, um den Überblick zu bewahren. Sie werden in der Lage sein, Ihre Kosten durch eine optimierte Domino-Konfiguration zu reduzieren und auch in Zukunft gering zu halten.
Diese Themen werden behandelt
- Reduzierung der Lizenzkosten durch Auffinden und Beheben von Fehlkonfigurationen und überflüssigen Konten
- Wie funktionieren CCB- und CCX-Lizenzen wirklich?
- Verstehen des DLAU-Tools und wie man es am besten nutzt
- Tipps für häufige Problembereiche, wie z. B. Team-Postfächer, Funktions-/Testbenutzer usw.
- Praxisbeispiele und Best Practices zum sofortigen Umsetzen
A Comprehensive Guide to DeFi Development Services in 2024
DeFi represents a paradigm shift in the financial industry. Instead of relying on traditional, centralized institutions like banks, DeFi leverages blockchain technology to create a decentralized network of financial services. This means that financial transactions can occur directly between parties, without intermediaries, using smart contracts on platforms like Ethereum.
In 2024, we are witnessing an explosion of new DeFi projects and protocols, each pushing the boundaries of what’s possible in finance.
In summary, DeFi in 2024 is not just a trend; it’s a revolution that democratizes finance, enhances security and transparency, and fosters continuous innovation. As we proceed through this presentation, we'll explore the various components and services of DeFi in detail, shedding light on how they are transforming the financial landscape.
At Intelisync, we specialize in providing comprehensive DeFi development services tailored to meet the unique needs of our clients. From smart contract development to dApp creation and security audits, we ensure that your DeFi project is built with innovation, security, and scalability in mind. Trust Intelisync to guide you through the intricate landscape of decentralized finance and unlock the full potential of blockchain technology.
Ready to take your DeFi project to the next level? Partner with Intelisync for expert DeFi development services today!
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Redundancy analysis on linked data #cold2014 #ISWC2014
- 1. How redundant is it? – An empirical analysis on linked datasets Honghan Wu1, Boris Villazon-Terrazas2, Jeff Z. Pan1 and José Manuel Gómez Pérez2 University of Aberdeen1, UK iSOCO2 , Spain 20/10/2014 1
- 2. 2 Content • What is data redundancy with linked data? • Why is it of special interest to linked data consumption? • Linked Data redundancy categorisation • How to analysis? • Dataset selection & The Result • Conclusion
- 3. 3 What is the data redundancy in LD? • Data Redundancy – [Database systems] Same piece of data in multiple places – [Information theory] Wasted "space" used to transmit certain data • (In this work)Linked Data Redundancy – Wasted “space” to represent certain meaning (represented in certain semantics) – Duplication-free
- 4. 4 Why is it of special interest to LD consumption? • Bad Redundancy & Good Redundancy – Bad for exchange: storage, transmission – Good for inference computation • Relevant consumption tasks – Hosting/Sharing – Query Answering (SPARQL) – Ontology Based Data Access – Reasoning
- 5. Redundancy in Linked Data • Redundancy Categorisation for RDF Data • Redundancies caused by the “Linked” nature
- 6. 6 RDF Redundancies vs. Succinct Representations [Rule based] A. K. Joshi, P. Hitzler, and G. Dong. Logical linked data compression. In The Semantic Web: Semantics and Big Data, pages 170–184. Springer, 2013. [HDT]J. D. FernáNdez, M. A. MartíNez-Prieto, C. GutiéRrez, A. Polleres, and M. Arias. Binary rdf representation for publication and exchange (hdt). Web Semant., 19:22–41, Mar. 2013. [WaterFowl] O. Curé, G. Blin, D. Revuz, and D. C. Faye. Waterfowl: A compact, self-indexed and inference-enabled immutable rdf store. In The Semantic Web: Trends and Challenges, pages 302– 316. Springer, 2014. Pan, Jeff Z., Jose Manuel Gomez-Perez, Yuan Ren, Honghan Wu, Haofen Wang and Man Zhu. “Graph Pattern based RDF Data Compression”. In Proc. of 4th Joint International Semantic Technology Conference (JIST). 2014. (To appear)
- 7. 7 Semantic redundancy Rule Representation - DL Axioms (T-Box) - Other semantics (graph pattern substitution)
- 8. 8 Syntactic Redundancy Concise syntax - RDF abbreviation & striping syntax - Intra-structure & Inter- structure
- 9. 9 Symbolic Redundancy • http://xmlns.com/foaf/0.1/name – 31 bytes in ASCII URI ID (4 bytes) … … http://xmlns.com/foaf/0.1/name 128 … … Less bytes for basic data units - (Fix-length)Dictionary Based - (Variable-length) Huffman coding - Predictive encoding
- 10. 10 Semantic Redundancy Caused by “Linked” Nature • Vocabulary Linkage – Reuse of other vocabularies: more rules – Less redundancy ratio: more triples derivable – More redundancy: co-occurrence triples removable • Instance Linkage – sameAs linkages – Bring in new assertions (e.g., type assertions) – Bring in new axioms
- 11. How to analysis? • Two dimension analysis • Methodology • Metrics
- 12. 12 Two dimension analysis Semantic Syntactic Symbolic A-Box ✔ ✔ A-Box & T-Box No Linkage ✔ - - T-Box Reuse ✔ - - A-Box Linkage - - RDF Redundancy Dimension Linked Semantic Dimension
- 13. 13 Methodology: EDP Summarisation
- 14. 14 Virtually Materialised A-Box: expanded EDP A1, B1 (1) A2, B2 (1) A-Box: A1(o1) B1(o1) A2(o2) B2(o2) R(o1, o2) T-Box: A1⊆A, A2⊆A, B1⊆B, B2⊆B R (1:1) A, B, A, B,
- 15. Linked Dataset Analysis Results • Dataset Selection & Summary • Analysis Results
- 16. 16 Dataset Selection and Summary LOD 2011
- 17. 17 A-Box Only: Semantic Redundancies – Redundant Triples – Semantic redundancy ratio, i.e. – # Graph Patterns used to substitute redundant triples
- 18. 18 A-Box Only: Syntactic Redundancies – the redundant resource occurrences of inter-structural redundancies – the syntactic redundancy ratio, i.e.
- 19. 19 A-Box & T-Box: No Linkage DBLP2013: SWRC ontology Ordnance Survey: official published OS ontology 1.7% 184% 108% 4.7%
- 20. 20 A-Box & T-Box: No Linkage First 3 datasts are reusing FOAF Ontology – the number of directly used terms from reused T-Box – the number of applicable axioms from (materialised) reused T-Box 26.9% 4% 45.4% 1.3%
- 21. 21 Conclusion • LOD redundancy are heterogeneous & huge • Vocabulary linkage might lead to huge number of derivable triples • Redundancy aware techniques are demanded
- 22. 22 Redundancy-aware Consumption • Compression: different redundancies might need different techniques • For Data Access: (high inter-structure redundancy) skewed entity distributions over EDPs -> efficient access? • OBDA/Reasoning: A-Box redundancy = less T-Box axioms • Data Publisher: should be aware of the consequences of reusing
- 23. Thanks! Q & A