The document discusses contextualized knowledge graphs from the perspectives of semantic web and graph databases. It describes different models for representing facts and associated metadata in RDF, including reification, singleton properties, PaCE, and named graphs. Experiments show that the singleton property model provides the most compact representation and reasonable query performance. The document also discusses using a contextualized knowledge graph to represent chemical similarity data from PubChem in a more scalable way than the current approach.
Don’t like RDF Reification? Making Statements about Statements Using Singleto...Vinh Nguyen
Statements about RDF statements, or meta triples, provide additional information about individual triples, such as the source, the occuring time or place, or the certainty. Integrating such meta triples into semantic knowledge bases would enable the querying and reasoning mechanisms to be aware of provenance, time, location, or certainty of triples. How- ever, an efficient RDF representation for such meta knowledge of triples remains challenging. The existing reification approach allows such meta knowledge of RDF triples to be expressed using RDF by two steps. The first step is representing the triple by a Statement instance which has subject, predicate, and object indicated separately in three different triples. The second step is creating assertions about that instance as if it is a statement. While reification is simple and intuitive, this approach does not have formal semantics and is not commonly used in practice as described in the RDF Primer.
In this paper, we propose a novel approach called Singleton Property for representing meta triples and provide a for- mal semantics for it. We explain how this singleton property approach fits well with the existing syntax and formal semantics of RDF, and the syntax of SPARQL query lan- guage. We also demonstrate the use of singleton property in the representation and querying of meta knowledge in two examples of Semantic Web knowledge bases: YAGO2 and BKR. This approach, which is also simple and intuitive, can be easily adopted for representing and querying statements about statements in other knowledge bases.
KnowledgeWiki: An OpenSource Tool for Creating Community-Curated Vocabulary, ...Nishita Jaykumar
Resource Description Framework (RDF) datasets can be
created by transforming structured databases, extracting
the triples from semi-structured and unstructured sources,
crowd-sourcing, or by integrating the existing datasets. The
reliability and quality of these datasets can be improved by
the participation of domain experts via a special purpose
tool or a crowd-sourced application. Wikidata and Semantic
MediaWiki are platforms which facilitate this kind of
crowd-sourced data curation.
We present our system, KnowledgeWiki, which is built
upon the existing Semantic MediaWiki. We develop a novel
extension by adopting the singleton property data model in
our KnowledgeWiki. This extension allows various kinds of
metadata about the RDF triples to be created in the Wiki.
We combine this extension with other extensions such as se-
mantic forms to provide a user-friendly, Wiki-like interface
for domain experts with no prior technical expertise to easily
curate data. We also present our new enhancement to Semantic
Mediawiki, which facilitates importing existing RDF
datasets into the wiki-based curating platform based on the
singleton property approach, that preserves the provenance
of individual triples. We also describe how it is being used
by the materials science community to create and curate
consolidated vocabularies.
Semantic Web technologies such as RDF and OWL have become World Wide Web Consortium (W3C) standards for knowledge representation and reasoning. RDF triples about triples, or meta triples, form the basis for a contextualized knowledge graph. They represent the contextual information about individual triples such as the source, the occurring time or place, or the certainty.
However, an efficient RDF representation for such meta-knowledge of triples remains a major limitation of the RDF data model. The existing reification approach allows such meta-knowledge of RDF triples to be expressed in RDF by using four triples per reified triple. While reification is simple and intuitive, this approach does not have a formal foundation and is not commonly used in practice as described in the RDF Primer.
This dissertation presents the foundations for representing, querying, reasoning and traversing the contextualized knowledge graphs (CKG) using Semantic Web technologies.
A triple-based compact representation for CKGs. We propose a principled approach and construct RDF triples about triples by extending the current RDF data model with a new concept, called singleton property (SP), as a triple identifier. The SP representation needs two triples to the RDF datasets and can be queried with SPARQL.
A formal model-theoretic semantics for CKGs. We formalize the semantics of the singleton property and its relationships with the triple it represents. We extend the current RDF model-theoretic semantics to capture the semantics of the singleton properties and provide the interpretation at three levels: simple, RDF, and RDFS. It provides a single interpretation of the singleton property semantics across applications and systems.
A sound and complete inference mechanism for CKGs. Based on the semantics we propose, we develop a set of inference rules for validating and inferring new triples based on the SP syntax. We also develop different sets of context-based inference rules for provenance, time, and uncertainty.
A graph-based formalism for CKGs. We propose a formal contextualized graph model for the SP representation. We formalize the RDF triples as a mathematical graph by combining the model theory and the graph theory into a hybrid RDF formal semantics. The unified semantics allows the RDF formal semantics to be leveraged in the graph-based algorithms.
Data Provenance and its role in Data SciencePaolo Missier
Invited talk at the April 18th-20th Data Science workshop in Islamabad, Pakistan
How provenance may help Data Science. State of the art and open challenges
Learning Multilingual Semantics from Big Data on the WebGerard de Melo
This document summarizes Gerard de Melo's presentation on learning multilingual semantics from big data on the web. It discusses how lexical and taxonomic knowledge can be extracted at large scale from online resources like Wiktionary, Wikipedia, and WordNet. Methods are presented for merging structured data like knowledge graphs and integrating taxonomies across languages using techniques like linear program relaxation and belief propagation. The goal is to build large yet reasonably clean multilingual knowledge bases to power applications in areas like semantic search and the digital humanities.
The document discusses improving information retrieval by structuring data in records, mapping data to common standards like CRM, and publishing as RDF. This would allow linking data across systems, more comprehensive searches, and more representative conclusions by processing more data. Key recommendations include using existing databases, structuring records without free text, mapping to CRM, and publishing as RDF.
Knowledge extraction in Web media: at the frontier of NLP, Machine Learning a...Julien PLU
Julien Plu defended his PhD thesis on knowledge extraction from web media. His research addressed three main challenges: 1) extracting entities from different types of texts and languages, 2) linking entities to multiple knowledge bases, and 3) adapting entity linking pipelines for different contexts. To extract entities, he evaluated various natural language processing techniques including phrase matching, sequence labeling using neural networks, and coreference resolution. He found that combining multiple named entity recognition models improved performance over using a single model. Plu's research provided methods for extracting and linking entities from diverse textual sources in an adaptable manner.
Don’t like RDF Reification? Making Statements about Statements Using Singleto...Vinh Nguyen
Statements about RDF statements, or meta triples, provide additional information about individual triples, such as the source, the occuring time or place, or the certainty. Integrating such meta triples into semantic knowledge bases would enable the querying and reasoning mechanisms to be aware of provenance, time, location, or certainty of triples. How- ever, an efficient RDF representation for such meta knowledge of triples remains challenging. The existing reification approach allows such meta knowledge of RDF triples to be expressed using RDF by two steps. The first step is representing the triple by a Statement instance which has subject, predicate, and object indicated separately in three different triples. The second step is creating assertions about that instance as if it is a statement. While reification is simple and intuitive, this approach does not have formal semantics and is not commonly used in practice as described in the RDF Primer.
In this paper, we propose a novel approach called Singleton Property for representing meta triples and provide a for- mal semantics for it. We explain how this singleton property approach fits well with the existing syntax and formal semantics of RDF, and the syntax of SPARQL query lan- guage. We also demonstrate the use of singleton property in the representation and querying of meta knowledge in two examples of Semantic Web knowledge bases: YAGO2 and BKR. This approach, which is also simple and intuitive, can be easily adopted for representing and querying statements about statements in other knowledge bases.
KnowledgeWiki: An OpenSource Tool for Creating Community-Curated Vocabulary, ...Nishita Jaykumar
Resource Description Framework (RDF) datasets can be
created by transforming structured databases, extracting
the triples from semi-structured and unstructured sources,
crowd-sourcing, or by integrating the existing datasets. The
reliability and quality of these datasets can be improved by
the participation of domain experts via a special purpose
tool or a crowd-sourced application. Wikidata and Semantic
MediaWiki are platforms which facilitate this kind of
crowd-sourced data curation.
We present our system, KnowledgeWiki, which is built
upon the existing Semantic MediaWiki. We develop a novel
extension by adopting the singleton property data model in
our KnowledgeWiki. This extension allows various kinds of
metadata about the RDF triples to be created in the Wiki.
We combine this extension with other extensions such as se-
mantic forms to provide a user-friendly, Wiki-like interface
for domain experts with no prior technical expertise to easily
curate data. We also present our new enhancement to Semantic
Mediawiki, which facilitates importing existing RDF
datasets into the wiki-based curating platform based on the
singleton property approach, that preserves the provenance
of individual triples. We also describe how it is being used
by the materials science community to create and curate
consolidated vocabularies.
Semantic Web technologies such as RDF and OWL have become World Wide Web Consortium (W3C) standards for knowledge representation and reasoning. RDF triples about triples, or meta triples, form the basis for a contextualized knowledge graph. They represent the contextual information about individual triples such as the source, the occurring time or place, or the certainty.
However, an efficient RDF representation for such meta-knowledge of triples remains a major limitation of the RDF data model. The existing reification approach allows such meta-knowledge of RDF triples to be expressed in RDF by using four triples per reified triple. While reification is simple and intuitive, this approach does not have a formal foundation and is not commonly used in practice as described in the RDF Primer.
This dissertation presents the foundations for representing, querying, reasoning and traversing the contextualized knowledge graphs (CKG) using Semantic Web technologies.
A triple-based compact representation for CKGs. We propose a principled approach and construct RDF triples about triples by extending the current RDF data model with a new concept, called singleton property (SP), as a triple identifier. The SP representation needs two triples to the RDF datasets and can be queried with SPARQL.
A formal model-theoretic semantics for CKGs. We formalize the semantics of the singleton property and its relationships with the triple it represents. We extend the current RDF model-theoretic semantics to capture the semantics of the singleton properties and provide the interpretation at three levels: simple, RDF, and RDFS. It provides a single interpretation of the singleton property semantics across applications and systems.
A sound and complete inference mechanism for CKGs. Based on the semantics we propose, we develop a set of inference rules for validating and inferring new triples based on the SP syntax. We also develop different sets of context-based inference rules for provenance, time, and uncertainty.
A graph-based formalism for CKGs. We propose a formal contextualized graph model for the SP representation. We formalize the RDF triples as a mathematical graph by combining the model theory and the graph theory into a hybrid RDF formal semantics. The unified semantics allows the RDF formal semantics to be leveraged in the graph-based algorithms.
Data Provenance and its role in Data SciencePaolo Missier
Invited talk at the April 18th-20th Data Science workshop in Islamabad, Pakistan
How provenance may help Data Science. State of the art and open challenges
Learning Multilingual Semantics from Big Data on the WebGerard de Melo
This document summarizes Gerard de Melo's presentation on learning multilingual semantics from big data on the web. It discusses how lexical and taxonomic knowledge can be extracted at large scale from online resources like Wiktionary, Wikipedia, and WordNet. Methods are presented for merging structured data like knowledge graphs and integrating taxonomies across languages using techniques like linear program relaxation and belief propagation. The goal is to build large yet reasonably clean multilingual knowledge bases to power applications in areas like semantic search and the digital humanities.
The document discusses improving information retrieval by structuring data in records, mapping data to common standards like CRM, and publishing as RDF. This would allow linking data across systems, more comprehensive searches, and more representative conclusions by processing more data. Key recommendations include using existing databases, structuring records without free text, mapping to CRM, and publishing as RDF.
Knowledge extraction in Web media: at the frontier of NLP, Machine Learning a...Julien PLU
Julien Plu defended his PhD thesis on knowledge extraction from web media. His research addressed three main challenges: 1) extracting entities from different types of texts and languages, 2) linking entities to multiple knowledge bases, and 3) adapting entity linking pipelines for different contexts. To extract entities, he evaluated various natural language processing techniques including phrase matching, sequence labeling using neural networks, and coreference resolution. He found that combining multiple named entity recognition models improved performance over using a single model. Plu's research provided methods for extracting and linking entities from diverse textual sources in an adaptable manner.
The document discusses a webinar presented by NISO and DCMI on Schema.org and Linked Data. The webinar provides an overview of Schema.org and Linked Data, examines the advantages and challenges of using RDF and Linked Data, looks at Schema.org in more detail, and discusses how Schema.org and Linked Data can be combined. The goals of the webinar are to illustrate the different design choices for identifying entities and describing structured data, integrating vocabularies, and incentives for publishing accurate data, as well as to help guide adoption of Schema.org and Linked Data approaches.
Radically Open Cultural Heritage Data on the WebJulie Allinson
What happens when tens of thousands of archival photos are shared with open licenses, then mashed up with geolocation data and current photos? Or when app developers can freely utilize information and images from millions of books? On this panel, we'll explore the fundamental elements of Linked Open Data and discover how rapidly growing access to metadata within the world's libraries, archives and museums is opening exciting new possibilities for understanding our past, and may help in predicting our future. Our panelists will look into the technological underpinnings of Linked Open Data, demonstrate use cases and applications, and consider the possibilities of such data for scholarly research, preservation, commercial interests, and the future of cultural heritage data.
CEDAR & PRELIDA Preservation of Linked Socio-Historical DataPRELIDA Project
by Albert Meroño, presented at the 3rd PRELIDA Consolidation and Dissemination Workshop, Riva, Italy, October, 17, 2014. More information about the workshop at: prelida.eu
These slides were presented at the "graph databases in life sciences workshop". There is an accompanying Neo4j guide that will walk you through importing data into Neo4j using web services form a number of databases at EMBL-EBI.
https://github.com/simonjupp/importing-lifesci-data-into-neo4j
Presentation at ELAG 2011, European Library Automation Group Conference, Prague, Czech Republic. 25th May 2011
http://elag2011.techlib.cz/en/815-lifting-the-lid-on-linked-data/
This document summarizes work being done to express the Data Documentation Initiative (DDI) metadata standard in Resource Description Framework (RDF) format to improve discovery and linking of microdata on the Web of Linked Data. It describes background on the DDI to RDF mapping effort, the goals of making microdata more accessible and interoperable online, and examples of how the RDF representation would support common discovery use cases. It also provides information on tools and next steps for the ongoing work, acknowledging contributions from participants in workshops where this effort was discussed.
This document provides an overview of linked data and the SPARQL query language. It defines linked data as a method of publishing structured data on the web so that it can be interlinked and queried. The key aspects covered include linked data principles of using URIs to identify things and including links to other related data. SPARQL is introduced as the query language for retrieving and manipulating linked data.
Lecture at the advanced course on Data Science of the SIKS research school, May 20, 2016, Vught, The Netherlands.
Contents
-Why do we create Linked Open Data? Example questions from the Humanities and Social Sciences
-Introduction into Linked Open Data
-Lessons learned about the creation of Linked Open Data (link discovery, knowledge representation, evaluation).
-Accessing Linked Open Data
RDF presentation at DrupalCon San Francisco 2010scorlosquet
The document discusses RDF and the Semantic Web in Drupal 7. It introduces RDF, how resources can be described as relationships between properties and values, and how this turns the web into a giant linked database. It describes Drupal 7's new RDF and RDFa support which exposes entity relationships and allows for machine-readable semantic data. Future improvements discussed include custom RDF mappings, SPARQL querying of site data, and connecting to external RDF sources.
Perspectives on mining knowledge graphs from textJennifer D'Souza
A survey presented at the International Winter School on Knowledge Graphs and Semantic Web 2021 http://www.kgswc.org/winter-school/; November 2021; DOI: 10.13140/RG.2.2.24482.56005
The Semantic Web - Interacting with the UnknownSteffen Staab
When developing user interfaces for interacting with data and content one typically assumes that one knows the type of data and one knows how to interact with such type of data. The core idea of the Semantic Web is that data is self-describing, which implies that its semantics is not designed and described at an initial point in time, but it rather emerges by its use. This flexibility is one of the greatest assets of the Semantic Web, but it also severely handicaps intelligent interaction with its data.
In this talk, we will sketch the principal problem as well as first steps to deal with the problem of interacting with the unknown.
The web of interlinked data and knowledge strippedSören Auer
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.
With the advent of Facebook’s Open Graph, HTML5 and Google’s Rich Snippets, the web has begun a rapid transformation to being understandable for computers. This understanding comes from data that is embedded in webpages and, perhaps more importantly, a new kind of hyperlink that connects concepts instead of documents. Information architects and interaction designers are needed now more than ever to make sense of all this data and to visualize it in new and interesting ways. In this presentation, you will learn how to take advantage of the Semantic Web’s foundational technology called Linked Data, which allows you to both produce and consume the data that is making up this new web.
Prateek Jain dissertation defense, Kno.e.sis, Wright State UniversityPrateek Jain
The recent emergence of the “Linked Data” approach for publishing data represents a major step forward in realizing the original vision of a web that can "understand and satisfy the requests of people and machines to use the web content" – i.e. the Semantic Web. This new approach has resulted in the Linked Open Data (LOD) Cloud, which includes more than 70 large datasets contributed by experts belonging to diverse communities such as geography, entertainment, and life sciences. However, the current interlinks between datasets in the LOD Cloud – as we will illustrate – are too shallow to realize much of the benefits promised. If this limitation is left unaddressed, then the LOD Cloud will merely be more data that suffers from the same kinds of problems, which plague the Web of Documents, and hence the vision of the Semantic Web will fall short.
This thesis presents a comprehensive solution to address the issue of alignment and relationship identification using a bootstrapping based approach. By alignment we mean the process of determining correspondences between classes and properties of ontologies. We identify subsumption, equivalence and part-of relationship between classes. The work identifies part-of relationship between instances. Between properties we will establish subsumption and equivalence relationship. By bootstrapping we mean the process of being able to utilize the information which is contained within the datasets for improving the data within them. The work showcases use of bootstrapping based methods to identify and create richer relationships between LOD datasets. The BLOOMS project (http://wiki.knoesis.org/index.php/BLOOMS) and the PLATO project, both built as part of this research, have provided evidence to the feasibility and the applicability of the solution.
Providing open data is of interest for its societal and commercial value, for transparency, and because more people can do fun things with data. There is a growing number of initiatives to provide open data, from, for example, the UK government and the World Bank. However, much of this data is provided in formats such as Excel files, or even PDF files. This raises the question of
- How best to provide access to data so it can be most easily reused?
- How to enable the discovery of relevant data within the multitude of available data sets?
- How to enable applications to integrate data from large numbers of formerly unknown data sources?
One way to address these issues to to use the design principles of linked data (http://www.w3.org/DesignIssues/LinkedData.html), which suggest best practices for how to publish and connect structured data on the Web. This presentation gives an overview of linked data technologies (such as RDF and SPARQL), examples of how they can be used, as well as some starting points for people who want to provide and use linked data.
The presentation was given on August 8, at the Hacknight event (http://hacknight.se/) of Forskningsavdelningen (http://forskningsavd.se/) (Swedish: “Research Department”) a hackerspace in Malmö.
This document discusses semantic search over big linked data. It describes the technical challenges of searching large linked datasets including issues related to volume, velocity, and variety of data. It presents the author's previous and current work on acquiring, organizing, analyzing, and searching linked data. This includes developing indexes and algorithms for efficient keyword search and top-k query processing over large, heterogeneous linked datasets. The author discusses achievements and opportunities for improving search over hybrid and heterogeneous big data in the future.
Linked Data and Knowledge Graphs -- Constructing and Understanding Knowledge ...Jeff Z. Pan
Tutorial on "Linked Data and Knowledge Graphs -- Constructing and Understanding Knowledge Graphs" presented at the 4th Joint International Conference on Semantic Technologies (JIST2014)
RDA implementation is scheduled for March 31, 2013. Testers of RDA recommended improvements like rewriting instructions in plain English and ensuring community involvement. Differences from AACR2 include lack of abbreviations, more transcription of what is seen, and new fields in MARC like 336, 337, 338 for content/media/carrier types. Linked data and semantic web approaches may make relationships between works more explicit over time. Preparing for RDA involves decisions about cataloging workflows and training.
How information systems are built or acquired puts information, which is what they should be about, in a secondary place. Our language adapted accordingly, and we no longer talk about information systems but applications. Applications evolved in a way to break data into diverse fragments, tightly coupled with applications and expensive to integrate. The result is technical debt, which is re-paid by taking even bigger "loans", resulting in an ever-increasing technical debt. Software engineering and procurement practices work in sync with market forces to maintain this trend. This talk demonstrates how natural this situation is. The question is: can something be done to reverse the trend?
Have you ever been confused by the myriad of choices offered by AWS for hosting a website or an API?
Lambda, Elastic Beanstalk, Lightsail, Amplify, S3 (and more!) can each host websites + APIs. But which one should we choose?
Which one is cheapest? Which one is fastest? Which one will scale to meet our needs?
Join me in this session as we dive into each AWS hosting service to determine which one is best for your scenario and explain why!
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The document discusses a webinar presented by NISO and DCMI on Schema.org and Linked Data. The webinar provides an overview of Schema.org and Linked Data, examines the advantages and challenges of using RDF and Linked Data, looks at Schema.org in more detail, and discusses how Schema.org and Linked Data can be combined. The goals of the webinar are to illustrate the different design choices for identifying entities and describing structured data, integrating vocabularies, and incentives for publishing accurate data, as well as to help guide adoption of Schema.org and Linked Data approaches.
Radically Open Cultural Heritage Data on the WebJulie Allinson
What happens when tens of thousands of archival photos are shared with open licenses, then mashed up with geolocation data and current photos? Or when app developers can freely utilize information and images from millions of books? On this panel, we'll explore the fundamental elements of Linked Open Data and discover how rapidly growing access to metadata within the world's libraries, archives and museums is opening exciting new possibilities for understanding our past, and may help in predicting our future. Our panelists will look into the technological underpinnings of Linked Open Data, demonstrate use cases and applications, and consider the possibilities of such data for scholarly research, preservation, commercial interests, and the future of cultural heritage data.
CEDAR & PRELIDA Preservation of Linked Socio-Historical DataPRELIDA Project
by Albert Meroño, presented at the 3rd PRELIDA Consolidation and Dissemination Workshop, Riva, Italy, October, 17, 2014. More information about the workshop at: prelida.eu
These slides were presented at the "graph databases in life sciences workshop". There is an accompanying Neo4j guide that will walk you through importing data into Neo4j using web services form a number of databases at EMBL-EBI.
https://github.com/simonjupp/importing-lifesci-data-into-neo4j
Presentation at ELAG 2011, European Library Automation Group Conference, Prague, Czech Republic. 25th May 2011
http://elag2011.techlib.cz/en/815-lifting-the-lid-on-linked-data/
This document summarizes work being done to express the Data Documentation Initiative (DDI) metadata standard in Resource Description Framework (RDF) format to improve discovery and linking of microdata on the Web of Linked Data. It describes background on the DDI to RDF mapping effort, the goals of making microdata more accessible and interoperable online, and examples of how the RDF representation would support common discovery use cases. It also provides information on tools and next steps for the ongoing work, acknowledging contributions from participants in workshops where this effort was discussed.
This document provides an overview of linked data and the SPARQL query language. It defines linked data as a method of publishing structured data on the web so that it can be interlinked and queried. The key aspects covered include linked data principles of using URIs to identify things and including links to other related data. SPARQL is introduced as the query language for retrieving and manipulating linked data.
Lecture at the advanced course on Data Science of the SIKS research school, May 20, 2016, Vught, The Netherlands.
Contents
-Why do we create Linked Open Data? Example questions from the Humanities and Social Sciences
-Introduction into Linked Open Data
-Lessons learned about the creation of Linked Open Data (link discovery, knowledge representation, evaluation).
-Accessing Linked Open Data
RDF presentation at DrupalCon San Francisco 2010scorlosquet
The document discusses RDF and the Semantic Web in Drupal 7. It introduces RDF, how resources can be described as relationships between properties and values, and how this turns the web into a giant linked database. It describes Drupal 7's new RDF and RDFa support which exposes entity relationships and allows for machine-readable semantic data. Future improvements discussed include custom RDF mappings, SPARQL querying of site data, and connecting to external RDF sources.
Perspectives on mining knowledge graphs from textJennifer D'Souza
A survey presented at the International Winter School on Knowledge Graphs and Semantic Web 2021 http://www.kgswc.org/winter-school/; November 2021; DOI: 10.13140/RG.2.2.24482.56005
The Semantic Web - Interacting with the UnknownSteffen Staab
When developing user interfaces for interacting with data and content one typically assumes that one knows the type of data and one knows how to interact with such type of data. The core idea of the Semantic Web is that data is self-describing, which implies that its semantics is not designed and described at an initial point in time, but it rather emerges by its use. This flexibility is one of the greatest assets of the Semantic Web, but it also severely handicaps intelligent interaction with its data.
In this talk, we will sketch the principal problem as well as first steps to deal with the problem of interacting with the unknown.
The web of interlinked data and knowledge strippedSören Auer
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.
With the advent of Facebook’s Open Graph, HTML5 and Google’s Rich Snippets, the web has begun a rapid transformation to being understandable for computers. This understanding comes from data that is embedded in webpages and, perhaps more importantly, a new kind of hyperlink that connects concepts instead of documents. Information architects and interaction designers are needed now more than ever to make sense of all this data and to visualize it in new and interesting ways. In this presentation, you will learn how to take advantage of the Semantic Web’s foundational technology called Linked Data, which allows you to both produce and consume the data that is making up this new web.
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The recent emergence of the “Linked Data” approach for publishing data represents a major step forward in realizing the original vision of a web that can "understand and satisfy the requests of people and machines to use the web content" – i.e. the Semantic Web. This new approach has resulted in the Linked Open Data (LOD) Cloud, which includes more than 70 large datasets contributed by experts belonging to diverse communities such as geography, entertainment, and life sciences. However, the current interlinks between datasets in the LOD Cloud – as we will illustrate – are too shallow to realize much of the benefits promised. If this limitation is left unaddressed, then the LOD Cloud will merely be more data that suffers from the same kinds of problems, which plague the Web of Documents, and hence the vision of the Semantic Web will fall short.
This thesis presents a comprehensive solution to address the issue of alignment and relationship identification using a bootstrapping based approach. By alignment we mean the process of determining correspondences between classes and properties of ontologies. We identify subsumption, equivalence and part-of relationship between classes. The work identifies part-of relationship between instances. Between properties we will establish subsumption and equivalence relationship. By bootstrapping we mean the process of being able to utilize the information which is contained within the datasets for improving the data within them. The work showcases use of bootstrapping based methods to identify and create richer relationships between LOD datasets. The BLOOMS project (http://wiki.knoesis.org/index.php/BLOOMS) and the PLATO project, both built as part of this research, have provided evidence to the feasibility and the applicability of the solution.
Providing open data is of interest for its societal and commercial value, for transparency, and because more people can do fun things with data. There is a growing number of initiatives to provide open data, from, for example, the UK government and the World Bank. However, much of this data is provided in formats such as Excel files, or even PDF files. This raises the question of
- How best to provide access to data so it can be most easily reused?
- How to enable the discovery of relevant data within the multitude of available data sets?
- How to enable applications to integrate data from large numbers of formerly unknown data sources?
One way to address these issues to to use the design principles of linked data (http://www.w3.org/DesignIssues/LinkedData.html), which suggest best practices for how to publish and connect structured data on the Web. This presentation gives an overview of linked data technologies (such as RDF and SPARQL), examples of how they can be used, as well as some starting points for people who want to provide and use linked data.
The presentation was given on August 8, at the Hacknight event (http://hacknight.se/) of Forskningsavdelningen (http://forskningsavd.se/) (Swedish: “Research Department”) a hackerspace in Malmö.
This document discusses semantic search over big linked data. It describes the technical challenges of searching large linked datasets including issues related to volume, velocity, and variety of data. It presents the author's previous and current work on acquiring, organizing, analyzing, and searching linked data. This includes developing indexes and algorithms for efficient keyword search and top-k query processing over large, heterogeneous linked datasets. The author discusses achievements and opportunities for improving search over hybrid and heterogeneous big data in the future.
Linked Data and Knowledge Graphs -- Constructing and Understanding Knowledge ...Jeff Z. Pan
Tutorial on "Linked Data and Knowledge Graphs -- Constructing and Understanding Knowledge Graphs" presented at the 4th Joint International Conference on Semantic Technologies (JIST2014)
RDA implementation is scheduled for March 31, 2013. Testers of RDA recommended improvements like rewriting instructions in plain English and ensuring community involvement. Differences from AACR2 include lack of abbreviations, more transcription of what is seen, and new fields in MARC like 336, 337, 338 for content/media/carrier types. Linked data and semantic web approaches may make relationships between works more explicit over time. Preparing for RDA involves decisions about cataloging workflows and training.
Similar to Contextualized Knowledge Graphfrom two perspectives: Semantic Web and Graph Database with an application in PubChem (20)
How information systems are built or acquired puts information, which is what they should be about, in a secondary place. Our language adapted accordingly, and we no longer talk about information systems but applications. Applications evolved in a way to break data into diverse fragments, tightly coupled with applications and expensive to integrate. The result is technical debt, which is re-paid by taking even bigger "loans", resulting in an ever-increasing technical debt. Software engineering and procurement practices work in sync with market forces to maintain this trend. This talk demonstrates how natural this situation is. The question is: can something be done to reverse the trend?
Have you ever been confused by the myriad of choices offered by AWS for hosting a website or an API?
Lambda, Elastic Beanstalk, Lightsail, Amplify, S3 (and more!) can each host websites + APIs. But which one should we choose?
Which one is cheapest? Which one is fastest? Which one will scale to meet our needs?
Join me in this session as we dive into each AWS hosting service to determine which one is best for your scenario and explain why!
Taking AI to the Next Level in Manufacturing.pdfssuserfac0301
Read Taking AI to the Next Level in Manufacturing to gain insights on AI adoption in the manufacturing industry, such as:
1. How quickly AI is being implemented in manufacturing.
2. Which barriers stand in the way of AI adoption.
3. How data quality and governance form the backbone of AI.
4. Organizational processes and structures that may inhibit effective AI adoption.
6. Ideas and approaches to help build your organization's AI strategy.
The Microsoft 365 Migration Tutorial For Beginner.pptxoperationspcvita
This presentation will help you understand the power of Microsoft 365. However, we have mentioned every productivity app included in Office 365. Additionally, we have suggested the migration situation related to Office 365 and how we can help you.
You can also read: https://www.systoolsgroup.com/updates/office-365-tenant-to-tenant-migration-step-by-step-complete-guide/
Monitoring and Managing Anomaly Detection on OpenShift.pdfTosin Akinosho
Monitoring and Managing Anomaly Detection on OpenShift
Overview
Dive into the world of anomaly detection on edge devices with our comprehensive hands-on tutorial. This SlideShare presentation will guide you through the entire process, from data collection and model training to edge deployment and real-time monitoring. Perfect for those looking to implement robust anomaly detection systems on resource-constrained IoT/edge devices.
Key Topics Covered
1. Introduction to Anomaly Detection
- Understand the fundamentals of anomaly detection and its importance in identifying unusual behavior or failures in systems.
2. Understanding Edge (IoT)
- Learn about edge computing and IoT, and how they enable real-time data processing and decision-making at the source.
3. What is ArgoCD?
- Discover ArgoCD, a declarative, GitOps continuous delivery tool for Kubernetes, and its role in deploying applications on edge devices.
4. Deployment Using ArgoCD for Edge Devices
- 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.
Northern Engraving | Nameplate Manufacturing Process - 2024Northern Engraving
Manufacturing custom quality metal nameplates and badges involves several standard operations. Processes include sheet prep, lithography, screening, coating, punch press and inspection. All decoration is completed in the flat sheet with adhesive and tooling operations following. The possibilities for creating unique durable nameplates are endless. How will you create your brand identity? We can help!
Programming Foundation Models with DSPy - Meetup SlidesZilliz
Prompting language models is hard, while programming language models is easy. In this talk, I will discuss the state-of-the-art framework DSPy for programming foundation models with its powerful optimizers and runtime constraint system.
zkStudyClub - LatticeFold: A Lattice-based Folding Scheme and its Application...Alex Pruden
Folding is a recent technique for building efficient recursive SNARKs. Several elegant folding protocols have been proposed, such as Nova, Supernova, Hypernova, Protostar, and others. However, all of them rely on an additively homomorphic commitment scheme based on discrete log, and are therefore not post-quantum secure. In this work we present LatticeFold, the first lattice-based folding protocol based on the Module SIS problem. This folding protocol naturally leads to an efficient recursive lattice-based SNARK and an efficient PCD scheme. LatticeFold supports folding low-degree relations, such as R1CS, as well as high-degree relations, such as CCS. The key challenge is to construct a secure folding protocol that works with the Ajtai commitment scheme. The difficulty, is ensuring that extracted witnesses are low norm through many rounds of folding. We present a novel technique using the sumcheck protocol to ensure that extracted witnesses are always low norm no matter how many rounds of folding are used. Our evaluation of the final proof system suggests that it is as performant as Hypernova, while providing post-quantum security.
Paper Link: https://eprint.iacr.org/2024/257
Connector Corner: Seamlessly power UiPath Apps, GenAI with prebuilt connectorsDianaGray10
Join us to learn how UiPath Apps can directly and easily interact with prebuilt connectors via Integration Service--including Salesforce, ServiceNow, Open GenAI, and more.
The best part is you can achieve this without building a custom workflow! Say goodbye to the hassle of using separate automations to call APIs. By seamlessly integrating within App Studio, you can now easily streamline your workflow, while gaining direct access to our Connector Catalog of popular applications.
We’ll discuss and demo the benefits of UiPath Apps and connectors including:
Creating a compelling user experience for any software, without the limitations of APIs.
Accelerating the app creation process, saving time and effort
Enjoying high-performance CRUD (create, read, update, delete) operations, for
seamless data management.
Speakers:
Russell Alfeche, Technology Leader, RPA at qBotic and UiPath MVP
Charlie Greenberg, host
HCL Notes and Domino License Cost Reduction in the World of DLAUpanagenda
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
Dandelion Hashtable: beyond billion requests per second on a commodity serverAntonios Katsarakis
This slide deck presents DLHT, a concurrent in-memory hashtable. Despite efforts to optimize hashtables, that go as far as sacrificing core functionality, state-of-the-art designs still incur multiple memory accesses per request and block request processing in three cases. First, most hashtables block while waiting for data to be retrieved from memory. Second, open-addressing designs, which represent the current state-of-the-art, either cannot free index slots on deletes or must block all requests to do so. Third, index resizes block every request until all objects are copied to the new index. Defying folklore wisdom, DLHT forgoes open-addressing and adopts a fully-featured and memory-aware closed-addressing design based on bounded cache-line-chaining. This design offers lock-free index operations and deletes that free slots instantly, (2) completes most requests with a single memory access, (3) utilizes software prefetching to hide memory latencies, and (4) employs a novel non-blocking and parallel resizing. In a commodity server and a memory-resident workload, DLHT surpasses 1.6B requests per second and provides 3.5x (12x) the throughput of the state-of-the-art closed-addressing (open-addressing) resizable hashtable on Gets (Deletes).
Freshworks Rethinks NoSQL for Rapid Scaling & Cost-EfficiencyScyllaDB
Freshworks creates AI-boosted business software that helps employees work more efficiently and effectively. Managing data across multiple RDBMS and NoSQL databases was already a challenge at their current scale. To prepare for 10X growth, they knew it was time to rethink their database strategy. Learn how they architected a solution that would simplify scaling while keeping costs under control.
6. What is Contextualized Knowledge Graph?
10/25/2018 6
A contextualized knowledge graph is a knowledge graph in which
every fact is qualified with a set of contextual properties.
7. Subject Predicate Object Starts Ends
Bob Dylan marriedTo Sarah Lownds 1965-11-22 1977-06-29
Bob Dylan marriedTo Carolyn Dennis 1986-06-## 1992-10-##
Motivation Scenario
Facts:
Meta Queries:
Query type Sample query
Provenance P1. Where is this fact from?
P2. When was it created?
P3. Who created this fact?
Time T1. When did this fact occur?
T2. What is the time span of this fact?
T3. Which events happened in the same year?
Location L1. What is the location associated with this fact?
L2. Which events happened at the same place?
Certainty C1. What is the author confidence of this fact?
7
Subject Predicate Object
Bob Dylan marriedTo Sarah Lownds
Bob Dylan marriedTo Carolyn Dennis
9. 9
2973 datasets with 149 billion triples
Linked Data principles
Use URIs as names
Use HTTP URLs to be looked up
URI provides useful info using
standard
Include links to other URIs to
discover more
11. Subject Predicate Object Starts Ends
Bob Dylan marriedTo Sarah Lownds 1965-11-22 1977-06-29
RDF Reification
Form of Triples: RDF Reification
Pros:
1. Intuitive, easy to understand
Cons:
1. Takes 3N triples (4N if including
Statement typing) to represent a
statement => Not scalable
2. No formal semantics defined =>
Semantics is unclear
3. Discouraged in LOD!
Time-aware Facts:
11
Subject Predicate Object
#stmt1 type Statement
#stmt1 hasSubject BobDylan
#stmt1 hasProperty marriedTo
#stmt1 hasObject Sara Lownds
Bob Dylan marriedTo Sarah Lownds
#stmt1 starts 1965-11-22
#stmt1 ends 1977-06-29
12. Subject Predicate Object Starts Ends
Bob Dylan marriedTo Sarah Lownds 1965-11-22 1977-06-29
RDF Reification
RDF Reification vs. Singleton Property
Time-aware Facts:
Subject Predicate Object
#stmt1 type Statement
#stmt1 hasSubject BobDylan
#stmt1 hasProperty marriedTo
#stmt1 hasObject Sara Lownds
Bob Dylan marriedTo Sarah Lownds
#stmt1 starts 1965-11-22
#stmt1 ends 1977-06-29
Subject Predicate Object
marriedTo#1 rdf:sp marriedTo
BobDylan marriedTo#1 Sarah Lownds
marriedTo#1 starts 1965-11-22
marriedTo#1 ends 1977-06-29
Singleton Property
12
Vinh Nguyen, Olivier Bodenreider, and Amit Sheth. "Don't like RDF reification?: making statements about statements
using singleton property." In Proceedings of the 23rd international conference on World wide web, pp. 759-770. ACM,
2014.
13. Subject Predicate Object Source DateExtracted
Bob Dylan marriedTo Sarah Lownds wikipage:Bob_Dylan 2009-06-07
Form of Triples: PaCE
Pros:
1. Save ~50% number of triples
compared to reification thanks
to the repeated subject,
predicate, and object.
Cons:
1. Not intuitive, hard to
understand
2. Limited expressiveness
Provenance-aware Facts:
13
Provenance-aware Context Entity
Subject Predicate Object
BobDylan_wp rdf:type Bob Dylan
SaraLownds_wp rdf:type Sara Lownds
BobDylan_wp marriedTo SaraLownds_wp
BobDylan_wp hasSource wiki:Bob_Dylan
BobDylan_wp hasDateExt 2009-06-07
Satya S. Sahoo, Olivier Bodenreider, Pascal Hitzler, Amit Sheth, and Krishnaprasad Thirunarayan. 2010. Provenance
context entity (PaCE): scalable provenance tracking for scientific RDF data. In Proceedings of the 22nd international
conference on Scientific and statistical database management (SSDBM'10),
14. Subject Predicate Object Source DateExtracted
Bob Dylan marriedTo Sarah Lownds wikipage:Bob_Dylan 2009-06-07
Provenance-aware Context Entity
Subject Predicate Object
BobDylan_wp rdf:type Bob Dylan
SaraLownds_wp rdf:type Sara Lownds
BobDylan_wp marriedTo SaraLownds_wp
BobDylan_wp hasSource wiki:Bob_Dylan
BobDylan_wp hasDateExt 2009-06-07
Facts and Provenance:
14
PaCE vs. Singleton Property
Subject Predicate Object
marriedTo#1 rdf:sp marriedTo
BobDylan marriedTo#1 Sarah Lownds
marriedTo#1 hasSource wp:Bob_Dylan
marriedTo#1 hasDateExt 2009-06-07
Singleton Property
15. Form of Quadruples: Named Graph
Pros:
1. Intuitive --creating # named graphs
for # sources
2. Attach metadata for a set of triples
3. SPARQL supported
Cons:
1. Defined for provenance only
2. Ambiguous semantics while
associating different types of
metadata at triple level
Time-aware Facts:
* Carroll, Jeremy J., et al. "Named graphs, provenance and trust." Proceedings of the 14th international conference on World Wide Web. ACM, 2005.
15
Subject Predicate Object Starts Ends
Bob Dylan marriedTo Sarah Lownds 1965-11-22 1977-06-29
Named Graph
Subject Predicate Object NG
Bob Dylan marriedTo Sarah Lownds ng_1
ng_1 starts 1965-11-22 Prov_graph
ng_2 ends 1977-06-29 Prov_graph
16. Named Graph
Subject Predicate Object NG
Bob Dylan marriedTo Sarah Lownds ng_1
ng_1 starts 1965-11-22 Prov_graph
ng_2 ends 1977-06-29 Prov_graph
Time-aware Facts:
Subject Predicate Object Starts Ends
Bob Dylan marriedTo Sarah Lownds 1965-11-22 1977-06-29
Named Graph vs. Singleton Property
Subject Predicate Object
marriedTo#1 rdf:sp marriedTo
Bob Dylan marriedTo#1 Sarah Lownds
marriedTo#1 starts 1965-11-22
marriedTo#1 ends 1977-06-29 16
Singleton Property
17. RDF+:
Subject Predicate Object Meta Property Meta value
Bob Dylan marriedTo Sarah Lownds starts 1965-11-22
Bob Dylan marriedTo Sarah Lownds ends 1977-06-29
Form of Quintuples: RDF+
Cons:
1. The representation is not in the form of RDF. Statement identifiers are used
internally. Require the mappings from RDF to RDF+ and vice versa.
2. The SPARQL query syntax and semantics need to be extended to support RDF+
Facts and Temporal Information:
* Dividino, Renata, et al. "Querying for provenance, trust, uncertainty and other meta knowledge in RDF." Web
Semantics: Science, Services and Agents on the World Wide Web 7.3 (2009): 204-219.
17
Subject Predicate Object Starts Ends
Bob Dylan marriedTo Sarah Lownds 1965-11-22 1977-06-29
18. Experiment: BKR with Provenance
All datasets are available at http://wiki.knoesis.org/index.php/Singleton_Property 20
• Five data sets generated from the same seed BKR
Singleton Property (SP)
Reification (R)
PaCE C1 (C1)
PaCE C2 (C2)
PaCE C3 (C3)
20. • Gang Fu, Evan Bolton, Núria Queralt Rosinach, Laura I Furlong, Vinh Nguyen, Amit
Sheth, Olivier Bodenreider, Michel Dumontier. Exposing provenance metadata using
different RDF models. In Proceedings of Semantic Web Applications and Tools for
Life Science (SWAT4LS), 2016.
https://pubchem.ncbi.nlm.nih.gov/
• Hernández, Daniel, Aidan Hogan, and Markus Krötzsch. "Reifying RDF: What works
well with wikidata?." SSWS@ ISWC 1457 (2015): 32-47.
• Frey, Johannes, Kay Müller, Sebastian Hellmann, Erhard Rahm, and Maria-Esther
Vidal. "Evaluation of Metadata Representations in RDF stores.”
• Daniel Hernández, Aidan Hogan, Cristian Riveros, Carlos Rojas, Enzo Zerega:
Querying Wikidata: Comparing SPARQL, Relational and Graph Databases.
International Semantic Web Conference (2) 2016: 88-103
22
External Evaluation
21. Subject Predicate Object Source FromDataset Confidence
CID5280961(Genistein) inhibits GID2100(ESR2) PMID12502307 ChemBL
CID5757(Estradiol) activates GID2100(ESR2) PMID19128016 ChemBL
10/25/2018
Exposing provenance metadata using different RDF models
Gang Fu, Evan Bolton, Núria Queralt Rosinach, Laura I Furlong, Vinh Nguyen, Amit Sheth, Olivier Bodenreider, Michel Dumontier
22. Model I Model II Model III Model IV Model V
22,787,218 21,445,348 19,575,298 17,239,427 27,605,782
24
PubChem
• Five data sets generated from the same seed
N-ary with cardinal assertion (Model I)
N-ary without cardinal assertion (Model II)
Singleton property with cardinal assertion (Model III)
Singleton property without cardinal assertion (Model IV)
NanoPublication (Model V)
• Comparing sizes of generated datasets
SP datasets are the most compact ones
Gang Fu, Evan Bolton, Núria Queralt Rosinach, Laura I Furlong, Vinh Nguyen, Amit Sheth, Olivier
Bodenreider, Michel Dumontier. Exposing provenance metadata using different RDF models. In
Proceedings of Semantic Web Applications and Tools for Life Science (SWAT4LS), 2016.
25. 27
WikiData
• Four data sets generated from the same seed
Standard Reification (SR)
N-ary relation (NR)
Singleton property (SP)
Named Graph (NG)
• Comparing sizes of generated datasets
SP dataset is the most compact one
Hernández, Daniel, Aidan Hogan, and Markus Krötzsch. "Reifying RDF: What works well with
wikidata?." SSWS@ ISWC 1457 (2015): 32-47.
26. 28
WikiData
• Query performance in 4store and GraphDB
SP models are not supported by 4store and GraphDB
• Query performance in Virtuoso and BlazeGraph
Reification and NG are well-supported by Virtuoso and
BlazeGraph
SP is little faster than NR in Virtuoso, slower in BlazeGraph
27. 29
WikiData
• Six data sets generated from the same seed
Standard Reification (stdreif)
N-ary relation (naryrel)
Singleton property (sgprop)
Companion property (cpprop)
Named Graph (ngraphs)
RDF* (rdr)
• Comparing sizes of generated datasets
SP dataset is the most compact triple representation
Fastest in loading time for WikiData
Best query performance for StarDog in all cases
Slowest in Virtuoso but not by much for WikiData queries
Not encounter performance issues with SP
Frey, Johannes, Kay Müller, Sebastian Hellmann, Erhard Rahm, and Maria-Esther Vidal. "Evaluation of
Metadata Representations in RDF stores."
28. 30
Experimental Comparison
• Dataset size
SP offers the most concise representation in all cases
• Query performance
SP performs reasonably well in Virtuoso, best in StarDog, OK in
BlazeGraph
SP may have the potential for the performance gain if
supported and optimized by the query engines
Is SP representation optimal?
34. 10/25/2018 36
Current PubChem Neighbor
• Number of links
92,000,000 * 92,000,000 / 2 = 4.232 * 10^15
4 quadrillion
• Challenges
⨯ Number of triples increases to quadrillion
⨯ SPARQL query processing for Quadrillion triples
• Is it worth?
Chemical similarity is one of the most important concept in
chemoinformatics
Similar compounds have similar properties
Semantic Web Technology, enhanced by a massive use of open linked data, plays a crucial role in the overall Deep QA architecture
CEO Sundar Pichai led the charge here, noting that Google's Knowledge Graph (the easily accessible information that pop up under the search bar for certain queries) now encompasses 70 billion facts
1163 datasets
Using Semantic Web technologies
149,423,660,620 triples from 2973 datasets (retrieved Dec 14)
Use URIs as names for things
Use HTTP URIs so that people can look up those names.
When someone looks up a URI, provide useful information, using the standards (RDF*, SPARQL)
Include links to other URIs. so that they can discover more things.
Five datasets
One slide shows the graph database approach
One slide compares the SP and property graph
One slide shows the schema
One slide shows similarity score file
One slide shows the numbers in the schema
One slides show the numbers for all approaches