Andrew Ashton's presentation from DH2010; discusses techniques for using RDF/OWL as a mechanism for using TEI -encoded texts in distributed analysis and publication frameworks.
A view on data quality in the real estate domain.
Presented at the LDQ workshop, colocated with SEMANTICS 2017 conference.
see https://2017.semantics.cc/satellite-events/linked-data-quality-assessment-and-improvement-academia-industry
for more details
The document discusses test-driven quality assessment of RDF data. It proposes a methodology called the Test-driven Quality Assessment Methodology (TDQAM) where test cases are generated automatically from the RDF schema to validate data constraints. Test cases are written as SPARQL queries and can check for issues like a person having a birthdate after a deathdate. Pattern-based test generators analyze the schema to instantiate test cases. The methodology provides a unified way to validate RDF data against different schema languages to improve data quality.
Semantic Web and Linked Data for cultural heritage materials - Approaches in ...Antoine Isaac
The document discusses using semantic web technologies like linked data and the Europeana Data Model (EDM) to improve access to cultural heritage materials by enabling semantic search and exploiting relationships between concepts, objects, and vocabularies. EDM aims to preserve original metadata while allowing for interoperability by using standards like Dublin Core, SKOS, and OAI ORE. Linked data approaches can ease getting and publishing data across cultural heritage datasets by direct access to RDF descriptions via URIs.
This document discusses 3 use cases for linked data in higher education, including projects in the UK and Australia. It also describes David Flanders' background working with linked data at organizations like JISC and ANDS, and several linked data projects he has worked on including Open Bibliography, LOCAH, and developing ANDS vocabularies. The document raises the idea of using URIs instead of human terms as metadata for research data to enable machines to better understand and compare the data.
Deriving an Emergent Relational Schema from RDF DataGraph-TA
This document discusses deriving an emergent relational schema from RDF data. It describes extracting characteristic sets from RDF data to recognize classes and relationships between classes. These characteristic sets are then merged and labeled to create a logical relational schema. This emergent schema provides benefits for both systems through improved efficiency and humans through easier query formulation over the RDF data. Key aspects of a useful emergent schema are discussed such as being compact, having human-friendly labels, providing high coverage of the RDF data, and being efficient to compute. Experimental results on real-world RDF datasets show the approach produces compact schemas with high coverage and understandable labels that improve performance over the native RDF representation.
The document discusses RDF (Resource Description Framework), which is a W3C standard for encoding knowledge on the Semantic Web. It allows computers to seek out knowledge and take action on it. RDFa extends HTML to add rich metadata within web documents and enables embedding and extracting of RDF triples. The document then discusses the history and goals of incorporating RDF into the Drupal content management system, including automatically exposing Drupal data in RDF without requiring RDF expertise and supporting a user-driven data model. It proposes some experiments with Drupal 7, like automatically generating site vocabularies and mapping content to existing ontologies.
This document introduces exploratory querying and SPEX, a tool for exploratory querying of spatial and temporal data. It summarizes the goals of exploratory querying, gives examples of exploratory querying software, and demonstrates SPEX through use cases of exploring integrated datasets like the Dutch BAG registry and real estate listings. The presentation describes SPEX's capabilities for interactively querying and visualizing linked geospatial and temporal data to understand dataset contents for further use and integration.
A view on data quality in the real estate domain.
Presented at the LDQ workshop, colocated with SEMANTICS 2017 conference.
see https://2017.semantics.cc/satellite-events/linked-data-quality-assessment-and-improvement-academia-industry
for more details
The document discusses test-driven quality assessment of RDF data. It proposes a methodology called the Test-driven Quality Assessment Methodology (TDQAM) where test cases are generated automatically from the RDF schema to validate data constraints. Test cases are written as SPARQL queries and can check for issues like a person having a birthdate after a deathdate. Pattern-based test generators analyze the schema to instantiate test cases. The methodology provides a unified way to validate RDF data against different schema languages to improve data quality.
Semantic Web and Linked Data for cultural heritage materials - Approaches in ...Antoine Isaac
The document discusses using semantic web technologies like linked data and the Europeana Data Model (EDM) to improve access to cultural heritage materials by enabling semantic search and exploiting relationships between concepts, objects, and vocabularies. EDM aims to preserve original metadata while allowing for interoperability by using standards like Dublin Core, SKOS, and OAI ORE. Linked data approaches can ease getting and publishing data across cultural heritage datasets by direct access to RDF descriptions via URIs.
This document discusses 3 use cases for linked data in higher education, including projects in the UK and Australia. It also describes David Flanders' background working with linked data at organizations like JISC and ANDS, and several linked data projects he has worked on including Open Bibliography, LOCAH, and developing ANDS vocabularies. The document raises the idea of using URIs instead of human terms as metadata for research data to enable machines to better understand and compare the data.
Deriving an Emergent Relational Schema from RDF DataGraph-TA
This document discusses deriving an emergent relational schema from RDF data. It describes extracting characteristic sets from RDF data to recognize classes and relationships between classes. These characteristic sets are then merged and labeled to create a logical relational schema. This emergent schema provides benefits for both systems through improved efficiency and humans through easier query formulation over the RDF data. Key aspects of a useful emergent schema are discussed such as being compact, having human-friendly labels, providing high coverage of the RDF data, and being efficient to compute. Experimental results on real-world RDF datasets show the approach produces compact schemas with high coverage and understandable labels that improve performance over the native RDF representation.
The document discusses RDF (Resource Description Framework), which is a W3C standard for encoding knowledge on the Semantic Web. It allows computers to seek out knowledge and take action on it. RDFa extends HTML to add rich metadata within web documents and enables embedding and extracting of RDF triples. The document then discusses the history and goals of incorporating RDF into the Drupal content management system, including automatically exposing Drupal data in RDF without requiring RDF expertise and supporting a user-driven data model. It proposes some experiments with Drupal 7, like automatically generating site vocabularies and mapping content to existing ontologies.
This document introduces exploratory querying and SPEX, a tool for exploratory querying of spatial and temporal data. It summarizes the goals of exploratory querying, gives examples of exploratory querying software, and demonstrates SPEX through use cases of exploring integrated datasets like the Dutch BAG registry and real estate listings. The presentation describes SPEX's capabilities for interactively querying and visualizing linked geospatial and temporal data to understand dataset contents for further use and integration.
RDF Graph Data Management in Oracle Database and NoSQL PlatformsGraph-TA
This document discusses Oracle's support for graph data models across its database and NoSQL platforms. It provides an overview of Oracle's RDF graph and property graph support in Oracle Database 12c and Oracle NoSQL Database. It also outlines Oracle's strategy to support graph data types on all its enterprise platforms, including Oracle Database, Oracle NoSQL, Oracle Big Data, and Oracle Cloud.
VALA Tech Camp 2017: Intro to Wikidata & SPARQLJane Frazier
A hands-on introduction to interrogation of Wikidata content using SPARQL, the query language used to query data represented in RDF, SKOS, OWL, and other Semantic Web standards.
Presented by myself and Peter Neish, Research Data Specialist @ University of Melbourne.
Presentation of the INVENiT Expert Meeting on Monday 16 February 2015Leon Wessels
This document provides an agenda and summaries of presentations for an INVENiT supervision team meeting. The agenda includes introductions of INVENiT and various search demonstration tools, including the Rijksmuseum interface and a research space tool using the CIDOC-CRM ontology. Presentations will cover linking cultural heritage data, defining genre-specific relevance patterns, and new ways of opening up religious heritage collections at the VU University Library using image crowdsourcing. The meeting will conclude with an evaluation period over drinks.
From XML to MARC. RDF behind the scenes.Y. Nicolas
[ELAG Conference. 2018]
We collect heterogeneous metadata packages from various publishers. Although all of them are in XML, they vary a lot in terms of vocabulary, structure, granularity, precision, and accuracy. It is quite a challenge to cope with this jungle and recycling it to meet the needs of the Sudoc, the French academic union cataloguing system.
How to integrate and enrich these metadata ? How to integrate them in order to process them in a regular way, not through ad hoc processes ? How to integrate them with specific or generic controlled vocabularies ? How to enrich them with author identifiers, for instance ?
RDF looks like the ideal solution for integration and enrichment. Metadata are stored in the Virtuoso RDF database and processed through a workflow steered by the Oracle DB. We will illustrate this generic solution with Oxford UP metadata : ONIX records for printed books and KBART package description for ebooks.
The document discusses the ABES agency's work in collecting, normalizing, enriching and sharing bibliographic metadata from various sources like XML files, MARC records, and linked open data using RDF. It focuses on four use cases: linking print and ebook metadata, linking documents to authority records, linking articles to controlled vocabularies, and linking book chapters to concepts. The work involves transforming different data formats into RDF and linking entities between multiple data graphs. Challenges discussed include balancing data model flexibility with technological choices and workflows, and ensuring two-way communication between the RDF processing and cataloging activities.
This document discusses locality-sensitive hashing (LSH) and related techniques for efficiently finding similar items in large datasets. LSH works by using hash functions to map similar items to the same "buckets", allowing efficient lookup of near neighbors. The document outlines applications of LSH such as duplicate detection, clustering, and search. It also discusses limitations of LSH and how Bayesian and probabilistic graphical models can be used to improve similarity search for less similar items or incorporate additional context. Links to further resources on machine learning, statistics, and related topics are provided.
Hash tables and hash maps in python | EdurekaEdureka!
YouTube Link: https://youtu.be/APAbRkrqDVI
** Python Certification Training: https://www.edureka.co/python-programming-certification-training**
This Edureka PPT on 'HashTables and HashMaps in Python' will help you learn how you to implement Hash Tables and HashMaps in Python using dictionaries.
Follow us to never miss an update in the future.
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The Open Knowledge Extraction Challenge focuses on the production of new knowledge aimed at either populating and enriching existing knowledge bases or creating new ones. This means that the defined tasks focus on extracting concepts, individuals, properties, and statements that not necessarily exist already in a target knowledge base, and on representing them according to Semantic Web standard in order to be directly injected in linked datasets and their ontologies. The OKE challenge, has the ambition to advance a reference framework for research on Knowledge Extraction from text for the Semantic Web by re-defining a number of tasks (typically from information and knowledge extraction) by taking into account specific SW requirements. The Challenge is open to everyone from industry and academia.
The document discusses generating high quality Linked Open Data using the RDF Mapping Language (RML). RML allows for the uniform and declarative generation of RDF from heterogeneous data sources through mapping rules. It supports assessing mapping quality to identify issues before data is generated. Metadata can also be automatically generated from the mappings. The document emphasizes that non-technical data specialists should be able to easily edit the mappings over time.
Knowledge Patterns for the Web: extraction, transformation, and reuseAndrea Nuzzolese
KPs are an abstraction of frames as introduced by Fillmore and Minsky. KP discovery needs to address two main research problems: the heterogeneity of sources, formats and semantics in the Web (i.e., the knowledge soup problem) and the difficulty to draw relevant boundary around data that allows to capture the meaningful knowledge with respect to a certain context (i.e., the knowledge boundary problem). Hence, we introduce two methods that provide different solutions to these two problems by tackling KP discovery from two different perspectives: (i) the transformation of KP-like artifacts (i.e., top-down defined artifacts that can be compared to KPs, such as FrameNet frames or Ontology Design Patterns) to KPs formalized as OWL2 ontologies; (ii) the bottom-up extraction of KPs by analyzing how data are organized in Linked Data. The two methods address the knowledge soup and boundary problems in different ways. The first method provides a solution to the two aforementioned problems that is based on a purely syntactic transformation step of the original source to RDF followed by a refactoring step whose aim is to add semantics to RDF by select meaningful RDF triples. The second method allows to draw boundaries around RDF in Linked Data by analyzing type paths. A type path is a possible route through an RDF that takes into account the types associated to the nodes of a path. Unfortunately, type paths are not always available. In fact, Linked Data is a knowledge soup because of the heterogeneous semantics of its datasets and because of the limited intentional as well as extensional coverage of ontologies (e.g., DBpedia ontology, YAGO) or other controlled vocabularies (e.g., SKOS, FOAF, etc.). Thus, we propose a solution for enriching Linked Data with additional axioms (e.g., rdf:type axioms) by exploiting the natural language available for example in annotations (e.g. rdfs:comment) or in corpora on which datasets in Linked Data are grounded (e.g. DBpedia is grounded on Wikipedia). Then we present K∼ore, a software architec- ture conceived to be the basis for developing KP discovery systems and designed according to two software architectural styles, i.e, the Component-based and REST. K∼ore is the architectural binding of a set of tools, i.e., K∼tools, which implements the methods for KP transformation and extraction. Finally we provide an example of reuse of KP based on Aemoo, an exploratory search tool which exploits KPs for performing entity summarization.
This document discusses rules and the Semantic Web Rule Language (SWRL). It defines rules as a means of representing knowledge similar to if-then statements. SWRL combines OWL and rule-based languages by allowing users to write rules that can refer to OWL classes, properties, individuals and datatypes. SWRL has an abstract and XML syntax and supports built-in predicates for manipulating data types. Rules provide more expressivity than RDFS and OWL in some cases, such as defining application behaviors, but rule-based reasoning is less performant so they should not be overused when RDFS/OWL suffice.
Federated data stores using semantic web technologySteve Ray
Semantic web, or linked data technology can help address interoperability problems in the internet, and particularly in support of the Internet of Things. This is an simple introduction to this technology.
This document discusses using public RDF resources in Neo4j graphs. It describes various RDF resources like databases, annotated datasets, and public vocabularies that are available. It then explains how to access these resources through bulk download, APIs, SPARQL queries, or by converting RDF to Neo4j's native property graph format using the n10s tool. The document demonstrates importing various life science and disease datasets to create a COVID-19 knowledge graph in Neo4j in under 20 minutes. It encourages users to download Neo4j and n10s and link additional public data sources to explore applications like semantic search, knowledge discovery, and reconciliation.
An Algebraic Data Model for Graphs and Hypergraphs (Category Theory meetup, N...Joshua Shinavier
A presentation for the Category Theory meetup at Uber in San Francisco, November 21, 2019. A combination of previous slide shows motivating and presenting the Algebraic Property Graphs data model.
A Graph is a Graph is a Graph: Equivalence, Transformation, and Composition o...Joshua Shinavier
This document provides an overview of graphs and graph data models. It discusses how graphs can be represented as categories and how different data models like property graphs, RDF, and relational models are equivalent categories. It also describes common graph transformations between these models and discusses Uber's goal of building a knowledge graph to integrate their diverse datasets.
Not sure what RDF is and confused about or how it relates to Linked Data and the jargon surrounding it? This describes of what RDF as well as what you need to know to understand how it applies to library work.
Although you may not have heard of JavaScript Object Notation Linked Data (JSON-LD), it is already impacting your business. Search engine giants such as Google have mandated JSON-LD as a preferred means of adding structured data to web pages to make them considerably easier to parse for more accurate search engine results. The Google use case is indicative of the larger capacity for JSON-LD to increase web traffic for sites and better guide users to the results they want.
Expectations are high for (JSON-LD), and with good reason. JSON-LD effectively delivers the many benefits of JSON, a lightweight data interchange format, into the linked data world. Linked data is the technological approach supporting the World Wide Web and one of the most effective means of sharing data ever devised.
In addition, the growing number of enterprise knowledge graphs fully exploit the potential of JSON-LD as it enables organizations to readily access data stored in document formats and a variety of semi-structured and unstructured data as well. By using this technology to link internal and external data, knowledge graphs exemplify the linked data approach underpinning the growing adoption of JSON-LD—and the demonstrable, recurring business value that linked data consistently provides.
Join us learn more about optimizing the unique Document and Graph Database capabilities provided by AllegroGraph to develop or enhance your Enterprise Knowledge Graph using JSON-LD.
This document summarizes a presentation about visualizing data in time and space dimensions. It discusses exploring temporal and spatial aspects in humanities scholarship. It provides examples of tools for browsing objects using time and location, visualizing data on maps, and timelines. It also covers principles of working with time series and geospatial data, including processing, analysis, and combining statistical and geospatial data to identify patterns. Finally, it presents tools for refining, manipulating, and integrating spatial and temporal data in exhibits and digital projects.
This document discusses time-space mapping techniques in architecture and urban planning. It provides an overview of time-space visualization principles, including indicating time in maps, activity patterns, isochronic maps, tempographic maps, and rhythm maps. Examples of classic time-space maps are shown, such as Minard's 1861 map of Napoleon's march and retreat from Moscow, Chombart de Lauwe's 1957 map of daily activity patterns in Paris, and Galton's 1881 map showing the time required to travel between London parishes.
RDF Graph Data Management in Oracle Database and NoSQL PlatformsGraph-TA
This document discusses Oracle's support for graph data models across its database and NoSQL platforms. It provides an overview of Oracle's RDF graph and property graph support in Oracle Database 12c and Oracle NoSQL Database. It also outlines Oracle's strategy to support graph data types on all its enterprise platforms, including Oracle Database, Oracle NoSQL, Oracle Big Data, and Oracle Cloud.
VALA Tech Camp 2017: Intro to Wikidata & SPARQLJane Frazier
A hands-on introduction to interrogation of Wikidata content using SPARQL, the query language used to query data represented in RDF, SKOS, OWL, and other Semantic Web standards.
Presented by myself and Peter Neish, Research Data Specialist @ University of Melbourne.
Presentation of the INVENiT Expert Meeting on Monday 16 February 2015Leon Wessels
This document provides an agenda and summaries of presentations for an INVENiT supervision team meeting. The agenda includes introductions of INVENiT and various search demonstration tools, including the Rijksmuseum interface and a research space tool using the CIDOC-CRM ontology. Presentations will cover linking cultural heritage data, defining genre-specific relevance patterns, and new ways of opening up religious heritage collections at the VU University Library using image crowdsourcing. The meeting will conclude with an evaluation period over drinks.
From XML to MARC. RDF behind the scenes.Y. Nicolas
[ELAG Conference. 2018]
We collect heterogeneous metadata packages from various publishers. Although all of them are in XML, they vary a lot in terms of vocabulary, structure, granularity, precision, and accuracy. It is quite a challenge to cope with this jungle and recycling it to meet the needs of the Sudoc, the French academic union cataloguing system.
How to integrate and enrich these metadata ? How to integrate them in order to process them in a regular way, not through ad hoc processes ? How to integrate them with specific or generic controlled vocabularies ? How to enrich them with author identifiers, for instance ?
RDF looks like the ideal solution for integration and enrichment. Metadata are stored in the Virtuoso RDF database and processed through a workflow steered by the Oracle DB. We will illustrate this generic solution with Oxford UP metadata : ONIX records for printed books and KBART package description for ebooks.
The document discusses the ABES agency's work in collecting, normalizing, enriching and sharing bibliographic metadata from various sources like XML files, MARC records, and linked open data using RDF. It focuses on four use cases: linking print and ebook metadata, linking documents to authority records, linking articles to controlled vocabularies, and linking book chapters to concepts. The work involves transforming different data formats into RDF and linking entities between multiple data graphs. Challenges discussed include balancing data model flexibility with technological choices and workflows, and ensuring two-way communication between the RDF processing and cataloging activities.
This document discusses locality-sensitive hashing (LSH) and related techniques for efficiently finding similar items in large datasets. LSH works by using hash functions to map similar items to the same "buckets", allowing efficient lookup of near neighbors. The document outlines applications of LSH such as duplicate detection, clustering, and search. It also discusses limitations of LSH and how Bayesian and probabilistic graphical models can be used to improve similarity search for less similar items or incorporate additional context. Links to further resources on machine learning, statistics, and related topics are provided.
Hash tables and hash maps in python | EdurekaEdureka!
YouTube Link: https://youtu.be/APAbRkrqDVI
** Python Certification Training: https://www.edureka.co/python-programming-certification-training**
This Edureka PPT on 'HashTables and HashMaps in Python' will help you learn how you to implement Hash Tables and HashMaps in Python using dictionaries.
Follow us to never miss an update in the future.
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Facebook: https://www.facebook.com/edurekaIN/
Twitter: https://twitter.com/edurekain
LinkedIn: https://www.linkedin.com/company/edureka
Castbox: https://castbox.fm/networks/505?country=in
The Open Knowledge Extraction Challenge focuses on the production of new knowledge aimed at either populating and enriching existing knowledge bases or creating new ones. This means that the defined tasks focus on extracting concepts, individuals, properties, and statements that not necessarily exist already in a target knowledge base, and on representing them according to Semantic Web standard in order to be directly injected in linked datasets and their ontologies. The OKE challenge, has the ambition to advance a reference framework for research on Knowledge Extraction from text for the Semantic Web by re-defining a number of tasks (typically from information and knowledge extraction) by taking into account specific SW requirements. The Challenge is open to everyone from industry and academia.
The document discusses generating high quality Linked Open Data using the RDF Mapping Language (RML). RML allows for the uniform and declarative generation of RDF from heterogeneous data sources through mapping rules. It supports assessing mapping quality to identify issues before data is generated. Metadata can also be automatically generated from the mappings. The document emphasizes that non-technical data specialists should be able to easily edit the mappings over time.
Knowledge Patterns for the Web: extraction, transformation, and reuseAndrea Nuzzolese
KPs are an abstraction of frames as introduced by Fillmore and Minsky. KP discovery needs to address two main research problems: the heterogeneity of sources, formats and semantics in the Web (i.e., the knowledge soup problem) and the difficulty to draw relevant boundary around data that allows to capture the meaningful knowledge with respect to a certain context (i.e., the knowledge boundary problem). Hence, we introduce two methods that provide different solutions to these two problems by tackling KP discovery from two different perspectives: (i) the transformation of KP-like artifacts (i.e., top-down defined artifacts that can be compared to KPs, such as FrameNet frames or Ontology Design Patterns) to KPs formalized as OWL2 ontologies; (ii) the bottom-up extraction of KPs by analyzing how data are organized in Linked Data. The two methods address the knowledge soup and boundary problems in different ways. The first method provides a solution to the two aforementioned problems that is based on a purely syntactic transformation step of the original source to RDF followed by a refactoring step whose aim is to add semantics to RDF by select meaningful RDF triples. The second method allows to draw boundaries around RDF in Linked Data by analyzing type paths. A type path is a possible route through an RDF that takes into account the types associated to the nodes of a path. Unfortunately, type paths are not always available. In fact, Linked Data is a knowledge soup because of the heterogeneous semantics of its datasets and because of the limited intentional as well as extensional coverage of ontologies (e.g., DBpedia ontology, YAGO) or other controlled vocabularies (e.g., SKOS, FOAF, etc.). Thus, we propose a solution for enriching Linked Data with additional axioms (e.g., rdf:type axioms) by exploiting the natural language available for example in annotations (e.g. rdfs:comment) or in corpora on which datasets in Linked Data are grounded (e.g. DBpedia is grounded on Wikipedia). Then we present K∼ore, a software architec- ture conceived to be the basis for developing KP discovery systems and designed according to two software architectural styles, i.e, the Component-based and REST. K∼ore is the architectural binding of a set of tools, i.e., K∼tools, which implements the methods for KP transformation and extraction. Finally we provide an example of reuse of KP based on Aemoo, an exploratory search tool which exploits KPs for performing entity summarization.
This document discusses rules and the Semantic Web Rule Language (SWRL). It defines rules as a means of representing knowledge similar to if-then statements. SWRL combines OWL and rule-based languages by allowing users to write rules that can refer to OWL classes, properties, individuals and datatypes. SWRL has an abstract and XML syntax and supports built-in predicates for manipulating data types. Rules provide more expressivity than RDFS and OWL in some cases, such as defining application behaviors, but rule-based reasoning is less performant so they should not be overused when RDFS/OWL suffice.
Federated data stores using semantic web technologySteve Ray
Semantic web, or linked data technology can help address interoperability problems in the internet, and particularly in support of the Internet of Things. This is an simple introduction to this technology.
This document discusses using public RDF resources in Neo4j graphs. It describes various RDF resources like databases, annotated datasets, and public vocabularies that are available. It then explains how to access these resources through bulk download, APIs, SPARQL queries, or by converting RDF to Neo4j's native property graph format using the n10s tool. The document demonstrates importing various life science and disease datasets to create a COVID-19 knowledge graph in Neo4j in under 20 minutes. It encourages users to download Neo4j and n10s and link additional public data sources to explore applications like semantic search, knowledge discovery, and reconciliation.
An Algebraic Data Model for Graphs and Hypergraphs (Category Theory meetup, N...Joshua Shinavier
A presentation for the Category Theory meetup at Uber in San Francisco, November 21, 2019. A combination of previous slide shows motivating and presenting the Algebraic Property Graphs data model.
A Graph is a Graph is a Graph: Equivalence, Transformation, and Composition o...Joshua Shinavier
This document provides an overview of graphs and graph data models. It discusses how graphs can be represented as categories and how different data models like property graphs, RDF, and relational models are equivalent categories. It also describes common graph transformations between these models and discusses Uber's goal of building a knowledge graph to integrate their diverse datasets.
Not sure what RDF is and confused about or how it relates to Linked Data and the jargon surrounding it? This describes of what RDF as well as what you need to know to understand how it applies to library work.
Although you may not have heard of JavaScript Object Notation Linked Data (JSON-LD), it is already impacting your business. Search engine giants such as Google have mandated JSON-LD as a preferred means of adding structured data to web pages to make them considerably easier to parse for more accurate search engine results. The Google use case is indicative of the larger capacity for JSON-LD to increase web traffic for sites and better guide users to the results they want.
Expectations are high for (JSON-LD), and with good reason. JSON-LD effectively delivers the many benefits of JSON, a lightweight data interchange format, into the linked data world. Linked data is the technological approach supporting the World Wide Web and one of the most effective means of sharing data ever devised.
In addition, the growing number of enterprise knowledge graphs fully exploit the potential of JSON-LD as it enables organizations to readily access data stored in document formats and a variety of semi-structured and unstructured data as well. By using this technology to link internal and external data, knowledge graphs exemplify the linked data approach underpinning the growing adoption of JSON-LD—and the demonstrable, recurring business value that linked data consistently provides.
Join us learn more about optimizing the unique Document and Graph Database capabilities provided by AllegroGraph to develop or enhance your Enterprise Knowledge Graph using JSON-LD.
This document summarizes a presentation about visualizing data in time and space dimensions. It discusses exploring temporal and spatial aspects in humanities scholarship. It provides examples of tools for browsing objects using time and location, visualizing data on maps, and timelines. It also covers principles of working with time series and geospatial data, including processing, analysis, and combining statistical and geospatial data to identify patterns. Finally, it presents tools for refining, manipulating, and integrating spatial and temporal data in exhibits and digital projects.
This document discusses time-space mapping techniques in architecture and urban planning. It provides an overview of time-space visualization principles, including indicating time in maps, activity patterns, isochronic maps, tempographic maps, and rhythm maps. Examples of classic time-space maps are shown, such as Minard's 1861 map of Napoleon's march and retreat from Moscow, Chombart de Lauwe's 1957 map of daily activity patterns in Paris, and Galton's 1881 map showing the time required to travel between London parishes.
Mapping at “Object Geographies: Dis-assembly / Re-assembly Workshop in Art and Architecture” class at ACT in MIT.
A similar lecture, Civic Maps using this slides could be seen at the video-round table that took place at MIT Media Lab on October 20th 2011: http://civic.mit.edu/event/civic-media-session-civic-maps
Unfolding - A Library for Interactive Maps and GeovisualizationsTill Nagel
Presentation at the SouthCHI 2013 conference in Maribor, Slovenia.
Won a Best Presentation Award.
More information on Unfolding at http://unfoldingmaps.org
This document discusses various techniques for visualizing urban data to better understand cities. It describes projects like Splendor which uses crowd-sourced data, Venice Unfolding which engages local stakeholders, and LiquiData which expands the social space. The document also discusses visualizing transit patterns in Singapore, bike routes in Berlin, and metro flows in Shanghai. The overall goals of urban data visualization are represented as representing the city, raising awareness, supporting decision making, and improving daily life.
Content Design, UI Architecture and UI MappingWolfram Nagel
When you want to gather, manage and publish content and display it independently on any user interface and/or target channel you need a system that supports “Content Design and Content UI Mapping”. Content and user interfaces can be planned and assembled modularly and structured in a similar manner — comparable to bricks in a building block system. Content basically runs through three steps until it reaches its recipient: Gathering, management and output. A mapping has to occure at the intersections of these three steps. There's also an extended version with more and detailed slides available. And here's an article on the topic: https://medium.com/@wolframnagel/content-design-and-ui-mapping-a35af8cac3f6#.3ylkxrakf
This document provides information on different types of mapping, including cognitive mapping, behavioural mapping, and activity mapping. It discusses cognitive mapping as the process of encoding, storing, and manipulating experienced spatial information. Behavioural mapping is described as an objective method to observe and link human behavior to built environment attributes. Activity mapping involves recording the patterns and types of activities that people engage in within a space on a map. The document provides details on how to approach and represent each type of mapping to understand human spatial behavior and perceptions.
Content Design, UI Architecture and Content-UI-MappingWolfram Nagel
When you want to gather, manage and publish content and display it independently on any user interface and/or target channel you need a system that supports “Content Design and Content UI Mapping”. Content and user interfaces can be planned and assembled modularly and structured in a similar manner — comparable to bricks in a building block system. Content basically runs through three steps until it reaches its recipient: Gathering, management and output. A mapping has to occure at the intersections of these three steps.
This is the extended slides version on the topic.
There's also an article on the topic: https://medium.com/@wolframnagel/content-design-and-ui-mapping-a35af8cac3f6#.3ylkxrakf
This document discusses various architectural styles including data-centered, data-flow, call and return, layered, and client-server architectures. It explains how to map a data flow diagram (DFD) showing transform or transaction flows to a call and return architecture. Examples are provided of mapping transform and transaction flows from DFDs to the corresponding call and return architecture. Homework tasks are assigned to map DFDs for course registration and temperature monitoring systems to a call and return architecture.
Information Architecture: Making Information Accessible and Usefulfrog
This is a talk about how designers can help people make use of information—both find and act upon it.
To illustrate this, I take a trip to the SFMOMA to share the work of Dieter Rams, whose ethos of "Less, but better" is a challenge to any designer seeking to create better websites and applications.
I re-explore this trip multiple times over the course of the talk, considering the overlap of information in physical and digital systems—and how conceptually we merge them.
From there, I provide best practices and principles for how to approach information architecture and user experience design in a more iterative, agile fashion through in-line prototyping.
The document discusses the history and development of artificial intelligence over the past 70 years, from early research into neural networks in the 1940s to modern deep learning techniques. While AI has made tremendous progress, fully human-level AI remains challenging to achieve and raises complex issues around safety, ethics, and its impact on society that require careful consideration and oversight. Overall progress in AI has occurred in steps by incorporating more data and modeling increasingly complex phenomena, but fully general human intelligence remains a long-term goal that will require ongoing research.
This document summarizes Sebastian Hellmann's PhD thesis on integrating natural language processing (NLP) data, tools, and applications with RDF and OWL. The thesis proposes creating datasets in RDF to facilitate data integration and linking. It describes converting Wiktionary and the Wortschatz corpus to RDF to create a linguistic linked data web. Standardized formats like POWLA are discussed for representing corpora on the web. The thesis also covers knowledge acquisition from resources like the Tiger Corpus Navigator and ontology learning from text using techniques like LExO.
This document compares three APIs for processing RDF in the .NET Framework: SemWeb, LinqToRdf, and Rowlex. SemWeb provides low-level RDF interaction and the others build on it. LinqToRdf allows LINQ querying of RDF graphs while Rowlex maps RDF triples to object-oriented classes. All three APIs lack documentation and support as they were last updated in 2008-2009. SemWeb has the best performance while LinqToRdf has the lowest due to additional processing of LINQ queries to SPARQL.
Semantic Web: From Representations to ApplicationsGuus Schreiber
This document discusses semantic web representations and applications. It provides an overview of the W3C Web Ontology Working Group and Semantic Web Best Practices and Deployment Working Group, including their goals and key issues addressed. Examples of semantic web applications are also described, such as using ontologies to integrate information from heterogeneous cultural heritage sources.
This document provides an overview of a tutorial on semantic digital libraries. The tutorial will introduce semantic web technologies and how they can be applied to digital libraries. It will present existing semantic digital library systems, discuss current problems and future directions, and include hands-on sessions for participants. Attendees will learn about semantic digital libraries, existing solutions, and how to run semantic digital library solutions on their own machines.
This document discusses semantic technologies and digital data processing. It provides an overview of semantics and the semantic web, including XML, RDF, OWL, SPARQL, ontologies, and data models. It also discusses capturing semantics in XML documents, OWL, RDF schema, semantic web applications like cartographic searching, SKOS for knowledge organization systems, and the SKOS Play visualization tool.
The document provides an overview of a tutorial on semantic digital libraries. It introduces the speakers and schedule, which includes an introduction to semantic digital libraries and existing solutions, followed by discussions on conclusions and future directions. It also briefly covers the semantic web, ontologies, RDF, and how these technologies can help digital libraries by making metadata machine-understandable.
Innovative methods for data integration: Linked Data and NLPariadnenetwork
Linked Data (LD) + Natural Language Processing (NLP)
Two technologies that open up new possibilities for semantic integration of archaeological datasets and fieldwork reports.
Overview
•Illustrative early examples
- a flavour of progress and challenges to date
•NLP of grey literature (English – Dutch)
•Mapping between multilingual vocabularies
RDF and the Semantic Web are building blocks for representing data on the World Wide Web in a structured and linked manner. RDF uses triples of subject-predicate-object to describe resources, allowing data to be interlinked and combined across different schemas. This facilitates interoperability between web applications and enables machines to more easily process information at a global scale. While RDF syntax can be clunky, it provides a flexible and extensible framework for exchanging machine-readable metadata. The development of a global network of interlinked data accessed by intelligent programs remains a goal of the Semantic Web.
The Datalift Project aims to publish and interconnect government open data. It develops tools and methodologies to transform raw datasets into interconnected semantic data. The project's first phase focuses on opening data by developing an infrastructure to ease publication. The second phase will validate the platform by publishing real datasets. The goal of Datalift is to move data from its raw published state to being fully interconnected on the Semantic Web.
Rdf and open linked data a first approach @CULT Srl
The document discusses challenges and opportunities for libraries to publish their data as linked open data on the semantic web. It provides examples of libraries that have begun publishing authority files, catalog data, and thesauri as linked open data. The document also outlines advantages of the semantic web for libraries and potential applications that could make use of linked library data.
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.
Digital libraries of the future will use semantic web and social bookmarking technologies to support e-learning. Semantic digital libraries integrate information from different metadata sources to provide more robust search and browsing interfaces. They describe resources in a machine-understandable way using ontologies and expose semantics to enable interoperability between systems. This allows new search paradigms like ontology-based search and helps integrate metadata from different sources.
These slides were presented as part of a W3C tutorial at the CSHALS 2010 conference (http://www.iscb.org/cshals2010). The slides are adapted from a longer introduction to the Semantic Web available at http://www.slideshare.net/LeeFeigenbaum/semantic-web-landscape-2009 .
A PDF version of the slides is available at http://thefigtrees.net/lee/sw/cshals/cshals-w3c-semantic-web-tutorial.pdf .
Although animals do not use language, they are capable of many of the same kinds of cognition as us; much of our experience is at a non-verbal level.
Semantics is the bridge between surface forms used in language and what we do and experience.
Language understanding depends on world knowledge (i.e. “the pig is in the pen” vs. “the ink is in the pen”)
We might not be ready for executives to specify policies themselves, but we can make the process from specification to behavior more automated, linked to precise vocabulary, and more traceable.
Advances such as SVBR and an English serialization for ISO Common Logic means that executives and line workers can understand why the system does certain things, or verify that policies and regulations are implemented
The document defines key terms related to semantic technologies and the semantic web including:
- Linked Open Data (LOD) which publishes open data according to semantic web standards and links it to other sources to create a web of data.
- LOD2, an EU project developing infrastructure for building LOD.
- OWL, a language for more expressive semantic modeling.
- R2RML, a standard for mapping data in relational databases to RDF.
- RDF, the standard data model using triples to represent information.
The WESO Research Group is located at the University of Oviedo in Spain and focuses on applying semantic web technologies. It has 4 associate professors and 6 students working on projects related to linked open data, semantic search, knowledge graphs, and using semantic web techniques in domains like legal documents, procurement notices, and measuring the impact of the web. The researcher's interests include linked open data, reasoning over large graphs in the cloud, and functional programming.
Semantic Interoperability - grafi della conoscenzaGiorgia Lodi
This document summarizes Giorgia Lodi's presentation on meaningful data and semantic interoperability in the Italian public sector. Lodi discusses issues with data quality such as missing values, semantics mismatches, and use of strings instead of codes. She argues that adopting semantic web standards like RDF, OWL and SPARQL can help address these issues by linking data together and representing it semantically. Ontologies and knowledge graphs can be used to represent domain knowledge and infer new facts. Tools like FRED can generate knowledge graphs from unstructured text. Overall, Lodi argues that semantic web technologies have the potential to improve data interoperability and quality in the public sector, though challenges remain.
Similar to Semantic Cartography: Using ontologies to create adaptable tools for text exploration (20)
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).
Salesforce Integration for Bonterra Impact Management (fka Social Solutions A...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on integration of Salesforce with Bonterra Impact Management.
Interested in deploying an integration with Salesforce for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
A Comprehensive Guide to DeFi Development Services in 2024Intelisync
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!
Best 20 SEO Techniques To Improve Website Visibility In SERPPixlogix Infotech
Boost your website's visibility with proven SEO techniques! Our latest blog dives into essential strategies to enhance your online presence, increase traffic, and rank higher on search engines. From keyword optimization to quality content creation, learn how to make your site stand out in the crowded digital landscape. Discover actionable tips and expert insights to elevate your SEO game.
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
Digital Marketing Trends in 2024 | Guide for Staying AheadWask
https://www.wask.co/ebooks/digital-marketing-trends-in-2024
Feeling lost in the digital marketing whirlwind of 2024? Technology is changing, consumer habits are evolving, and staying ahead of the curve feels like a never-ending pursuit. This e-book is your compass. Dive into actionable insights to handle the complexities of modern marketing. From hyper-personalization to the power of user-generated content, learn how to build long-term relationships with your audience and unlock the secrets to success in the ever-shifting digital landscape.
In the realm of cybersecurity, offensive security practices act as a critical shield. By simulating real-world attacks in a controlled environment, these techniques expose vulnerabilities before malicious actors can exploit them. This proactive approach allows manufacturers to identify and fix weaknesses, significantly enhancing system security.
This presentation delves into the development of a system designed to mimic Galileo's Open Service signal using software-defined radio (SDR) technology. We'll begin with a foundational overview of both Global Navigation Satellite Systems (GNSS) and the intricacies of digital signal processing.
The presentation culminates in a live demonstration. We'll showcase the manipulation of Galileo's Open Service pilot signal, simulating an attack on various software and hardware systems. This practical demonstration serves to highlight the potential consequences of unaddressed vulnerabilities, emphasizing the importance of offensive security practices in safeguarding critical infrastructure.
Driving Business Innovation: Latest Generative AI Advancements & Success StorySafe Software
Are you ready to revolutionize how you handle data? Join us for a webinar where we’ll bring you up to speed with the latest advancements in Generative AI technology and discover how leveraging FME with tools from giants like Google Gemini, Amazon, and Microsoft OpenAI can supercharge your workflow efficiency.
During the hour, we’ll take you through:
Guest Speaker Segment with Hannah Barrington: Dive into the world of dynamic real estate marketing with Hannah, the Marketing Manager at Workspace Group. Hear firsthand how their team generates engaging descriptions for thousands of office units by integrating diverse data sources—from PDF floorplans to web pages—using FME transformers, like OpenAIVisionConnector and AnthropicVisionConnector. This use case will show you how GenAI can streamline content creation for marketing across the board.
Ollama Use Case: Learn how Scenario Specialist Dmitri Bagh has utilized Ollama within FME to input data, create custom models, and enhance security protocols. This segment will include demos to illustrate the full capabilities of FME in AI-driven processes.
Custom AI Models: Discover how to leverage FME to build personalized AI models using your data. Whether it’s populating a model with local data for added security or integrating public AI tools, find out how FME facilitates a versatile and secure approach to AI.
We’ll wrap up with a live Q&A session where you can engage with our experts on your specific use cases, and learn more about optimizing your data workflows with AI.
This webinar is ideal for professionals seeking to harness the power of AI within their data management systems while ensuring high levels of customization and security. Whether you're a novice or an expert, gain actionable insights and strategies to elevate your data processes. Join us to see how FME and AI can revolutionize how you work with data!
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
GraphRAG for Life Science to increase LLM accuracyTomaz Bratanic
GraphRAG for life science domain, where you retriever information from biomedical knowledge graphs using LLMs to increase the accuracy and performance of generated answers
Main news related to the CCS TSI 2023 (2023/1695)Jakub Marek
An English 🇬🇧 translation of a presentation to the speech I gave about the main changes brought by CCS TSI 2023 at the biggest Czech conference on Communications and signalling systems on Railways, which was held in Clarion Hotel Olomouc from 7th to 9th November 2023 (konferenceszt.cz). Attended by around 500 participants and 200 on-line followers.
The original Czech 🇨🇿 version of the presentation can be found here: https://www.slideshare.net/slideshow/hlavni-novinky-souvisejici-s-ccs-tsi-2023-2023-1695/269688092 .
The videorecording (in Czech) from the presentation is available here: https://youtu.be/WzjJWm4IyPk?si=SImb06tuXGb30BEH .
How to Interpret Trends in the Kalyan Rajdhani Mix Chart.pdfChart Kalyan
A Mix Chart displays historical data of numbers in a graphical or tabular form. The Kalyan Rajdhani Mix Chart specifically shows the results of a sequence of numbers over different periods.
5th LF Energy Power Grid Model Meet-up SlidesDanBrown980551
5th Power Grid Model Meet-up
It is with great pleasure that we extend to you an invitation to the 5th Power Grid Model Meet-up, scheduled for 6th June 2024. This event will adopt a hybrid format, allowing participants to join us either through an online Mircosoft Teams session or in person at TU/e located at Den Dolech 2, Eindhoven, Netherlands. The meet-up will be hosted by Eindhoven University of Technology (TU/e), a research university specializing in engineering science & technology.
Power Grid Model
The global energy transition is placing new and unprecedented demands on Distribution System Operators (DSOs). Alongside upgrades to grid capacity, processes such as digitization, capacity optimization, and congestion management are becoming vital for delivering reliable services.
Power Grid Model is an open source project from Linux Foundation Energy and provides a calculation engine that is increasingly essential for DSOs. It offers a standards-based foundation enabling real-time power systems analysis, simulations of electrical power grids, and sophisticated what-if analysis. In addition, it enables in-depth studies and analysis of the electrical power grid’s behavior and performance. This comprehensive model incorporates essential factors such as power generation capacity, electrical losses, voltage levels, power flows, and system stability.
Power Grid Model is currently being applied in a wide variety of use cases, including grid planning, expansion, reliability, and congestion studies. It can also help in analyzing the impact of renewable energy integration, assessing the effects of disturbances or faults, and developing strategies for grid control and optimization.
What to expect
For the upcoming meetup we are organizing, we have an exciting lineup of activities planned:
-Insightful presentations covering two practical applications of the Power Grid Model.
-An update on the latest advancements in Power Grid -Model technology during the first and second quarters of 2024.
-An interactive brainstorming session to discuss and propose new feature requests.
-An opportunity to connect with fellow Power Grid Model enthusiasts and users.
2. TEI and SEASR SEASR: Software Environment for the Advancement of Scholarly Research NEH Digital Humanities Start-Up Grant to develop a set of SEASR tools for exploring TEI-encoded texts.
5. Problem: How do we handle variability in the incoming TEI due to: Idiosyncratic encoding Inconsistent encoding TEI’s native flexibility
6. Semantic Mapping using Ontologies RDF uses ontologies (RDFS/OWL) to associate a piece of data with a conceptual framework: Example: xmlns:dbo=http://dbpedia.org/ontology/ Class: dbo:populatedPlace Subclass: dbo:country Instance: “Spain”
7. Ontological definition Understands Is RDF “Slice”[1] Software The Semantic Map allows any software that can interpret RDF to work with any semantic idea that can be associated with an ontological definition. 1http://rdftef.sourceforge.net/