The document discusses using uniform resource locators (URLs) and pipelines of processors to enable dynamic conversion between different structured content formats. Consistent structure is important for enabling automatic processing. URLs can encode conversion pipelines so that content like Excel files can be referenced in DITA topics and other XML documents through simple URLs. This allows for cross-format publishing and editing content in one format that can be saved in another.
RDF/XML is a format for representing data in RDF, which is a model for structuring metadata. RDF/XML serializes RDF graphs into XML documents so they can be processed by computers. Properties and values in RDF are expressed as elements and attributes in RDF/XML. While RDF/XML allows RDF data to be expressed in XML, it is not very human-readable and other formats like Turtle and JSON may be better for processing by machines and developers.
SPARQL is a standardized query language for retrieving and manipulating data stored in RDF format. It was created by the RDF Data Access Working Group to provide querying of RDF stores. SPARQL supports four query forms: SELECT, CONSTRUCT, DESCRIBE, and ASK. It also defines a protocol for executing queries over HTTP. SPARQL has become a key technology for working with semantic data on the web.
Building Self Documenting HTTP APIs with CQRSDerek Comartin
Does your HTTP API expose your database structure?
HTTP endpoints that represent your database entities couples your consuming clients to the internals of your application. Making it much harder to change your API.
Go beyond serializing a database row into json by leveraging CQRS.
Start designing an HTTP API like a regular HTML website. Bringing the concepts of HTML links and forms to your API allows your clients to consume it with ease.
Attendees will learn how to design an HTTP API by leveraging CQRS and hypermedia to decouple their core application from their HTTP API.
There are 4 SPARQL query forms: SELECT, ASK, CONSTRUCT, and DESCRIBE. Each form serves a different purpose. SELECT returns variable bindings and is equivalent to an SQL SELECT query. ASK returns a boolean for whether a pattern matches or not. CONSTRUCT returns an RDF graph constructed from templates. DESCRIBE returns an RDF graph that describes resources found. Beyond their basic uses, the forms can be used for tasks like indexing, transformation, validation, and prototyping user interfaces.
This document discusses a resource-oriented approach to data services using REST, Python and RDF. It describes how data can be transformed into data services by creating data resources that represent the data and can be composed into transformation pipelines. The pipelines themselves are also represented as resources, allowing new data services to be incrementally composed from existing ones. The document also provides an overview of the SnapLogic open source data integration toolkit.
The document discusses how data models and technologies change over time, but constants are needed to maintain meaning. It describes how different data models like tables, databases and XML each deal differently with changes. While the RDF model is flexible, changes in data or schemas still require changes in identifiers and symbols used in machine interfaces. To maintain meaning, unique identifiers, ontologies and resources need to remain constant as technologies and models evolve. Promises are needed to ensure these constants endure despite changes.
What Factors Influence the Design of a Linked Data Generation Algorithm?andimou
Generating Linked Data remains a complicated and intensive engineering process. While different factors determine how a Linked Data generation algorithm is designed, potential alternatives for each factor are currently not considered when designing the tools’ underlying algorithms. Certain design patterns are frequently ap- plied across different tools, covering certain alternatives of a few of these factors, whereas other alternatives are never explored. Consequently, there are no adequate tools for Linked Data generation for certain occasions, or tools with inadequate and inefficient algorithms are chosen. In this position paper, we determine such factors, based on our experiences, and present a preliminary list. These factors could be considered when a Linked Data generation algorithm is designed or a tool is chosen. We investigated which factors are covered by widely known Linked Data generation tools and concluded that only certain design patterns are frequently encountered. By these means, we aim to point out that Linked Data generation is above and beyond bare implementations, and algorithms need to be thoroughly and systematically studied and exploited.
The document discusses using uniform resource locators (URLs) and pipelines of processors to enable dynamic conversion between different structured content formats. Consistent structure is important for enabling automatic processing. URLs can encode conversion pipelines so that content like Excel files can be referenced in DITA topics and other XML documents through simple URLs. This allows for cross-format publishing and editing content in one format that can be saved in another.
RDF/XML is a format for representing data in RDF, which is a model for structuring metadata. RDF/XML serializes RDF graphs into XML documents so they can be processed by computers. Properties and values in RDF are expressed as elements and attributes in RDF/XML. While RDF/XML allows RDF data to be expressed in XML, it is not very human-readable and other formats like Turtle and JSON may be better for processing by machines and developers.
SPARQL is a standardized query language for retrieving and manipulating data stored in RDF format. It was created by the RDF Data Access Working Group to provide querying of RDF stores. SPARQL supports four query forms: SELECT, CONSTRUCT, DESCRIBE, and ASK. It also defines a protocol for executing queries over HTTP. SPARQL has become a key technology for working with semantic data on the web.
Building Self Documenting HTTP APIs with CQRSDerek Comartin
Does your HTTP API expose your database structure?
HTTP endpoints that represent your database entities couples your consuming clients to the internals of your application. Making it much harder to change your API.
Go beyond serializing a database row into json by leveraging CQRS.
Start designing an HTTP API like a regular HTML website. Bringing the concepts of HTML links and forms to your API allows your clients to consume it with ease.
Attendees will learn how to design an HTTP API by leveraging CQRS and hypermedia to decouple their core application from their HTTP API.
There are 4 SPARQL query forms: SELECT, ASK, CONSTRUCT, and DESCRIBE. Each form serves a different purpose. SELECT returns variable bindings and is equivalent to an SQL SELECT query. ASK returns a boolean for whether a pattern matches or not. CONSTRUCT returns an RDF graph constructed from templates. DESCRIBE returns an RDF graph that describes resources found. Beyond their basic uses, the forms can be used for tasks like indexing, transformation, validation, and prototyping user interfaces.
This document discusses a resource-oriented approach to data services using REST, Python and RDF. It describes how data can be transformed into data services by creating data resources that represent the data and can be composed into transformation pipelines. The pipelines themselves are also represented as resources, allowing new data services to be incrementally composed from existing ones. The document also provides an overview of the SnapLogic open source data integration toolkit.
The document discusses how data models and technologies change over time, but constants are needed to maintain meaning. It describes how different data models like tables, databases and XML each deal differently with changes. While the RDF model is flexible, changes in data or schemas still require changes in identifiers and symbols used in machine interfaces. To maintain meaning, unique identifiers, ontologies and resources need to remain constant as technologies and models evolve. Promises are needed to ensure these constants endure despite changes.
What Factors Influence the Design of a Linked Data Generation Algorithm?andimou
Generating Linked Data remains a complicated and intensive engineering process. While different factors determine how a Linked Data generation algorithm is designed, potential alternatives for each factor are currently not considered when designing the tools’ underlying algorithms. Certain design patterns are frequently ap- plied across different tools, covering certain alternatives of a few of these factors, whereas other alternatives are never explored. Consequently, there are no adequate tools for Linked Data generation for certain occasions, or tools with inadequate and inefficient algorithms are chosen. In this position paper, we determine such factors, based on our experiences, and present a preliminary list. These factors could be considered when a Linked Data generation algorithm is designed or a tool is chosen. We investigated which factors are covered by widely known Linked Data generation tools and concluded that only certain design patterns are frequently encountered. By these means, we aim to point out that Linked Data generation is above and beyond bare implementations, and algorithms need to be thoroughly and systematically studied and exploited.
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.
The document discusses approaches for building APIs over RDF data sources. It describes limitations of SPARQL and proposes the Linked Data API approach, which maps parameterized URLs to SPARQL queries to extract data views. The Linked Data API aims to optimize for common query patterns, prioritize simple RESTful interactions, and provide a pathway to exploring RDF and SPARQL. It presents a processing model involving selecting views, resources, and output formats. Open source implementations of the Linked Data API are also mentioned.
Update from the W3C Web Annotation Working Group on its progress towards establishing a data model, vocabulary, serialization, and interaction protocol for digital annotation.
Linked Data Driven Data Virtualization for Web-scale Integrationrumito
- Linked data and data virtualization can help address challenges of growing data heterogeneity, complexity, and need for agility by providing a common data model and identifiers.
- Linked data uses RDF to represent information as graphs of triples connected by URIs, allowing different data sources to be integrated and queried together.
- As more data is published using common vocabularies and linking to existing URIs, it increases opportunities for discovery, integration and novel ways to extract value from diverse data sources.
In today's world, we cannot expect to find a single format for information across an enterprise. People write spreadsheets, markdown, HTML, comments within the source code of different programming languages, structured XML based documents, and so on. This makes it very difficult to publish — as a single publication — content that originates in different formats, without re-encoding that in a common format. We propose the use of URLs to dynamically convert content from one format to another, thus we avoid duplicating information and realize single source publishing across multiple formats.
As long as the information has a structure that is machine processable, we should be able to convert from one form of encoding to another. For example, if you have a table encoded as an Excel sheet then you can get a DITA topic out of that just by referring to that file with a URL like "excel2dita:/path/to/excel/file.xls".
To test how this actually works, we implemented such URLs that perform dynamic conversions for:
Excel to DITA
Google Sheets to DITA
JavaDoc to DITA
Java source to DITA
Markdown to DITA
HTML to DITA Custom
XML format to SVG
Comma Separated Values to DITA and back (to test also round-tripping support)
Basically, with this simple dynamic conversion technology (just use a URL to point to files in different format and get them as DITA or some other format) we can bridge between formats with advantages of avoiding duplicating content and thus reducing work and potential errors and being able to provide a unified publishing framework across different formats.
This presentation was given at Information Development World on October 2, 2015.
This document discusses using smart SPARQL agents to distribute reasoning over linked data. The agents can outsource reasoning to infrastructure like client-side, server-side, or third-party reasoning services. This allows reasoning to be performed as a service. Reasoned SPARQL allows data consumers to choose inference rules for querying distributed data. Nested queries and workload balancing techniques are also described.
1) The author developed a connector to integrate the Sirsi ILS with Drupal by writing PHP classes to access Sirsi APIs and return bibliographic and patron data as structured data.
2) The connector uses three PHP classes - one to gather patron data from Sirsi, one to perform actions like renewals and holds, and one to return bibliographic data.
3) To improve performance, a MARC server was created to run the catalogdump process continuously rather than spawning a new process for each request, reducing response time for bibliographic data.
ELUNA2013:Providing Voyager catalog data in a custom, open source web applica...Michael Cummings
Providing Voyager catalog data in a custom, open source web application, "Launchpad" outlines the features of customized library catalog software application from the George Washington University.
Initial Usage Analysis of DBpedia's Triple Pattern FragmentsRuben Verborgh
The document summarizes an analysis of the usage of DBpedia's Triple Pattern Fragments interface between November 2014 and February 2015. Over 4 million requests were made to the interface with 99.9994% uptime. The top clients were the TPF client library, crawlers and Chrome browser. Most requests came from Europe, US and China. The analysis found the interface provided highly available querying of DBpedia's data but more work is needed to understand specific queries and build applications for end users.
DC-2008 Tutorial 3 - Dublin Core and other metadata schemasMikael Nilsson
The document discusses metadata standards and interoperability. It provides an overview of Dublin Core and other metadata schemas. It describes how Dublin Core terms are defined both for human understanding through textual definitions, as well as machine understanding through formal semantics expressed in RDF. This allows metadata using Dublin Core terms to be combined and processed in an interoperable way on the Semantic Web.
The document discusses the concepts of linked data, how it can be created and deployed from various data sources, and how it can be exploited. Linked data allows accessing data on the web by reference using HTTP-based URIs and RDF, forming a giant global graph. It can be generated from existing web pages, services, databases and content, and deployed using a linked data server. Exploiting linked data allows discovery, integration and conceptual interaction across silos of heterogeneous data on the web and in enterprises.
Comparative Study That Aims Rdf Processing For The Java PlatformComputer Science
This document provides a comparative study of popular Java APIs for processing Resource Description Framework (RDF) data. It summarizes four main APIs: JRDF, Sesame, and Jena. For each API, it describes key features like storage methods, query support, documentation, and license. It finds that while each API has strengths, Sesame and Jena tend to have richer documentation and more developed feature sets than JRDF. The study aims to help Java developers choose the best RDF processing API for their needs.
The document discusses the need for standardized protocols to enable communication between semantic web clients and servers. It proposes two such protocols: RDF Net API and Topic Map Fragment Processing. RDF Net API defines operations like query, get statements, insert statements, and remove statements. It also defines HTTP and SOAP bindings. Topic Map Fragment Processing allows clients to retrieve and update fragments of topic maps. These protocols aim to fulfill the requirements for semantic web servers to enable querying, updating, and interacting with semantic web data in a distributed environment.
Discussion of the needs around updating Shared Canvas data model for IIIF's Presentation API, and aligning with new work such as the Web Annotation specs.
The document discusses leveraging library authority control and controlled vocabularies on the semantic web. It describes converting existing metadata like Library of Congress Subject Headings (LCSH) into semantic web standards like SKOS to make the data accessible and linkable on the web. This would allow libraries to publish and share authority and classification data using common web technologies, enabling new applications and discovery across systems.
Deploying PHP applications using Virtuoso as Application Serverwebhostingguy
Virtuoso can act as an application server for PHP applications, providing both web server and database functionality. It exposes application data as RDF, allowing for more advanced querying across applications. Existing PHP applications like PHPBB, Drupal, and WordPress have been set up to work with Virtuoso and expose their data as RDF through a mapping process. Developers can build Virtuoso from source to include PHP support, enabling the hosting of PHP applications and accessing of application data as RDF through a SPARQL endpoint.
This tutorial explains the Data Web vision, some preliminary standards and technologies as well as some tools and technological building blocks developed by AKSW research group from Universität Leipzig.
Modern PHP RDF toolkits: a comparative studyMarius Butuc
This work presents a comparative study on the RDF processing APIs implemented in PHP. We took into consideration diferent
criteria including, but not limited to: the solution for storing RDF statements, the support for SPARQL queries, performance, interoperability,
and implementation maturity.
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.
The document discusses approaches for building APIs over RDF data sources. It describes limitations of SPARQL and proposes the Linked Data API approach, which maps parameterized URLs to SPARQL queries to extract data views. The Linked Data API aims to optimize for common query patterns, prioritize simple RESTful interactions, and provide a pathway to exploring RDF and SPARQL. It presents a processing model involving selecting views, resources, and output formats. Open source implementations of the Linked Data API are also mentioned.
Update from the W3C Web Annotation Working Group on its progress towards establishing a data model, vocabulary, serialization, and interaction protocol for digital annotation.
Linked Data Driven Data Virtualization for Web-scale Integrationrumito
- Linked data and data virtualization can help address challenges of growing data heterogeneity, complexity, and need for agility by providing a common data model and identifiers.
- Linked data uses RDF to represent information as graphs of triples connected by URIs, allowing different data sources to be integrated and queried together.
- As more data is published using common vocabularies and linking to existing URIs, it increases opportunities for discovery, integration and novel ways to extract value from diverse data sources.
In today's world, we cannot expect to find a single format for information across an enterprise. People write spreadsheets, markdown, HTML, comments within the source code of different programming languages, structured XML based documents, and so on. This makes it very difficult to publish — as a single publication — content that originates in different formats, without re-encoding that in a common format. We propose the use of URLs to dynamically convert content from one format to another, thus we avoid duplicating information and realize single source publishing across multiple formats.
As long as the information has a structure that is machine processable, we should be able to convert from one form of encoding to another. For example, if you have a table encoded as an Excel sheet then you can get a DITA topic out of that just by referring to that file with a URL like "excel2dita:/path/to/excel/file.xls".
To test how this actually works, we implemented such URLs that perform dynamic conversions for:
Excel to DITA
Google Sheets to DITA
JavaDoc to DITA
Java source to DITA
Markdown to DITA
HTML to DITA Custom
XML format to SVG
Comma Separated Values to DITA and back (to test also round-tripping support)
Basically, with this simple dynamic conversion technology (just use a URL to point to files in different format and get them as DITA or some other format) we can bridge between formats with advantages of avoiding duplicating content and thus reducing work and potential errors and being able to provide a unified publishing framework across different formats.
This presentation was given at Information Development World on October 2, 2015.
This document discusses using smart SPARQL agents to distribute reasoning over linked data. The agents can outsource reasoning to infrastructure like client-side, server-side, or third-party reasoning services. This allows reasoning to be performed as a service. Reasoned SPARQL allows data consumers to choose inference rules for querying distributed data. Nested queries and workload balancing techniques are also described.
1) The author developed a connector to integrate the Sirsi ILS with Drupal by writing PHP classes to access Sirsi APIs and return bibliographic and patron data as structured data.
2) The connector uses three PHP classes - one to gather patron data from Sirsi, one to perform actions like renewals and holds, and one to return bibliographic data.
3) To improve performance, a MARC server was created to run the catalogdump process continuously rather than spawning a new process for each request, reducing response time for bibliographic data.
ELUNA2013:Providing Voyager catalog data in a custom, open source web applica...Michael Cummings
Providing Voyager catalog data in a custom, open source web application, "Launchpad" outlines the features of customized library catalog software application from the George Washington University.
Initial Usage Analysis of DBpedia's Triple Pattern FragmentsRuben Verborgh
The document summarizes an analysis of the usage of DBpedia's Triple Pattern Fragments interface between November 2014 and February 2015. Over 4 million requests were made to the interface with 99.9994% uptime. The top clients were the TPF client library, crawlers and Chrome browser. Most requests came from Europe, US and China. The analysis found the interface provided highly available querying of DBpedia's data but more work is needed to understand specific queries and build applications for end users.
DC-2008 Tutorial 3 - Dublin Core and other metadata schemasMikael Nilsson
The document discusses metadata standards and interoperability. It provides an overview of Dublin Core and other metadata schemas. It describes how Dublin Core terms are defined both for human understanding through textual definitions, as well as machine understanding through formal semantics expressed in RDF. This allows metadata using Dublin Core terms to be combined and processed in an interoperable way on the Semantic Web.
The document discusses the concepts of linked data, how it can be created and deployed from various data sources, and how it can be exploited. Linked data allows accessing data on the web by reference using HTTP-based URIs and RDF, forming a giant global graph. It can be generated from existing web pages, services, databases and content, and deployed using a linked data server. Exploiting linked data allows discovery, integration and conceptual interaction across silos of heterogeneous data on the web and in enterprises.
Comparative Study That Aims Rdf Processing For The Java PlatformComputer Science
This document provides a comparative study of popular Java APIs for processing Resource Description Framework (RDF) data. It summarizes four main APIs: JRDF, Sesame, and Jena. For each API, it describes key features like storage methods, query support, documentation, and license. It finds that while each API has strengths, Sesame and Jena tend to have richer documentation and more developed feature sets than JRDF. The study aims to help Java developers choose the best RDF processing API for their needs.
The document discusses the need for standardized protocols to enable communication between semantic web clients and servers. It proposes two such protocols: RDF Net API and Topic Map Fragment Processing. RDF Net API defines operations like query, get statements, insert statements, and remove statements. It also defines HTTP and SOAP bindings. Topic Map Fragment Processing allows clients to retrieve and update fragments of topic maps. These protocols aim to fulfill the requirements for semantic web servers to enable querying, updating, and interacting with semantic web data in a distributed environment.
Discussion of the needs around updating Shared Canvas data model for IIIF's Presentation API, and aligning with new work such as the Web Annotation specs.
The document discusses leveraging library authority control and controlled vocabularies on the semantic web. It describes converting existing metadata like Library of Congress Subject Headings (LCSH) into semantic web standards like SKOS to make the data accessible and linkable on the web. This would allow libraries to publish and share authority and classification data using common web technologies, enabling new applications and discovery across systems.
Deploying PHP applications using Virtuoso as Application Serverwebhostingguy
Virtuoso can act as an application server for PHP applications, providing both web server and database functionality. It exposes application data as RDF, allowing for more advanced querying across applications. Existing PHP applications like PHPBB, Drupal, and WordPress have been set up to work with Virtuoso and expose their data as RDF through a mapping process. Developers can build Virtuoso from source to include PHP support, enabling the hosting of PHP applications and accessing of application data as RDF through a SPARQL endpoint.
This tutorial explains the Data Web vision, some preliminary standards and technologies as well as some tools and technological building blocks developed by AKSW research group from Universität Leipzig.
Modern PHP RDF toolkits: a comparative studyMarius Butuc
This work presents a comparative study on the RDF processing APIs implemented in PHP. We took into consideration diferent
criteria including, but not limited to: the solution for storing RDF statements, the support for SPARQL queries, performance, interoperability,
and implementation maturity.
The document discusses the concepts of the semantic web and linked data. It explains that the semantic web aims to convert the web into a single database that can be understood by machines through linking data using URIs, RDF, and other standards. It provides examples of projects like DBpedia and the Linking Open Data cloud that publish open government and other data as linked data. The document outlines some of the technologies and best practices for publishing and connecting data as linked data.
Publishing Linked Data 3/5 Semtech2011Juan Sequeda
This document summarizes techniques for publishing linked data on the web. It discusses publishing static RDF files, embedding RDF in HTML using RDFa, linking to other URIs, generating linked data from relational databases using RDB2RDF tools, publishing linked data from triplestores and APIs, hosting linked data in the cloud, and testing linked data quality.
The document proposes applying Linked Data principles to services and data streams. It suggests representing service inputs and outputs as Linked Data by encoding parameters in URIs and returning RDF data. For data streams, it recommends using HTTP as an access protocol and streaming RDF triples over an open HTTP connection. This would allow services and streams to be easily integrated and linked with other Linked Data on the web.
Epiphany: Adaptable RDFa Generation Linking the Web of Documents to the Web o...Benjamin Adrian
This presentation is about Epiphany, a system that automatically generates RDFa annotated versions of web pages based on information from Linked Data models.
This document provides an overview of the Semantic Web, RDF, SPARQL, and triplestores. It discusses how RDF structures and links data using subject-predicate-object triples. SPARQL is introduced as a standard query language for retrieving and manipulating data stored in RDF format. Popular triplestore implementations like Apache Jena and applications of linked data like DBPedia are also summarized.
The document introduces the Scholarly Works Application Profile (SWAP), which is a Dublin Core application profile for describing scholarly works held in institutional repositories. SWAP defines a model for scholarly works and their relationships using entities like ScholarlyWork, Expression, Manifestation, and Copy. It also specifies a set of metadata properties and an XML format for encoding and sharing metadata records between systems according to this model. The document provides an example of using SWAP to describe a scholarly work with multiple expressions, manifestations, and copies.
The document provides an overview of the Resource Description Framework (RDF). It describes RDF as a standard for describing web resources using metadata. RDF uses a simple data model based on making statements about resources in the form of subject-predicate-object expressions. This allows data to be shared across different applications. The document discusses key RDF concepts including resources, properties, and statements. It provides examples of RDF statements and illustrates the RDF triple format. The goal of RDF is to enable the encoding, exchange, and reuse of structured metadata about Web resources between applications.
The document discusses the Semantic Web, providing an overview of identification languages, integration, storage and querying, browsing and viewing technologies. It describes languages like RDF, RDF Schema and OWL, and how they add machine-understandable semantics and shared ontologies to the web. It also discusses tools for querying, visualizing and presenting Semantic Web data like SPARQL, RDF browsers, Fresnel lenses, and Yahoo Pipes for aggregating and filtering RDF feeds.
Semantic pipes aggregate data from multiple sources to create new data sources, similar to Yahoo! Pipes. Semantic pipes operate on RDF data sources using SPARQL queries. DERI Pipes is a tool for building semantic pipes that defines blocks for processing RDF and other data sources. Semantic mashups may have additional reasoning capabilities beyond basic data aggregation, using semantic web reasoners. They implement behavior through SPARQL queries over RDF data. Examples include mashups over Flickr, book data, and scholarly references.
The document discusses the history and architecture of the World Wide Web and semantic web. It describes how Tim Berners-Lee created the World Wide Web in 1989 at CERN. It outlines the key components of the web including URIs, URLs, HTTP, HTML, and web browsers. It then discusses the evolution of the semantic web and linked data, including the use of XML, RDF, RDFS, and OWL to represent metadata and link data on the web.
Web services can be accessed over a network and are called using HTTP. There are two main types: SOAP uses XML and is language/platform independent; REST uses URI to expose resources and can use JSON. Java has JAX-WS for SOAP and JAX-RS for RESTful services. REST is faster and uses less bandwidth than SOAP. The document discusses implementing REST services in Java using JAX-RS and Jersey, including using annotations and returning Response objects.
The document discusses representing data in the Resource Description Framework (RDF). It describes how relational data can be represented as RDF triples with rows becoming subjects, columns becoming properties, and values becoming objects. It also discusses using URIs instead of internal IDs and names to allow data integration. The document then covers serializing RDF data in different formats like RDF/XML, N-Triples, N3, and Turtle and describes syntax for representing literals, language tags, and abbreviating subject and predicate pairs.
The document discusses APIs and provides examples of RESTful APIs. It describes how RESTful APIs are built upon a domain model to provide resources that can be navigated through requests. This allows clients to construct custom requests to get precisely the data needed, rather than requiring multiple calls or getting excess data. The domain model also provides a unified framework for request and response semantics.
This document provides an agenda and overview of semantic web and linked open data. It discusses the limitations of the current internet and the goals of the semantic web, which aims to make web content machine-readable through annotation and ontologies. It introduces key semantic web technologies like RDF, RDF schema, and OWL, and explains how they allow data to be interlinked and queried. Open linked data seeks to further evolve the web by linking data on the web through common vocabularies and enabling new types of browsers and search engines to utilize this semantic information.
This document discusses the Semantic Web and Linked Data. It provides an overview of key Semantic Web technologies like RDF, URIs, and SPARQL. It also describes several popular Linked Data datasets including DBpedia, Freebase, Geonames, and government open data. Finally, it discusses the Yahoo BOSS search API and WebScope data for building search applications.
OpenCalais is a web service that analyzes text and generates semantic metadata about entities, events, and facts mentioned. It links these entities to datasets like DBpedia, Wikipedia, and Geonames using URIs. This allows the data to be interconnected and explored through the web of linked data. OpenCalais follows the principles of linked data by assigning HTTP URIs to entities and linking them to other open datasets. It returns the extracted metadata in RDF format, integrating the analyzed content into the larger linked data cloud.
Essentials of Automations: The Art of Triggers and Actions in FMESafe Software
In this second installment of our Essentials of Automations webinar series, we’ll explore the landscape of triggers and actions, guiding you through the nuances of authoring and adapting workspaces for seamless automations. Gain an understanding of the full spectrum of triggers and actions available in FME, empowering you to enhance your workspaces for efficient automation.
We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!
UiPath Test Automation using UiPath Test Suite series, part 6DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 6. In this session, we will cover Test Automation with generative AI and Open AI.
UiPath Test Automation with generative AI and Open AI webinar offers an in-depth exploration of leveraging cutting-edge technologies for test automation within the UiPath platform. Attendees will delve into the integration of generative AI, a test automation solution, with Open AI advanced natural language processing capabilities.
Throughout the session, participants will discover how this synergy empowers testers to automate repetitive tasks, enhance testing accuracy, and expedite the software testing life cycle. Topics covered include the seamless integration process, practical use cases, and the benefits of harnessing AI-driven automation for UiPath testing initiatives. By attending this webinar, testers, and automation professionals can gain valuable insights into harnessing the power of AI to optimize their test automation workflows within the UiPath ecosystem, ultimately driving efficiency and quality in software development processes.
What will you get from this session?
1. Insights into integrating generative AI.
2. Understanding how this integration enhances test automation within the UiPath platform
3. Practical demonstrations
4. Exploration of real-world use cases illustrating the benefits of AI-driven test automation for UiPath
Topics covered:
What is generative AI
Test Automation with generative AI and Open AI.
UiPath integration with generative AI
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
OpenID AuthZEN Interop Read Out - AuthorizationDavid Brossard
During Identiverse 2024 and EIC 2024, members of the OpenID AuthZEN WG got together and demoed their authorization endpoints conforming to the AuthZEN API
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdfMalak Abu Hammad
Discover how MongoDB Atlas and vector search technology can revolutionize your application's search capabilities. This comprehensive presentation covers:
* What is Vector Search?
* Importance and benefits of vector search
* Practical use cases across various industries
* Step-by-step implementation guide
* Live demos with code snippets
* Enhancing LLM capabilities with vector search
* Best practices and optimization strategies
Perfect for developers, AI enthusiasts, and tech leaders. Learn how to leverage MongoDB Atlas to deliver highly relevant, context-aware search results, transforming your data retrieval process. Stay ahead in tech innovation and maximize the potential of your applications.
#MongoDB #VectorSearch #AI #SemanticSearch #TechInnovation #DataScience #LLM #MachineLearning #SearchTechnology
Threats to mobile devices are more prevalent and increasing in scope and complexity. Users of mobile devices desire to take full advantage of the features
available on those devices, but many of the features provide convenience and capability but sacrifice security. This best practices guide outlines steps the users can take to better protect personal devices and information.
How to Get CNIC Information System with Paksim Ga.pptxdanishmna97
Pakdata Cf is a groundbreaking system designed to streamline and facilitate access to CNIC information. This innovative platform leverages advanced technology to provide users with efficient and secure access to their CNIC details.
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAUpanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-und-domino-lizenzkostenreduzierung-in-der-welt-von-dlau/
DLAU und die Lizenzen nach dem CCB- und CCX-Modell sind für viele in der HCL-Community seit letztem Jahr ein heißes Thema. Als Notes- oder Domino-Kunde haben Sie vielleicht mit unerwartet hohen Benutzerzahlen und Lizenzgebühren zu kämpfen. Sie fragen sich vielleicht, wie diese neue Art der Lizenzierung funktioniert und welchen Nutzen sie Ihnen bringt. Vor allem wollen Sie sicherlich Ihr Budget einhalten und Kosten sparen, wo immer möglich. Das verstehen wir und wir möchten Ihnen dabei helfen!
Wir erklären Ihnen, wie Sie häufige Konfigurationsprobleme lösen können, die dazu führen können, dass mehr Benutzer gezählt werden als nötig, und wie Sie überflüssige oder ungenutzte Konten identifizieren und entfernen können, um Geld zu sparen. Es gibt auch einige Ansätze, die zu unnötigen Ausgaben führen können, z. B. wenn ein Personendokument anstelle eines Mail-Ins für geteilte Mailboxen verwendet wird. Wir zeigen Ihnen solche Fälle und deren Lösungen. Und natürlich erklären wir Ihnen das neue Lizenzmodell.
Nehmen Sie an diesem Webinar teil, bei dem HCL-Ambassador Marc Thomas und Gastredner Franz Walder Ihnen diese neue Welt näherbringen. Es vermittelt Ihnen die Tools und das Know-how, um den Überblick zu bewahren. Sie werden in der Lage sein, Ihre Kosten durch eine optimierte Domino-Konfiguration zu reduzieren und auch in Zukunft gering zu halten.
Diese Themen werden behandelt
- Reduzierung der Lizenzkosten durch Auffinden und Beheben von Fehlkonfigurationen und überflüssigen Konten
- Wie funktionieren CCB- und CCX-Lizenzen wirklich?
- Verstehen des DLAU-Tools und wie man es am besten nutzt
- Tipps für häufige Problembereiche, wie z. B. Team-Postfächer, Funktions-/Testbenutzer usw.
- Praxisbeispiele und Best Practices zum sofortigen Umsetzen
Ivanti’s Patch Tuesday breakdown goes beyond patching your applications and brings you the intelligence and guidance needed to prioritize where to focus your attention first. Catch early analysis on our Ivanti blog, then join industry expert Chris Goettl for the Patch Tuesday Webinar Event. There we’ll do a deep dive into each of the bulletins and give guidance on the risks associated with the newly-identified vulnerabilities.
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!
TrustArc Webinar - 2024 Global Privacy SurveyTrustArc
How does your privacy program stack up against your peers? What challenges are privacy teams tackling and prioritizing in 2024?
In the fifth annual Global Privacy Benchmarks Survey, we asked over 1,800 global privacy professionals and business executives to share their perspectives on the current state of privacy inside and outside of their organizations. This year’s report focused on emerging areas of importance for privacy and compliance professionals, including considerations and implications of Artificial Intelligence (AI) technologies, building brand trust, and different approaches for achieving higher privacy competence scores.
See how organizational priorities and strategic approaches to data security and privacy are evolving around the globe.
This webinar will review:
- The top 10 privacy insights from the fifth annual Global Privacy Benchmarks Survey
- The top challenges for privacy leaders, practitioners, and organizations in 2024
- Key themes to consider in developing and maintaining your privacy program
CAKE: Sharing Slices of Confidential Data on BlockchainClaudio Di Ciccio
Presented at the CAiSE 2024 Forum, Intelligent Information Systems, June 6th, Limassol, Cyprus.
Synopsis: Cooperative information systems typically involve various entities in a collaborative process within a distributed environment. Blockchain technology offers a mechanism for automating such processes, even when only partial trust exists among participants. The data stored on the blockchain is replicated across all nodes in the network, ensuring accessibility to all participants. While this aspect facilitates traceability, integrity, and persistence, it poses challenges for adopting public blockchains in enterprise settings due to confidentiality issues. In this paper, we present a software tool named Control Access via Key Encryption (CAKE), designed to ensure data confidentiality in scenarios involving public blockchains. After outlining its core components and functionalities, we showcase the application of CAKE in the context of a real-world cyber-security project within the logistics domain.
Paper: https://doi.org/10.1007/978-3-031-61000-4_16
Infrastructure Challenges in Scaling RAG with Custom AI modelsZilliz
Building Retrieval-Augmented Generation (RAG) systems with open-source and custom AI models is a complex task. This talk explores the challenges in productionizing RAG systems, including retrieval performance, response synthesis, and evaluation. We’ll discuss how to leverage open-source models like text embeddings, language models, and custom fine-tuned models to enhance RAG performance. Additionally, we’ll cover how BentoML can help orchestrate and scale these AI components efficiently, ensuring seamless deployment and management of RAG systems in the cloud.
Infrastructure Challenges in Scaling RAG with Custom AI models
Tutorial Linked APIs
1. Winter School on Knowledge Technologies for Complex Business Environments Linked Data and APIs Session 2: Linked APIs Steffen Stadtmüller, AIFB, KSRI, Karlsruhe Institute of Technology, DE Ljubljana, SLO, December 1 st , 2011
33. Example: enriching CRM information 12/02/11 Linked APIs CRM Application Customers #34 John Doe Address #35 Steffen Stadtmüller Address #36 Jane Doe Address #37 …. Roland Stühmer #12 Günter Ladwig - known relations: static data dynamic data ?
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40. Example: enriching CRM information static data ex:Steffen a foaf:Person. ex:Steffen sn:id “ abcde ” . ex:Steffen owl:sameAs < http://linkedapi.org/sn/getFriends?id=abcde#person> . HTTP GET 12/02/11 Linked APIs CRM Application Customers #34 John Doe Address #35 Steffen Stadtmüller Address #36 Jane Doe Address #37 …. Roland Stühmer #12 Günter Ladwig - known relations: dynamic data
83. Evaluation seconds nodes 12/02/11 Linked APIs Nodes sec mean (sec) standard deviation standard error 1 1. run 394 394.5 1.0 0.7 2. run 395 2 1. run 223 221 3.0 2.1 2. run 219 5 1. run 120 122 2.4 1.7 2. run 124 8 1. run 121 119 3.2 2.2 2. run 117 10 1. run 81 81.5 0.5 0.4 2. run 82
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Hinweis der Redaktion
Prof. Dr. Max Mustermann | Musterfakultät
Calculation is not necessarily to be understood in a mathematical sense. Prof. Dr. Max Mustermann | Musterfakultät
Prof. Dr. Max Mustermann | Musterfakultät
2xx: ok 3xx:somewhere else 4xx: client error 5xx: server error Prof. Dr. Max Mustermann | Musterfakultät
Implicit knowledge – if you call a service with input ‚Vienna ‘ and get output ‚20C ‘ , the implicit knowledge is that 20C is the temperature at the last report in Vienna (+ provenenance = ‚ according to ... ‘ ) Prof. Dr. Max Mustermann | Musterfakultät
Also content negotiation: text/html -> sn site Prof. Dr. Max Mustermann | Musterfakultät
NOTE hashtag!!! Prof. Dr. Max Mustermann | Musterfakultät
Prof. Dr. Max Mustermann | Musterfakultät
Prof. Dr. Max Mustermann | Musterfakultät
Prof. Dr. Max Mustermann | Musterfakultät
Prof. Dr. Max Mustermann | Musterfakultät
HashTag! Because we need a non-information URI to identify the entity Prof. Dr. Max Mustermann | Musterfakultät
Remember pattern only constraining! Prof. Dr. Max Mustermann | Musterfakultät
Prof. Dr. Max Mustermann | Musterfakultät
Prof. Dr. Max Mustermann | Musterfakultät
Prof. Dr. Max Mustermann | Musterfakultät
Prof. Dr. Max Mustermann | Musterfakultät
Self explenation also leverages schemas from the LOD cloud Prof. Dr. Max Mustermann | Musterfakultät
Don ‘t confuse SELECT query with input pattern (subset relationship) Prof. Dr. Max Mustermann | Musterfakultät
Explain: worknode – namenode! Additionally: probabilities, that variables are used in certain positions Size of local and global resource and predicate pools to draw from Prof. Dr. Max Mustermann | Musterfakultät
1-5: scales well. 5-8: no further decrease 10 worknodes: further, though diminishing decrease in time One maptask is very small Prof. Dr. Max Mustermann | Musterfakultät
Aiming at several mio Prof. Dr. Max Mustermann | Musterfakultät