Description of the work done for the Semantic Markup activity of the Semantic Sensor Networks Incubator activity (at W3C).
Presentation made at the Australian Ontology Workshop, Melbourne, December 2009. The full title of the paper is: "Review of semantic enablement techniques used in geospatial and semantic standards for legacy and opportunistic mashups" (and it is available via crpit.com)
The Other Way of Doing Big Data: Declarative, Decoupled, Federated, Simple, and Resilient.
Also known as: How to Win at Scale and its Influence of People. Originally presented by Flip Kromer to the Research Board, http://www.researchboard.com/ June 2012
ARCHSTONE: Intelligent Network Services for Advanced Application WorkflowsEd Dodds
This talk is motivated by the belief that the next generation of advanced networked applications (i.e., Net+, Cloud based services) will require integration and co-scheduling of Network, Middleware, and Application level services. These networked applications will be user focused and driven by domain specific requirements. A new class of "intelligent network services" must emerge in order to feed the co-scheduling algorithms which will be searching for real-time and scheduled solutions based on client requests. In this talk we present results from the ARCHSTONE (Advanced Resource Computation for Hybrid Service and TOpology NEtworks) project which has added functionality to the OSCARSv0.6 system to provide these types of "intelligent network services". This includes a framework for "modular composable network services" and an advanced multi-dimensional resource computation engine that allows clients to ask the network "what is possible?" questions as part a larger workflow and co-scheduling activity. Use of these network services by the Virtual Network On Demand (VNOD) co-scheduling workflow is described. We also describe our plans to utilize OpenFlow to expand on the set of available network services to develop even more advanced application services based on this paradigm.
The Other Way of Doing Big Data: Declarative, Decoupled, Federated, Simple, and Resilient.
Also known as: How to Win at Scale and its Influence of People. Originally presented by Flip Kromer to the Research Board, http://www.researchboard.com/ June 2012
ARCHSTONE: Intelligent Network Services for Advanced Application WorkflowsEd Dodds
This talk is motivated by the belief that the next generation of advanced networked applications (i.e., Net+, Cloud based services) will require integration and co-scheduling of Network, Middleware, and Application level services. These networked applications will be user focused and driven by domain specific requirements. A new class of "intelligent network services" must emerge in order to feed the co-scheduling algorithms which will be searching for real-time and scheduled solutions based on client requests. In this talk we present results from the ARCHSTONE (Advanced Resource Computation for Hybrid Service and TOpology NEtworks) project which has added functionality to the OSCARSv0.6 system to provide these types of "intelligent network services". This includes a framework for "modular composable network services" and an advanced multi-dimensional resource computation engine that allows clients to ask the network "what is possible?" questions as part a larger workflow and co-scheduling activity. Use of these network services by the Virtual Network On Demand (VNOD) co-scheduling workflow is described. We also describe our plans to utilize OpenFlow to expand on the set of available network services to develop even more advanced application services based on this paradigm.
A Survey of Petabyte Scale Databases and Storage Systems Deployed at FacebookBigDataCloud
At Facebook, we use various types of databases and storage system to satisfy the needs of different applications. The solutions built around these data store systems have a common set of requirements: they have to be highly scalable, maintenance costs should be low and they have to perform efficiently. We use a sharded mySQL+memcache solution to support real-time access of tens of petabytes of data and we use TAO to provide consistency of this web-scale database across geographical distances. We use Haystack datastore for storing the 3 billion new photos we host every week. We use Apache Hadoop to mine intelligence from 100 petabytes of clicklogs and combine it with the power of Apache HBase to store all Facebook Messages.
This talk describes the reasons why each of these databases are appropriate for their workloads and the design decisions and tradeoffs that were made while implementing these solutions. We touch upon the consistency, availability and partitioning tolerance of each of these solutions. We touch upon the reasons why some of these systems need ACID semantics and other systems do not. We briefly touch upon some futures of how we plan to do big-data deployments across geographical locations and our requirements for a new breed of pure-memory and pure-SSD based transactional database.
The presentation I gave at Linköping University about web stream processing. I discuss two problems: (i) exchanging data streams on the web, and (ii) combining streams and contextual quasi-static data on the web
Apache Drill [1] is a distributed system for interactive analysis of large-scale datasets, inspired by Google’s Dremel technology. It is a design goal to scale to 10,000 servers or more and to be able to process Petabytes of data and trillions of records in seconds. Since its inception in mid 2012, Apache Drill has gained widespread interest in the community. In this talk we focus on how Apache Drill enables interactive analysis and query at scale. First we walk through typical use cases and then delve into Drill's architecture, the data flow and query languages as well as data sources supported.
[1] http://incubator.apache.org/drill/
Introduction to basic concepts about cloud computing, from the mainframes to clusters, grids and then the cloud. Presentation given to the Polelo Research Lab on 2009-05-21 during our weekly group meeting.
As of Drupal 7 we'll have RDFa markup in core, in this session I will:
-explain what the implications are of this and why this matters
-give a short introduction to the Semantic web, RDF, RDFa and SPARQL in human language
-give a short overview of the RDF modules that are available in contrib
-talk about some of the potential use cases of all these magical technologies
We’ll review and apply videoludic techniques to non strictly ludic contexts, focusing on the many roles storytelling can play in games and outside games.
A Survey of Petabyte Scale Databases and Storage Systems Deployed at FacebookBigDataCloud
At Facebook, we use various types of databases and storage system to satisfy the needs of different applications. The solutions built around these data store systems have a common set of requirements: they have to be highly scalable, maintenance costs should be low and they have to perform efficiently. We use a sharded mySQL+memcache solution to support real-time access of tens of petabytes of data and we use TAO to provide consistency of this web-scale database across geographical distances. We use Haystack datastore for storing the 3 billion new photos we host every week. We use Apache Hadoop to mine intelligence from 100 petabytes of clicklogs and combine it with the power of Apache HBase to store all Facebook Messages.
This talk describes the reasons why each of these databases are appropriate for their workloads and the design decisions and tradeoffs that were made while implementing these solutions. We touch upon the consistency, availability and partitioning tolerance of each of these solutions. We touch upon the reasons why some of these systems need ACID semantics and other systems do not. We briefly touch upon some futures of how we plan to do big-data deployments across geographical locations and our requirements for a new breed of pure-memory and pure-SSD based transactional database.
The presentation I gave at Linköping University about web stream processing. I discuss two problems: (i) exchanging data streams on the web, and (ii) combining streams and contextual quasi-static data on the web
Apache Drill [1] is a distributed system for interactive analysis of large-scale datasets, inspired by Google’s Dremel technology. It is a design goal to scale to 10,000 servers or more and to be able to process Petabytes of data and trillions of records in seconds. Since its inception in mid 2012, Apache Drill has gained widespread interest in the community. In this talk we focus on how Apache Drill enables interactive analysis and query at scale. First we walk through typical use cases and then delve into Drill's architecture, the data flow and query languages as well as data sources supported.
[1] http://incubator.apache.org/drill/
Introduction to basic concepts about cloud computing, from the mainframes to clusters, grids and then the cloud. Presentation given to the Polelo Research Lab on 2009-05-21 during our weekly group meeting.
As of Drupal 7 we'll have RDFa markup in core, in this session I will:
-explain what the implications are of this and why this matters
-give a short introduction to the Semantic web, RDF, RDFa and SPARQL in human language
-give a short overview of the RDF modules that are available in contrib
-talk about some of the potential use cases of all these magical technologies
We’ll review and apply videoludic techniques to non strictly ludic contexts, focusing on the many roles storytelling can play in games and outside games.
Son seis lecciones que presentan el evangelio estudiando las conversiones de conocidos personajes que narra el libro de los Hechos.ÍNDICE Lección 1 La conversión del etíope, Lección 2 La conversión de Saulo, Lección 3 La conversión de Cornelio, Lección 4 La conversión de Sergio Paulo, Lección 5 La conversión de Lidia, Lección 6 La conversión del carcelero de Filipos.
Presentation give on the Mobile Campus Assistant software and MyMobileBristol project at "Open Source Junction: cross-platform mobile apps", 30 March 2011, Trinity College, Oxford
8th TUC Meeting - Zhe Wu (Oracle USA). Bridging RDF Graph and Property Graph...LDBC council
During the 8th TUC Meeting held at Oracle’s facilities in Redwood City, California, Zhe Wu, Software Architect at Oracle Spatial and Graph, explained how is his team trying to bridge RDF Graph and Property Data Models.
Dynamic and repeatable transformation of existing Thesauri and Authority list...DESTIN-Informatique.com
Integrating applications & projects
= Dynamic & repeatable transformation of existing Thesauri and Authority lists into SKOS
+ Cross-tabulation of Concepts Linked Data
Presentation to the Linked Data Meeting
University College of London, September 14th 2010
by Christophe Dupriez, Destin SSEB, working for Belgium Poison Centre
DEVNET-1106 Upcoming Services in OpenStackCisco DevNet
There are several new upcoming OpenStack projects/services that are build upon the core OpenStack infrastructure services. This session will first briefly discuss the new changes introduced for the project governance structure in OpenStack. Subsequently, the focus of the presentation will be to provide feature and architecture details on few of the new projects and services in OpenStack. These will include Trove-Database Service, Sahara-Dataprocessing Service, Congress - Policy Service and Magnum – Container Service. A summary of other OpenStack related services will also be provided.
This talk introduces the concepts of web 3.0 technology and how they relate to related technologies such as Internet of Things (IoT), Grid Computing and the Semantic Web:
• A short history of web technologies:
o Web 1.0: Publishing static information with links for human consumption.
o Web 2.0: Publishing dynamic information created by users, for human consumption.
o Web 3.0: Publishing all kinds of information with links between data items, for machine consumption.
• Standardization of protocols for description of any type of data (RDF, N3, Turtle).
• Standardization of protocols for the consumption of data in “the grid” (SPARQL).
• Standardization of protocols for rules (RIF).
• Comparison with the evolution of technologies related to data bases.
• Comparison of IoT solutions based on web 2.0 and web 3.0 technologies.
• Distributed solutions vs centralized solutions..
• Security
• Extensions of Peer-to-peer protocols (XMPP).
• Advantages of solutions based on web 3.0 and standards (IETF, XSF).
Duration of talk: 1-2 hours with questions.
Semantically-Enabling the Web of Things: The W3C Semantic Sensor Network Onto...Laurent Lefort
Presentation of the SSN XG results at eResearch Australia 2011 https://eresearchau.files.wordpress.com/2012/06/74-semantically-enabling-the-web-of-things-the-w3c-semantic-sensor-network-ontology.pdf
Future manufacturing informatics - typology of manufacturing dataLaurent Lefort
Starting point of manufacturing informatics 2013-2014 survey, presented at joint Sydney-Canberra Semantic web meetup, 21 October 2013 (free event at ISWC 2013).
Using the Data Cube vocabulary for Publishing Environmental Linked Data on la...Laurent Lefort
Canberra Semantic Web Meetup.
Initiatives have been launched to develop semantic vocabularies representing statistical classifications and discovery metadata. Tools are also being created by statistical organizations to support the publication of dimensional data conforming to the Data Cube specification, now in Last Call at W3C.
The meeting will be an opportunity to hear about two semantic Web and Linked Data initiatives for statistical data that are driven by the Australian Government. The Bureau of Meteorlogy and CSIRO have recently released a Linked Data version of the ACORN-SAT historical climate data at http://lab.environment.data.gov.au and the ABS has released the Census data modelled in the Data Cube vocabulary which is part of a challenge the ABS is organising in context of the SemStats Workshop (http://www.datalift.org/en/event/semstats2013/challenge) at the International Semantic Web Conference (ISWC) in Sydney (http://iswc2013.semanticweb.org).
Come along to hear about these two projects, the challenges encountered and the solutions developed.
Presentation made at the Metadata Australia conference, Canberra, May 2010 (also available via metadataaustralia2010.com)
(Light) Introduction to work done in the Semantic Sensor Networks Incubator activity.
Analysis of the commonalities and differences for the adoption of semantic web standards by sensing web and eGov communities of practice.
Canberra Semantic Web Meetup, 2 August 2010
The talk objective is to encourage the Meetup members to participate and prepare the Sydney Amped Hack Day (October 16 in Sydney: http://ampedweb.org/ ).
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
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See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
Unsubscribed: Combat Subscription Fatigue With a Membership Mentality by Head...
Standards for Semantic Mashups
1. Review of semantic enablement techniques used in
geospatial and semantic standards for legacy and
opportunistic mashups
Laurent Lefort, Australian Ontology Workshop 2009
Standards for Semantic Sensor Mashups
2. Outline of the talk
• Which standards for which mashups?
• Server-side/legacy or client-side/opportunistic
• Semantic-enabled?
• Semantic enablement pathways
• Links and annotations
• Meshup “value pyramid”
• Review of specific standards
• XLink, RDFa, SAWSDL/hRESTs
• Failure risk and validation issues
• Conclusion
CSIRO. Standards for Semantic Sensor Mashups
3. Web 2.0 & 3.0 (Sem Web) rocks
XML and WSDL don’t (anymore)
WHICH STANDARDS FOR WHICH MASHUPS?
Matt Jones
http://www.flickr.com/photos/
blackbeltjones/3150215637/
CSIRO. Standards for Semantic Sensor Mashups
4. Motivations:
W3C Semantic Sensor Network incubator group
Enable semantic service integration Enable semantic mashups
Semantic annotations Ontology-enabled
Ontology-enabled APIs reference datasets
Semanticaly-annotated Sensors and
OGC services Observations
(SOS, SPS, SAS, …) Linking Open Data
resources
OGC Services
Semantic annotations Registries &
(SOS, SPS, SAS, SES) - for OGC services? Dictionaries
Sensor and obs.
- for Mashups?
To begin the formal process of producing ontologies that define the
capabilities of sensors and sensor networks
To develop semantic annotations of a key language used by services based
sensor networks
(especially the ones developed by the Open Geospatial Consortium)
CSIRO. Standards for Semantic Sensor Mashups
5. Server-side mashups (Web 1.0 & 2.0)
• Server-side mashups
• Server-side software component accessing XML files, Databases,
SOAPful or RESTful web services
• The result is generally packaged as a web service
• For legacy resources:
• Complex APIs
• Workflow engine and wrappers
• Output in XML
CSIRO. Standards for Semantic Sensor Mashups
6. Client-side mashups (Web 1.0 & 2.0)
• Client-side mashup:
• Client-side scripts accessing mashable resources (RESTful
services mostly)
• The result is packaged into an interactive web application
• For opportunistic mashups:
• Simpler APIs
• Scripting languages
• Output in HTML
CSIRO. Standards for Semantic Sensor Mashups
7. Server-side semantic mashups (Web 3.0)
• Server side mashup:
• Semantic enablement of XML files, Databases, SOAPful or
RESTful web services (SAWSDL)
• Integration with linking open data and ontologies services through
triple stores (APIs or resources)
CSIRO. Standards for Semantic Sensor Mashups
8. Example of semantic composition (server side)
• Composer’s Workbench
• XML-RDF
• Wrap complex services using semantic annotations mapping
WSDL/XML schema to DL ontology (also SQL DBs)
• New requirements: provenance XG
Cameron et al. (2009) Semantic Solutions for Integration of Federated Ocean Observations
CSIRO. Standards for Semantic Sensor Mashups
9. Client-side semantic mashups (Web 3.0)
• Client side mashup:
• Enrichment of HTML resources with RDFa markup allowing to “lift”
the content into RDF
• Reduction of number of APIs to handle by scripts (SPARQL or
equivalent)
CSIRO. Standards for Semantic Sensor Mashups
10. Example of semantic pipes (client side)
• Sensor masher (browser-based)
• RDF-HTML (RESTful services, Javascript)
• Avoid the use of proprietary or product-specific APIs
• Leverage URI-based data integration (Linked Open Data)
• Lightweight pipes (user-defined) based on DERI Pipes
Danh Le Phuoc (2009): SensorMasher : publishing and building mashup of sensor data
CSIRO. Standards for Semantic Sensor Mashups
12. Four semantic enablement pathways:
Server-side (1,2, 3) or client-side (3,4)
• 1. Include RDF (SKOS/OWL) resources in XML using XLink,
• 2. Annotate SOAPful web services with SAWSDL
• 3. Annotate RESTful web services with hRESTs (SA-
REST/MicroWSMO),
• 4. Include RDF (SKOS/OWL) resources in HTML using RDFa.
XML HTML
1
1
3
2 3
1
4
1
CSIRO. Standards for Semantic Sensor Mashups
13. A possible use case with all types of mashups
bundled together
Geospatial mashups Web pages mashups (HTML)
Legacy Legacy OGC (XML/JSON+REST)
OGC aggregator
Geospatial mashups Geo Mashups
services (e.g. ArcGIS)
Web mashups
Composed
Model mashups Search
Legacy (XML/JSON+REST)
services services
Model
(XML+REST/ Model Mashups
WSDL) Legacy mashups pipes
(XML+REST/WSDL)
1 2 3 2 3 3 4
Semantic web page mashups
(HTML+RDFa)
RDF-ized RDF-ized
OGC OGC Semantic mashups
service Aggregator Geo Mashups
Web mashups
RDF-ized Search
Composed Semantic
Semantic mashups service pipes Model Mashups
(RDF/JSON+SPARQL)
CSIRO. Standards for Semantic Sensor Mashups
14. Meshup “value pyramid”
• Semantic mashups over Mesh
ups
HTML
• RDFa content embedded in web
pages
• Linked Open Data resources
HTML/RDFa
• XML, database and web service
resources
SPARQL protocol
• Meshup RDF
• A semantically mashable Linked Open Data resources
semantic mashup
• a mashup consuming and serving
RDF-ization (Lifting layer)
SW content,
XML
Legacy Resources
• RDFa standard is disruptive (XML, Database, Web services)
• New generation of SW apps
• New “value pyramid” top Extension of Kingsley Idehen’s pyramid:
“Getting The Linked Data Value Pyramid Layers Right (Updated)”
CSIRO. Standards for Semantic Sensor Mashups
15. Meshup standard “value pyramid” vs.
TBL’s Cracks and Mortar
Mash
ups
HTML
SPARQL protocol
Linked Open Data resources
RDF-ization (Lifting layer)
Legacy Resources
(XML, Database, Web services)
Tim Berners-Lee, Cracks and Mortar
W3C TPAC 2007
CSIRO. Standards for Semantic Sensor Mashups
16. Meshup standard “value pyramid”
vs. new “Cracks and Mortar”
Users
HTTP + HTML (RDFa) + SVG + DOM + JS + Mashable APIs
Mashup
site Mashup Mesh
site
ups
HTTP + HTML (RDFa) + SVG + DOM + JS + Mashable APIs
Mashup SparQL
site Ontology
Mashup
site
of objects Virtual HTML/RDFa
RDF
data
RDFa service
HTML
SPARQL protocol
pages
RDFa
markup
XML or JSON + HTTP + JS + Mashable APIs
Linked Open Data resources
SparQL SparQL
Ontology Virtual Ontology Virtual
of objects RDF of objects RDF
data data
RDF-ization (Lifting layer)
Lifting service
Lifting Lifting service
script RDB-RDF
XML Existing XSLT or Xquery Mapping
Schema XML
SQL Existing
Legacy Resources
GRDDL
markup Schema SQL DB (XML, Database, Web services)
CSIRO. Standards for Semantic Sensor Mashups
17. Definitions: links, annotations, lifting operations
• Links specifies the inclusion of remotely managed resources.
• Mechanisms used to extend available content from any type of
resources with information sourced from remotely managed
content (type or instance).
• Possible between two documents of the same type or between
documents of different types.
• Semantic annotations define how to map service capabilities
to semantic definitions to enable the discovery or composition
of web services.
• The transition from XML-based services to RDF-based services
is called a lifting operation (Farrell and Lausen 2007) and the
inverse one, from RDF to XML is called a lowering operation.
CSIRO. Standards for Semantic Sensor Mashups
18. Semantic enablement pathways using different
linking and annotation standards
• 1 Include RDF
1. Mesh Lifting
(SKOS/OWL) ups
operations
resources in XML RDFa
4
using XLink,
HTML/RDFa
• 2 Annotate SOAPful
2.
web services with SPARQL protocol
SAWSDL
• 3 Annotate RESTful
3.
web services with Linked Open Data resources
hRESTs (SA- SAWSDL
REST/MicroWSMO), hRESTs
RDF-ization (Lifting layer)
• 4 Include RDF
4. 2 3
(SKOS/OWL) XLink
resources in HTML Legacy Resources
1 (XML, Database, Web services)
using RDFa.
CSIRO. Standards for Semantic Sensor Mashups
19. Semantically-enabled XML resources and XLink
HTTP + HTML + SVG + DOM + JS
+ RDF + OWL + SPARQL
SparQL
Ontology Virtual
of objects RDF
data
Lifting service
Lifting
~1 script
XML Existing XSLT or Xquery
Schema XML
GRDDL
markup
CSIRO. Standards for Semantic Sensor Mashups
20. Variants of XLink usage
Inclusion of remote resources Model reference to ontological description
Described in GML spec. xlink Xlink @role and @arcrole
@href
Existing Existing
XML XML
XLink XLink
markup markup
Xlink href
Existing Xlink href Existing or URNs for
XML or URNs for XML ontologies
“data” (class or
(instances) (types)
(individuals) property)
Inclusion of remote semantic resources Model reference to ontological description
Xlink @href Xlink @role, @arcrole
and SWE/GML@definition and SWE/GML @definition
Existing Existing
XML XML
XLink XLink
markup markup
Existing Existing
RDF OWL
(instances) (types)
CSIRO. Standards for Semantic Sensor Mashups
21. XLink and RDF
Attribute Description Intended RDF
xlink:href Identifier of the resource rdf:about of range
which is the target of the resource
association, given as a
URI
xlink:role Nature of the target rdf:about of class of
resource, given as a URI range resource
xlink:arcrole Role or purpose of the rdf:about of object
target resource in property linking domain
relation to the present element to range
resource, given as a URI resource
xlink:title Text describing the rdfs:comment
association or the target
resource
CSIRO. Standards for Semantic Sensor Mashups
22. Usage of XLink in GML – related to URNs
• Conventions defined by the GML standard (Portele 2007)
• Portele C. (2007): OpenGIS® Geography Markup Language (GML)
Encoding Standard version 3.2.1 OGC 07-036 Open Geospatial
Consortium 2007-08-27
• Reference to an object element in the same GML document
<myProperty xlink:href="#o1"/>
• Reference to an object element in a remote XML document using
the gml:id value of that object: <myProperty
xlink:href="http://my.big.org/test.xml#o1"/>
• Reference to an object element with a uniform resource name may
be encoded as follows (a URN resolver is required): <myProperty
xlink:href="urn:x-ogc:def:crs:EPSG:6.3:4326"/>
• URN: Uniform Resource Name
• May or may not correspond to Semantic Web resources
• http://en.wikipedia.org/wiki/Uniform_Resource_Name
• URN is a generic resource naming mechanism: the mapping of a
URN to a class, property or individual is not normalised
CSIRO. Standards for Semantic Sensor Mashups
23. Current XLink usage
• Sheth Semantic Sensor Markup of Data and Services SSN-XG
briefing
• XLink @href pointing to individual
• Luis Bermudez Enriching SOS services with Ontologies -
OOSTethys/OceansIE and MMI SSN-XG briefing
• XLink @href pointing to individual
• Janowicz et al. (2009; forthcoming): Semantic Enablement for
Spatial Data Infrastructures. Transactions in GIS.
• XLink @href pointing to individual with @role pointing to
sawsdl:modelReference (should be arcrole)
• Correct use of sawsdl:modelReference in XML schema but does
not define the associated lifting script
• Compton et al. (2009) A Survey of the Semantic Specification
of Sensors, in Proc. International Workshop on Semantic
Sensor Networks SSN’09 CEUR-WS Vol. 552
• XLink @href pointing to undefined concepts (#AirTemperature)
CSIRO. Standards for Semantic Sensor Mashups
24. Major issues with XLink (and its usage in OGC)
• ISSUE: URNs can point to an individual, a class or a property
• No guidelines on these three types of URN
• <swe:Quantity
definition="urn:ogc:def:property:SBE:batteryCurrent">
• Confusion between XLink @role vs. @arcrole
• Ex of a property URN (here, @arcrole should be used): <swe:field
name="Battery Current“
xlink:role="urn:ogc:def:property:powerSupply">
• Same issue with the @definition attribute
• Usage of @href (to an individual) generally correct
• Because the majority of the community developing and using OGC
standard plans to use SKOS to manage vocabulary elements
CSIRO. Standards for Semantic Sensor Mashups
25. Semantically-enabled web pages (RDFa)
HTTP + HTML (RDFa) + DOM + JS + RDF + OWL + SPARQL
SparQL
Ontology Virtual
of objects RDF
data
RDFa service
HTML
pages
RDFa
markup
4
CSIRO. Standards for Semantic Sensor Mashups
26. Variants of RDFa usage comparable to XLink
CSIRO. Standards for Semantic Sensor Mashups
27. XLink – RDFa comparison
RDF mapping Xlink RDFa
Domain instance about or src
Domain class typeof
Object property arc role rel
Inverse object property rev
Range instance href href or resource
Range class role typeof
Datatype property property
Datatype property type role datatype
Range value content or element content
CSIRO. Standards for Semantic Sensor Mashups
28. Tentative use of RDFa instead of XLink
• Barnaghi et al. Sense and Sensíability: Semantic Data
Modelling for Sensor Networks, in Proc. of the ICT Mobile
Summit 2009, June 2009.
• SWE’s @definition mapped to class
• RDFa-inspired (to fix):
• OWL-like attribute namespaces to clear
• @about mapped to individual,
• @datatype mapped to xsd type,
• @resource used but without corresponding @property,
• @ID used,
• URI conventions?
• It is important to note that RDFa obeys to a rigorous
specification which allows the development and usage of
generic lifting scripts
CSIRO. Standards for Semantic Sensor Mashups
29. Variants of RDFa usage in relation to hRESTs
• Two possibilities to do semantic markup of HTML files
• Microformats
• RDFa
CSIRO. Standards for Semantic Sensor Mashups
30. Semantically-enabled RESTful web services
(hREST-microformat)
HTTP + HTML + SVG + DOM + JS + RDF + OWL + SPARQL
Semantically-enabled service
Semantically-
enabled output
Lifting service
?
for data
RDF description
of service
Lifting Lifting
Dynamic script operation
XML and service
Ontology ontology
RESTful service of objects hard-coded
Lifting
HTML script
hRESTs-
description micro- Service
formats ontology
markup SA-REST or
CSIRO. Standards for Semantic Sensor Mashups 3 ~4 MicroWSMO XSLT or Xquery
31. Semantically-enabled RESTful web services
(hREST-RDFa)
HTTP + HTML + SVG + DOM + JS + RDF + OWL + SPARQL
Semantically-enabled service
Semantically-
enabled output
Lifting service
?
for data
RDF description
of service
Lifting
Dynamic script Lifting
XML operation
Ontology following
RESTful service of objects RDFa spec.
HTML hRESTs-
description in-RDFa Service
markup
ontology
3 ~4 SA-REST or
CSIRO. Standards for Semantic Sensor Mashups MicroWSMO XSLT or Xquery
32. hRESTs-microformat vs. hRESTs-RDFa
RDF mapping hRESTs-microformat hRESTs-RDFa
Domain instance id (URL-prefixed) about
Domain class class (closed list) typeof
Object property ref=”model” rel
Inverse object property rev
Range instance href or resource
rdf:about of range class href typeof
Datatype property property
Datatype property type datatype
Range value content or element
content
CSIRO. Standards for Semantic Sensor Mashups
33. hRESTs-RDFa preferred to hRESTs-microformat
• hRESTs-microformat forces the user to pick the service ontology and
have access to the corresponding lifting script
• SAREST ontology ~ what’s used in SAWSDL
• http://knoesis.wright.edu/research/srl/standards/sa-rest/
• MicroWSMO ontology: WSMO-Lite:
• http://www.wsmo.org/ns/wsmo-lite/
• hRESTs-RDFa allows to specify the service ontology the mapping
definitions will be lifted to
• e.g. one adapted to a specific platform
• sensor networks, grid computing, …
• It should be possible to have a similar freedom of choice with
SAWSDL
• It’s not the case right now (next slide)
CSIRO. Standards for Semantic Sensor Mashups
34. Semantically-enabled SOAPful web services
HTTP + HTML + SVG + DOM + JS + RDF + OWL + SPARQL
Semantically-enabled service
Semantically-
enabled output
Lifting service
? RDF
for data
XSLT or Xquery description
of service
Dynamic Lifting
script Lifting service for description
XML Lifting
operation
WSDL Web service Ontology and service
of objects ontology
hard-coded
WSDL 2
SAWSDL Service Lifting
XML
markup ontology script
Schema
CSIRO. Standards for Semantic Sensor Mashups
35. Failure risk analysis
• Opportunistic mashups depends on external resources which
may disappear or evolve without notice,
• especially mashable services and semantic resources,
• The risks of failure are greater and more diverse than in other
environments.
• Question: where to start
XML RDF HTML
Web Triple
Web pages
services stores
Ontologies SPARQL RDFa
Semantic Linked Open Mashable
Services Data web pages
Legacy mashups Opportunistic mashups
CSIRO. Standards for Semantic Sensor Mashups
36. Validator mashup framework: Unicorn (Universal
Conformance Observation and Report Notation)
• Unicorn (2006-2008)
• Validator Mashup project at W3C
• http://www.w3.org/QA/Tools/Unicorn/
• HTML-only
• Markup Validator,
• CSS Validator,
• Link Checker
CSIRO. Standards for Semantic Sensor Mashups
37. Extend Unicorn to build a complete top-down validator
mashup pyramid
• Mashable validators
• HTML validators
• HTML + RDFa http://validator.w3.org/
• HTML http://validator.nu/
• SPARQL Mesh
ups
• SPARQL* http://www.sparql.org/validator.html
• Linked Data (URIs)* http://vapour.sourceforge.net/
• Linked Open Data HTML/RDFa
• OWL http://owl.cs.manchester.ac.uk/validator/
• RDF http://www.w3.org/RDF/Validator/ SPARQL protocol
• RDF-ization
• SAWSDL, …: ? Linked Open Data resources
• GRDDL (service) http://www.w3.org/2007/08/grddl/
• XML validators
RDF-ization (Lifting layer)
• WSDL http://www.validwsdl.com/ (via Wikipedia)
• OGC valdiators
Legacy Resources
• XLink SXLink? (XML, Database, Web services)
• Full list of W3C list validators:
http://www.w3.org/QA/TheMatrix
CSIRO. Standards for Semantic Sensor Mashups
38. Identification of area of future work
• Semantic annotation standards for both WSDL and REST services
• Ontologies for different types of services
• Lifting scripts for services
• Guidelines on the part of HTML to be annotated for RESTful services
• Controlled upgrade of legacy standards: need at least better guidelines
(and validation tools)
• XLink @role and @arcrole are easy to confuse
• URNs mappings to individuals, class or properties should be specified
unambiguously in OGC specifications (and elsewhere?)
• Develop a RDFa style for XLink may help to separate the current usage of
XLink (intra-XML) to new usages where XLink would be used in conjunction
with semantic web resources
• Validators and validator mashups
• Higher risk of errors with mashups
• Golden opportunity to re-engineer and mash existing validators
• Some missing validators especially at the lower levels (e.g. XLink, URNs)
CSIRO. Standards for Semantic Sensor Mashups
39. Conclusions
• Semantic mashups complete existing semantic integration
approaches but don’t replace them
• Lightweight composition by end users with semantic pipes to
explore opportunities
• Transition to more stable infrastructure built on top of legacy
services if the proof of concept phase is successful
• Mashups require hybrid combination of XML, RDF and HTML
standards
• Some standards like XLink or RDFa are adaptable at different
levels of the pyramid
• Special care must be taken for the semantic upgrades of existing
standards
• Mashups requires new validation approaches
• Which may also be based on mashups (Unicorn-like)
CSIRO. Standards for Semantic Sensor Mashups
40. CSIRO ICT Centre
Laurent Lefort
Senior Software Engineer and W3C Office manager
Phone: +61 2 6216 7046
Email: laurent.lefort@csiro.au
Web: www.ict.csiro.au
Thank you
Contact Us
Phone: 1300 363 400 or +61 3 9545 2176
Email: enquiries@csiro.au Web: www.csiro.au
42. Memo
• GRDDL - A markup format for Gleaning Resource Descriptions from Dialects of
Languages. It is a W3C Recommendation, and enables users to obtain RDF triples out of
XML documents, including XHTML. It defines the syntax to include a reference to a lifting
script in a source document - the lifting script can then be used to transform the document
to RDF
• Microdata - Allows nested groups of name-value pairs to be added to documents, in
parallel with the existing content. A non-semantic alternatibe to RDFa
• SAWSDL - A set of extension attributes for the Web Services Description Language and
XML Schema definition language that allows description of additional semantics of WSDL
components. Allows the user to record the mapping of WSDL elements to concepts defined
in a reference ontology and to specify the lifting scripts which can be applied to the output
of a service to transform it into a RDF file using the reference ontology concepts
• hRESTs - A microformat to add additional meta-data to REST API descriptions in HTML
and XHTML. Developers can directly embed meta-data from various models such an
ontology, taxonomy or a tag cloud into their API descriptions. The embedded meta-data
can be used to improve search (for example: perform faceted search for APIs), data
mediation (in conjunction with XML annotation) as well as help in easier integration of
services to create mashups.
• SA-REST and Micro-WSMO: two similar methods to semantically annotate REST services
using the same microformat (hRESTs) and a different target ontology. Similar basis than
SAWSDL (including the possibility to include a reference to a lifting script) but applicable to
an HTML-based description of a service).
CSIRO. Standards for Semantic Sensor Mashups