The document discusses the Linked-USDL (Unified Service Description Language), which is an ontology for describing services using semantic web principles. It provides an overview of the Linked-USDL modules, syntax, core classes and properties for describing services, service models, offerings, interactions and more. The goal is to develop a standardized way to describe services in a holistic manner, covering both business and technical aspects.
Linked USDL Agreement: Effectively Sharing Semantic Service Level Agreements ...José María García
Linked USDL Agreement is a Linked Data based semantic model to describe, share on the Web, and automatically process service agreements
This presentation describes the model, its design process and tooling support. Presented at IEEE International Conference on Web Services (ICWS) 2015.
Part of Linked USDL family. Find out more at https://github.com/linked-usdl/usdl-agreement
Try out a demo at: http://www.isa.us.es/IDEAS/Linked_USDL_Agreement/
Linked services: Connecting services to the Web of DataJohn Domingue
Keynote from the International Conference on e-Business Engineering, September 2013. The talk covers a short integration to Linked Data, our approach to building applications on top of the Web of Data (which we term Linked Services) and a number of applications in the areas of house hunting: crowdsourcing car parking, sharing human body processes. The talk also covers recent work on transforming SAP's Unified Service Description Language to a Linked Data format.
Description and portability of cloud services with USDL and TOSCAJorge Cardoso
The provisioning and management of cloud services are major concerns since they bring clear benefits such as elasticity, flexibility, scalability, and high availability of applications for enterprises. Two emerging contributions set semantics and machine-understandable specifications for the description and portability of cloud-based services: USDL and TOSCA. In this talk we will explain how both can be articulated to work in conjunction. The Unified Service Description Language (USDL) was created for describing business or real world services to allow services to become tradable and consumable on marketplaces. On the other hand, the Topology and Orchestration Specification for Cloud Applications (TOSCA) was standardized to enable the portability of complex cloud applications and their management across different cloud providers.
For more than 10 years, research on service descriptions has mainly studied software-based services and provided languages such as WSDL, OWL-S, WSMO for SOAP, and hREST for REST. Nonetheless, recent developments from service management (e.g., ITIL and COBIT) and cloud computing (e.g. Software-as-a-Service) have brought new requirements to service descriptions languages: the need to also model business services and account for the multi-faceted nature of services. Business-orientation, co- creation, pricing, legal aspects, and security issues are all elements which must also be part of service descriptions. While ontologies such as e  service and e  value provided a first modeling attempt to capture a business perspective, concerns on how to contract services and the agreements entailed by a contract also need to be taken into account. This has for the most part been disregarded by the e-family of ontologies. In this paper, we review the evolution and provide an overview of Linked USDL, a comprehensive language which provides a (multi-faceted) description to enable the commercialization of (business and technical) services over the web.
Cloud Computing Automation: Integrating USDL and TOSCAJorge Cardoso
-- Presented at CAiSE 2013, Valencia, Spain --
Standardization efforts to simplify the management of cloud applications are being conducted in isolation. The objective of this paper is to investigate to which extend two promising specifications, USDL and TOSCA, can be integrated to automate the lifecycle of cloud applications. In our approach, we selected a commercial SaaS CRM platform, modeled it using the service description language USDL, modeled its cloud deployment using TOSCA, and constructed a prototypical platform to integrate service selection with deployment. Our evaluation indicates that a high level of integration is possible. We were able to fully automatize the remote deployment of a cloud service after it was selected by a customer in a marketplace. Architectural decisions emerged during the construction of the platform and were related to global service identification and access, multi-layer routing, and dynamic binding.
Semantic interoperability courses training module 2 - core vocabularies v0.11Semic.eu
Goals:
- Understand what Core Vocabularies are.
- Understand how to extend the Core Vocabularies depending on your patterns of information exchange
- Understand how to use and extend the Core Vocabularies in your own data models.
Linked USDL Agreement: Effectively Sharing Semantic Service Level Agreements ...José María García
Linked USDL Agreement is a Linked Data based semantic model to describe, share on the Web, and automatically process service agreements
This presentation describes the model, its design process and tooling support. Presented at IEEE International Conference on Web Services (ICWS) 2015.
Part of Linked USDL family. Find out more at https://github.com/linked-usdl/usdl-agreement
Try out a demo at: http://www.isa.us.es/IDEAS/Linked_USDL_Agreement/
Linked services: Connecting services to the Web of DataJohn Domingue
Keynote from the International Conference on e-Business Engineering, September 2013. The talk covers a short integration to Linked Data, our approach to building applications on top of the Web of Data (which we term Linked Services) and a number of applications in the areas of house hunting: crowdsourcing car parking, sharing human body processes. The talk also covers recent work on transforming SAP's Unified Service Description Language to a Linked Data format.
Description and portability of cloud services with USDL and TOSCAJorge Cardoso
The provisioning and management of cloud services are major concerns since they bring clear benefits such as elasticity, flexibility, scalability, and high availability of applications for enterprises. Two emerging contributions set semantics and machine-understandable specifications for the description and portability of cloud-based services: USDL and TOSCA. In this talk we will explain how both can be articulated to work in conjunction. The Unified Service Description Language (USDL) was created for describing business or real world services to allow services to become tradable and consumable on marketplaces. On the other hand, the Topology and Orchestration Specification for Cloud Applications (TOSCA) was standardized to enable the portability of complex cloud applications and their management across different cloud providers.
For more than 10 years, research on service descriptions has mainly studied software-based services and provided languages such as WSDL, OWL-S, WSMO for SOAP, and hREST for REST. Nonetheless, recent developments from service management (e.g., ITIL and COBIT) and cloud computing (e.g. Software-as-a-Service) have brought new requirements to service descriptions languages: the need to also model business services and account for the multi-faceted nature of services. Business-orientation, co- creation, pricing, legal aspects, and security issues are all elements which must also be part of service descriptions. While ontologies such as e  service and e  value provided a first modeling attempt to capture a business perspective, concerns on how to contract services and the agreements entailed by a contract also need to be taken into account. This has for the most part been disregarded by the e-family of ontologies. In this paper, we review the evolution and provide an overview of Linked USDL, a comprehensive language which provides a (multi-faceted) description to enable the commercialization of (business and technical) services over the web.
Cloud Computing Automation: Integrating USDL and TOSCAJorge Cardoso
-- Presented at CAiSE 2013, Valencia, Spain --
Standardization efforts to simplify the management of cloud applications are being conducted in isolation. The objective of this paper is to investigate to which extend two promising specifications, USDL and TOSCA, can be integrated to automate the lifecycle of cloud applications. In our approach, we selected a commercial SaaS CRM platform, modeled it using the service description language USDL, modeled its cloud deployment using TOSCA, and constructed a prototypical platform to integrate service selection with deployment. Our evaluation indicates that a high level of integration is possible. We were able to fully automatize the remote deployment of a cloud service after it was selected by a customer in a marketplace. Architectural decisions emerged during the construction of the platform and were related to global service identification and access, multi-layer routing, and dynamic binding.
Semantic interoperability courses training module 2 - core vocabularies v0.11Semic.eu
Goals:
- Understand what Core Vocabularies are.
- Understand how to extend the Core Vocabularies depending on your patterns of information exchange
- Understand how to use and extend the Core Vocabularies in your own data models.
Semantic interoperability courses training module 3 - reference data v0.10Semic.eu
By the end of this training you should have an understanding of:
What reference data is, its context and purpose and how it creates value for organisations.
Why it is important to manage and govern the reference data lifecycle.
How to work with reference data using open-source tools.
The need of Interoperability in Office and GIS formatsMarkus Neteler
Free GIS and Interoperability: The need of Interoperability in Office and GIS formats
GIS Open Source, interoperabilità e cultura del dato nei SIAT della Pubblica Amministrazione
[GIS Open Source, interoperability and the 'culture of data' in the spatial data warehouses of the Public Administration]
Public Sector Information management frameworks, usually in the form of ontologies and taxonomies containing controlled vocabularies and relevant metadata sets, appear as a key enabler that assists the classification and sharing of resources related to the provision of open data and efficient digital services towards citizen and enterprises. As different authorities typically use different terms to describe their resources and publish them in various data and service registries that may enhance the access to and delivery of governmental knowledge, but also need to communicate seamlessly at a national and pan-European level, the need for unifying and inclusive digital public service metadata standards emerges. This paper presents the creation of an ontology-based extended metadata set that embraces public sectors services, documents, XML Schemas, codelists, public bodies and information systems. Furthermore, the paper presents experiences of application within the Greek Public Sector, as part of the National Interoperability Framework specification. Such a metadata framework is an attempt to formalize the automated exchange of information between various portals and registries and further assist the service transformation and simplification efforts, while it can be further taken into consideration when applying Web 2.0 techniques in governance.
In this Webinar Lorenz Bühmann presents the ontology repair and enrichment tool ORE and also the DL-Learner , a machine learning tool to solve supervised learnings tasks and support knowledge engineers in constructing knowledge. Those two beneighbored tools in the LOD2 Stack are for classification and the following quality analysis of Linked Data.
Ontolog Forum: Semantic Interop March 2008Jamie Clark
Clark comments on the practical challenges of semantic interoperability in e-commerce documents. At Ontolog Forum March 2008. Some parts come from presentation at W3C workshop on e-government in Washington, January 2007.
(http://lod2.eu/BlogPost/webinar-series) In this Webinar Michael Martin presents CubeViz - a facetted browser for statistical data utilizing the RDF Data Cube vocabulary which is the state-of-the-art in representing statistical data in RDF. This vocabulary is compatible with SDMX and increasingly being adopted. Based on the vocabulary and the encoded Data Cube, CubeViz is generating a facetted browsing widget that can be used to filter interactively observations to be visualized in charts. Based on the selected structure, CubeViz offer beneficiary chart types and options which can be selected by users.
If you are interested in Linked (Open) Data principles and mechanisms, LOD tools & services and concrete use cases that can be realised using LOD then join us in the free LOD2 webinar series!
IT managers and people involved in purchase of hardware for your organisation. here is a bit of what you need to know.
and how you could get support from manufacturers when such machines/software break down or need support/ maintenance .
Linux Performance Analysis: New Tools and Old SecretsBrendan Gregg
Talk for USENIX/LISA2014 by Brendan Gregg, Netflix. At Netflix performance is crucial, and we use many high to low level tools to analyze our stack in different ways. In this talk, I will introduce new system observability tools we are using at Netflix, which I've ported from my DTraceToolkit, and are intended for our Linux 3.2 cloud instances. These show that Linux can do more than you may think, by using creative hacks and workarounds with existing kernel features (ftrace, perf_events). While these are solving issues on current versions of Linux, I'll also briefly summarize the future in this space: eBPF, ktap, SystemTap, sysdig, etc.
Talk for PerconaLive 2016 by Brendan Gregg. Video: https://www.youtube.com/watch?v=CbmEDXq7es0 . "Systems performance provides a different perspective for analysis and tuning, and can help you find performance wins for your databases, applications, and the kernel. However, most of us are not performance or kernel engineers, and have limited time to study this topic. This talk summarizes six important areas of Linux systems performance in 50 minutes: observability tools, methodologies, benchmarking, profiling, tracing, and tuning. Included are recipes for Linux performance analysis and tuning (using vmstat, mpstat, iostat, etc), overviews of complex areas including profiling (perf_events), static tracing (tracepoints), and dynamic tracing (kprobes, uprobes), and much advice about what is and isn't important to learn. This talk is aimed at everyone: DBAs, developers, operations, etc, and in any environment running Linux, bare-metal or the cloud."
Broken benchmarks, misleading metrics, and terrible tools. This talk will help you navigate the treacherous waters of Linux performance tools, touring common problems with system tools, metrics, statistics, visualizations, measurement overhead, and benchmarks. You might discover that tools you have been using for years, are in fact, misleading, dangerous, or broken.
The speaker, Brendan Gregg, has given many talks on tools that work, including giving the Linux PerformanceTools talk originally at SCALE. This is an anti-version of that talk, to focus on broken tools and metrics instead of the working ones. Metrics can be misleading, and counters can be counter-intuitive! This talk will include advice for verifying new performance tools, understanding how they work, and using them successfully.
Semantic interoperability courses training module 3 - reference data v0.10Semic.eu
By the end of this training you should have an understanding of:
What reference data is, its context and purpose and how it creates value for organisations.
Why it is important to manage and govern the reference data lifecycle.
How to work with reference data using open-source tools.
The need of Interoperability in Office and GIS formatsMarkus Neteler
Free GIS and Interoperability: The need of Interoperability in Office and GIS formats
GIS Open Source, interoperabilità e cultura del dato nei SIAT della Pubblica Amministrazione
[GIS Open Source, interoperability and the 'culture of data' in the spatial data warehouses of the Public Administration]
Public Sector Information management frameworks, usually in the form of ontologies and taxonomies containing controlled vocabularies and relevant metadata sets, appear as a key enabler that assists the classification and sharing of resources related to the provision of open data and efficient digital services towards citizen and enterprises. As different authorities typically use different terms to describe their resources and publish them in various data and service registries that may enhance the access to and delivery of governmental knowledge, but also need to communicate seamlessly at a national and pan-European level, the need for unifying and inclusive digital public service metadata standards emerges. This paper presents the creation of an ontology-based extended metadata set that embraces public sectors services, documents, XML Schemas, codelists, public bodies and information systems. Furthermore, the paper presents experiences of application within the Greek Public Sector, as part of the National Interoperability Framework specification. Such a metadata framework is an attempt to formalize the automated exchange of information between various portals and registries and further assist the service transformation and simplification efforts, while it can be further taken into consideration when applying Web 2.0 techniques in governance.
In this Webinar Lorenz Bühmann presents the ontology repair and enrichment tool ORE and also the DL-Learner , a machine learning tool to solve supervised learnings tasks and support knowledge engineers in constructing knowledge. Those two beneighbored tools in the LOD2 Stack are for classification and the following quality analysis of Linked Data.
Ontolog Forum: Semantic Interop March 2008Jamie Clark
Clark comments on the practical challenges of semantic interoperability in e-commerce documents. At Ontolog Forum March 2008. Some parts come from presentation at W3C workshop on e-government in Washington, January 2007.
(http://lod2.eu/BlogPost/webinar-series) In this Webinar Michael Martin presents CubeViz - a facetted browser for statistical data utilizing the RDF Data Cube vocabulary which is the state-of-the-art in representing statistical data in RDF. This vocabulary is compatible with SDMX and increasingly being adopted. Based on the vocabulary and the encoded Data Cube, CubeViz is generating a facetted browsing widget that can be used to filter interactively observations to be visualized in charts. Based on the selected structure, CubeViz offer beneficiary chart types and options which can be selected by users.
If you are interested in Linked (Open) Data principles and mechanisms, LOD tools & services and concrete use cases that can be realised using LOD then join us in the free LOD2 webinar series!
IT managers and people involved in purchase of hardware for your organisation. here is a bit of what you need to know.
and how you could get support from manufacturers when such machines/software break down or need support/ maintenance .
Linux Performance Analysis: New Tools and Old SecretsBrendan Gregg
Talk for USENIX/LISA2014 by Brendan Gregg, Netflix. At Netflix performance is crucial, and we use many high to low level tools to analyze our stack in different ways. In this talk, I will introduce new system observability tools we are using at Netflix, which I've ported from my DTraceToolkit, and are intended for our Linux 3.2 cloud instances. These show that Linux can do more than you may think, by using creative hacks and workarounds with existing kernel features (ftrace, perf_events). While these are solving issues on current versions of Linux, I'll also briefly summarize the future in this space: eBPF, ktap, SystemTap, sysdig, etc.
Talk for PerconaLive 2016 by Brendan Gregg. Video: https://www.youtube.com/watch?v=CbmEDXq7es0 . "Systems performance provides a different perspective for analysis and tuning, and can help you find performance wins for your databases, applications, and the kernel. However, most of us are not performance or kernel engineers, and have limited time to study this topic. This talk summarizes six important areas of Linux systems performance in 50 minutes: observability tools, methodologies, benchmarking, profiling, tracing, and tuning. Included are recipes for Linux performance analysis and tuning (using vmstat, mpstat, iostat, etc), overviews of complex areas including profiling (perf_events), static tracing (tracepoints), and dynamic tracing (kprobes, uprobes), and much advice about what is and isn't important to learn. This talk is aimed at everyone: DBAs, developers, operations, etc, and in any environment running Linux, bare-metal or the cloud."
Broken benchmarks, misleading metrics, and terrible tools. This talk will help you navigate the treacherous waters of Linux performance tools, touring common problems with system tools, metrics, statistics, visualizations, measurement overhead, and benchmarks. You might discover that tools you have been using for years, are in fact, misleading, dangerous, or broken.
The speaker, Brendan Gregg, has given many talks on tools that work, including giving the Linux PerformanceTools talk originally at SCALE. This is an anti-version of that talk, to focus on broken tools and metrics instead of the working ones. Metrics can be misleading, and counters can be counter-intuitive! This talk will include advice for verifying new performance tools, understanding how they work, and using them successfully.
Video: https://www.youtube.com/watch?v=JRFNIKUROPE . Talk for linux.conf.au 2017 (LCA2017) by Brendan Gregg, about Linux enhanced BPF (eBPF). Abstract:
A world of new capabilities is emerging for the Linux 4.x series, thanks to enhancements that have been included in Linux for to Berkeley Packet Filter (BPF): an in-kernel virtual machine that can execute user space-defined programs. It is finding uses for security auditing and enforcement, enhancing networking (including eXpress Data Path), and performance observability and troubleshooting. Many new open source tools that have been written in the past 12 months for performance analysis that use BPF. Tracing superpowers have finally arrived for Linux!
For its use with tracing, BPF provides the programmable capabilities to the existing tracing frameworks: kprobes, uprobes, and tracepoints. In particular, BPF allows timestamps to be recorded and compared from custom events, allowing latency to be studied in many new places: kernel and application internals. It also allows data to be efficiently summarized in-kernel, including as histograms. This has allowed dozens of new observability tools to be developed so far, including measuring latency distributions for file system I/O and run queue latency, printing details of storage device I/O and TCP retransmits, investigating blocked stack traces and memory leaks, and a whole lot more.
This talk will summarize BPF capabilities and use cases so far, and then focus on its use to enhance Linux tracing, especially with the open source bcc collection. bcc includes BPF versions of old classics, and many new tools, including execsnoop, opensnoop, funcccount, ext4slower, and more (many of which I developed). Perhaps you'd like to develop new tools, or use the existing tools to find performance wins large and small, especially when instrumenting areas that previously had zero visibility. I'll also summarize how we intend to use these new capabilities to enhance systems analysis at Netflix.
Video: https://www.youtube.com/watch?v=FJW8nGV4jxY and https://www.youtube.com/watch?v=zrr2nUln9Kk . Tutorial slides for O'Reilly Velocity SC 2015, by Brendan Gregg.
There are many performance tools nowadays for Linux, but how do they all fit together, and when do we use them? This tutorial explains methodologies for using these tools, and provides a tour of four tool types: observability, benchmarking, tuning, and static tuning. Many tools will be discussed, including top, iostat, tcpdump, sar, perf_events, ftrace, SystemTap, sysdig, and others, as well observability frameworks in the Linux kernel: PMCs, tracepoints, kprobes, and uprobes.
This tutorial is updated and extended on an earlier talk that summarizes the Linux performance tool landscape. The value of this tutorial is not just learning that these tools exist and what they do, but hearing when and how they are used by a performance engineer to solve real world problems — important context that is typically not included in the standard documentation.
Talk for SCaLE13x. Video: https://www.youtube.com/watch?v=_Ik8oiQvWgo . Profiling can show what your Linux kernel and appliacations are doing in detail, across all software stack layers. This talk shows how we are using Linux perf_events (aka "perf") and flame graphs at Netflix to understand CPU usage in detail, to optimize our cloud usage, solve performance issues, and identify regressions. This will be more than just an intro: profiling difficult targets, including Java and Node.js, will be covered, which includes ways to resolve JITed symbols and broken stacks. Included are the easy examples, the hard, and the cutting edge.
Mobile Offline First for inclusive data that spans the data divideRob Worthington
This presentation - given at the 2016 GovTech conference in South Africa - provides an overview of a new mobile offline first architecture for government applications
EDF2013: Selected Talk Nikolaos Loutas, João Rodrigues Frade: Linked Open Gov...European Data Forum
Selected Talk by Nikolaos Loutas, João Rodrigues Frade, at the European Data Forum 2013, 10 April 2013 in Dublin, Ireland: Linked Open Government Data Business Models
Integration intervention: Get your apps and data up to speedKenneth Peeples
SOA has been the defacto methodology for enterprise application and process integration, because loosely coupled components and composite applications are more agile and efficient. The perfect solution? Not quite.
The data’s always been the problem. The most efficient and agile applications and services can be dragged down by the point-to-point data connections of a traditional data integration stack. Virtualized data services can eliminate the friction and get your applications up to speed.
In this webinar we'll show you how to (replay at http://www.redhat.com/en/about/events/integration-intervention-get-your-apps-and-data-speed):
-Quickly and easily create a virtual data services layer to plug data into your SOA infrastructure for an agile and efficient solution
-Derive more business value from your services.
Solid is a decentralized platform for social Web applications that allow users' data to be managed managed independently of the
applications that create and consume this data.
In this seminar we present the objectives, the architectural design, some examples and final considerations on Solid
This webinar in the course of the LOD2 webinar series will present Virtuoso 7. Virtuoso Column Store, Adaptive Techniques for RDF Graph Databases. In this webinar we shall discuss the application of column store techniques to both graph (RDF) and relational data for mixed work-loads ranging from lookup to analytics.
Virtuoso is an innovative enterprise grade multi-model data server for agile enterprises & individuals. It delivers an unrivaled platform agnostic solution for data management, access, and integration. The unique hybrid server architecture of Virtuoso enables it to offer traditionally distinct server functionality within a single product
If you are interested in Linked (Open) Data principles and mechanisms, LOD tools & services and concrete use cases that can be realised using LOD then join us in the free LOD2 webinar series!
http://lod2.eu/BlogPost/webinar-series
Presentation on an overview of LinkedIn data driven products and infrastructure given on 26 Oct 2012 in the big-data symposium given in honor of the retirement of my PhD advisor Dr Martin H. Schultz.
Oracle ADF Architecture TV - Design - ADF Service ArchitecturesChris Muir
Slides from Oracle's ADF Architecture TV series covering the Design phase of ADF projects, investigating different mechanisms to publish your ADF components as web services.
Like to know more? Check out:
- Subscribe to the YouTube channel - http://bit.ly/adftvsub
- Design Playlist - http://www.youtube.com/playlist?list=PLJz3HAsCPVaSemIjFk4lfokNynzp5Euet
- Read the episode index on the ADF Architecture Square - http://bit.ly/adfarchsquare
Greenclouds Presentation for Jury Meeting TIMMIE Award.Greenclouds
Greenclouds has been selected as finalist for the TIMMIE Awards 2014 as "Most Innovative Vendor". This award, an initiative of CIO Magazine and ICT Media, will be given to the company to award and stimulate their business success and leading innovation.
Modern Data Management for Federal ModernizationDenodo
Watch full webinar here: https://bit.ly/2QaVfE7
Faster, more agile data management is at the heart of government modernization. However, Traditional data delivery systems are limited in realizing a modernized and future-proof data architecture.
This webinar will address how data virtualization can modernize existing systems and enable new data strategies. Join this session to learn how government agencies can use data virtualization to:
- Enable governed, inter-agency data sharing
- Simplify data acquisition, search and tagging
- Streamline data delivery for transition to cloud, data science initiatives, and more
Data Services and the Modern Data Ecosystem (ASEAN)Denodo
Watch full webinar here: https://bit.ly/2YdstdU
Digital Transformation has changed IT the way information services are delivered. The pace of business engagement, the rise of Digital IT (formerly known as “Shadow IT), has also increased demands on IT, especially in the area of Data Management.
Data Services exploits widely adopted interoperability standards, providing a strong framework for information exchange but also has enabled growth of robust systems of engagement that can now exploit information that was normally locked away in some internal silo with Data Virtualization.
We will discuss how a business can easily support and manage a Data Service platform, providing a more flexible approach for information sharing supporting an ever-diverse community of consumers.
Watch this on-demand webinar as we cover:
- Why Data Services are a critical part of a modern data ecosystem
- How IT teams can manage Data Services and the increasing demand by businesses
- How Digital IT can benefit from Data Services and how this can support the need for rapid prototyping allowing businesses to experiment with data and fail fast where necessary
- How a good Data Virtualization platform can encourage a culture of Data amongst business consumers (internally and externally)
Webinar: Learn how to migrate mobile workers to next generation mobilityAppear
Second generation enterprise mobility is transforming mobile field worker productivity. This webinar looked at how to migrate from previous generation solutions to next generation mobile workforce solutions such as those from Appear.
Many organisations are now looking to move from 1st generation rugged devices to smartphones and tablet computers - enabling end users to bring their own favored devices into the workplace.
These slides are from a webinar dated 6th December 2012. For the full text or to view the video of the event please contact Mia Falgard at Appear - mia.falgard@appearnetworks.com
Appear is the leading provider of context-aware enterprise mobility solutions designed to power the next generation of mobile applications and services. By collecting and sharing user and environmental context, Appear’s solutions eliminate information overload and ensure users have exactly the information they need, when and where they need it.
Appear's IQ suite is a cloud-based mobile enterprise solution combining a cross-platform development environment (to support BYOD models), a context-aware mobility platform (to push updates, add/remove applications and change distribution criteria based on the precise context of your employees) and a vertical application store (your own private app store to control the lifecycle and distribution of your applications). Appear IQ offers a number of configurable mobile apps focusing on the needs of mobile workers in industries such as transportation, logistics, field service or construction. Join the app revolution atwww.appearshowroom.com
Industry leaders in transportation, retail, telecommunications and government use AppearIQ. Appear has an extensive partner network including industry leaders Cisco, Motorola, Orange Business Services, SITA, Thales and Logica in order to deliver innovative, end-to-end wireless and mobile solutions. The company is privately held and headquartered in Stockholm, Sweden and with offices across Europe.
Executive introduction to using Oracle BPM and open data web services to drive workflow collaborations.
A Child Welfare Case Management and Court filing application is show cased.
The technical "how to" build directions are covered in Part 2
On the Application of AI for Failure Management: Problems, Solutions and Algo...Jorge Cardoso
Artificial Intelligence for IT Operations (AIOps) is a class of software which targets the automation of operational tasks through machine learning technologies. ML algorithms are typically used to support tasks such as anomaly detection, root-causes analysis, failure prevention, failure prediction, and system remediation. AIOps is gaining an increasing interest from the industry due to the exponential growth of IT operations and the complexity of new technology. Modern applications are assembled from hundreds of dependent microservices distributed across many cloud platforms, leading to extremely complex software systems. Studies show that cloud environments are now too complex to be managed solely by humans. This talk discusses various AIOps problems we have addressed over the years and gives a sketch of the solutions and algorithms we have implemented. Interesting problems include hypervisor anomaly detection, root-cause analysis of software service failures using application logs, multi-modal anomaly detection, root-cause analysis using distributed traces, and verification of virtual private cloud networks.
Distributed Trace & Log Analysis using MLJorge Cardoso
The field of AIOps, also known as Artificial Intelligence for IT Operations, uses advanced technologies to dramatically improve the monitoring, operation, and troubleshooting of distributed systems. Its main premise is that operations can be automated using monitoring data to reduce the workload of operators (e.g., SREs or production engineers). Our current research explores how AIOps – and many related fields such as deep learning, machine learning, distributed traces, graph analysis, time-series analysis, sequence analysis, advanced statistics, NLP and log analysis – can be explored to effectively detect, localize, predict, and remediate failures in large-scale cloud infrastructures (>50 regions and AZs) by analyzing service management data (e.g., distributed traces, logs, events, alerts, metrics). In particular, this talk will describe how a particular monitoring data structure, called distributed traces, can be analyzed using deep learning to identify anomalies in its spans. This capability empowers operators to quickly identify which components of a distributed system are faulty.
AIOps: Anomalous Span Detection in Distributed Traces Using Deep LearningJorge Cardoso
The field of AIOps, also known as Artificial Intelligence for IT Operations, uses algorithms and machine learning to dramatically improve the monitoring, operation, and maintenance of distributed systems. Its main premise is that operations can be automated using monitoring data to reduce the workload of operators (e.g., SREs or production engineers). Our current research explores how AIOps – and many related fields such as deep learning, machine learning, distributed traces, graph analysis, time-series analysis, sequence analysis, and log analysis – can be explored to effectively detect, localize, and remediate failures in large-scale cloud infrastructures (>50 regions and AZs). In particular, this lecture will describe how a particular monitoring data structure, called distributed trace, can be analyzed using deep learning to identify anomalies in its spans. This capability empowers operators to quickly identify which components of a distributed system are faulty.
AIOps: Anomalies Detection of Distributed TracesJorge Cardoso
Introduction to the field of AIOps. large-scale monitoring, and observability. Provides an example illustrating how Deep Learning can be used to analyze distributed traces to reveal exactly which component is causing a problem in microservice applications.
Presentation given at the National University of Ireland, Galway (NUI Galway)
on 2019.08.20.
Thanks to Prof. John Breslin
In planet-scale deployments, the Operation and Maintenance (O&M) of cloud platforms cannot be done any longer manually or simply with off-the-shelf solutions. It requires self-developed automated systems, ideally exploiting the use of AI to provide tools for autonomous cloud operations. This talk will explain how deep learning, distributed traces, and time-series analysis (sequence analysis) can be used to effectively detect anomalous cloud infrastructure behaviors during operations to reduce the workload of human operators. The iForesight system is being used to evaluate this new O&M approach. iForesight 2.0 is the result of 2 years of research with the goal to provide an intelligent new tool aimed at SRE cloud maintenance teams. It enables them to quickly detect and predict anomalies thanks to the use of artificial intelligence when cloud services are slow or unresponsive.
Cloud Reliability: Decreasing outage frequency using fault injectionJorge Cardoso
Invited Keynote at the 9th International Workshop on Software Engineering for Resilient Systems, September 4-5, 2017, Geneva, Switzerland
Title: Cloud Reliability: Decreasing outage frequency using fault injection
Abstract: In 2016, Google Cloud had 74 minutes of total downtime, Microsoft Azure had 270 minutes, and 108 minutes of downtime for Amazon Web Services (see cloudharmony.com). Reliability is one of the most important properties of a successful cloud platform. Several approaches can be explored to increase reliability ranging from automated replication, to live migration, and to formal system analysis. Another interesting approach is to use software fault injection to test a platform during prototyping, implementation and operation. Fault injection was popularized by Netflix and their Chaos Monkey fault-injection tool to test cloud applications. The main idea behind this technique is to inject failures in a controlled manner to guarantee the ability of a system to survive failures during operations. This talk will explain how fault injection can also be applied to detect vulnerabilities of OpenStack cloud platform and how to effectively and efficiently detect the damages caused by the faults injected.
Cloud Operations and Analytics: Improving Distributed Systems Reliability usi...Jorge Cardoso
Lecture given at the Technical University of Munich, 12 December 2016, on Cloud Operations and Analytics: Improving Distributed Systems Reliability using Fault Injection.
Presentation at the International Industry-Academia Workshop on Cloud Reliability and Resilience. 7-8 November 2016, Berlin, Germany.
Organized by EIT Digital and Huawei GRC, Germany.
Twitter: @CloudRR2016
Presentation at the International Industry-Academia Workshop on Cloud Reliability and Resilience. 7-8 November 2016, Berlin, Germany.
Organized by EIT Digital and Huawei GRC, Germany.
Twitter: @CloudRR2016
Gartner analyzed data centers for a period of 10 years and found that 47% of all problems were caused by cloud services outages. The duration of outages ranged between 40 minutes and five days. Ponemon Institute studied the financial impact and found that on average outages cost US$ 690.204, with an average downtime cost of US$ 6.828 per minute. These results are important due to the economic impact of unplanned outages on cloud operations which calls for higher platform reliability.
The first part of this talk will present the mechanisms that pioneers, such as Amazon, Google, and Netflix, have already developed to increase the reliability of their cloud platforms. The second part of the talk will describe how Huawei Research is exploring the use of fault-injection mechanisms to effectively increase the reliability of the Open Telekom Cloud platform from Deutsche Telekom.
Ten years of service research from a computer science perspectiveJorge Cardoso
…It has been more than 10 years since a strong research stream on services started from the field of computer science. The main trigger was without a doubt the introduction of the Web Service Description Language (WSDL), a specification to represent a piece of software functionally which could be remotely invoked. Nonetheless, this was only the “tipping point”. The generalized interest on this new development was followed by interesting topics of research on the application of semantics to enhance the description of services, the composition of services into processes, the analysis of the quality of services, the complexity of processes supporting services, and the development of comprehensive service description languages. This seminar will provide an overview of the main research topics around services and will glimpse at a new research field on the analysis of service networks...
Understanding how services operate as part of large scale global networks, the related risks and gains of different network structures and their dynamics is becoming increasingly critical for society. Our vision and research agenda focuses on the particularly challenging task of building, analyzing, and reasoning about global service networks. This paper explains how Service Network Analysis (SNA) can be used to study and optimize the provisioning of complex services modeled as Open Semantic Service Networks (OSSN), a computer-understandable digital structure which represents connected and dependent services.
Open Semantic Service Networks: Modeling and AnalysisJorge Cardoso
A new interesting research area is the representation and analysis of the networked economy using Open Semantic Service Networks (OSSN). OSSN are represented using the service description language
USDL to model nodes and using the service relationship model OSSR to model edges. Nonetheless, in their current form USDL and OSSR do not provide constructs to capture the dynamic behavior of service networks. To bridge this gap, we used the General System Theory (GST) as a framework guiding the extension of USDL and OSSR to model dynamic OSSN. We evaluated the extensions made by applying USDL and OSSR to two distinct types of dynamic OSSN analysis: 1) evolutionary by using a Preferential Attachment (PA) and 2) analytical by using concepts from System Dynamics (SD). Results indicate that OSSN can constitute the rst stepping stones toward the analysis of global service-based economies.
Modeling Service Relationships for Service NetworksJorge Cardoso
The last decade has seen an increased interest in the study of networks in many fields of science. Examples are numerous, from sociology to biology, and to physical systems such as power grids. Nonetheless, the field of service networks has received less attention. Previous research has mainly tackled the modeling of single service systems and service compositions, often focusing only on studying temporal relationships between services. The objective of this paper is to propose a computational model to represent the various types of relationships which can be established between services systems to model service networks. This work acquires a particular importance since the study of service networks can bring new scientific discoveries on how service-based economies operate at a global scale.
To address the emerging importance of services and the relevance of relationships, we have developed and introduced the concept of Open Semantic Service Network (OSSN). OSSN are networks which relate services with the assumption that firms make the information of their services openly available using suitable models. Services, relationships and networks are said to be open (similar to LOD), when their models are transparently available and accessible by external entities and follow an open world assumption. Networks are said to be semantic when they explicitly describe their capabilities and usage, typically using a conceptual or domain model, and ideally using Semantic Web standards and techniques. One limitation of OSSNs is that they were conceived without accounting for the dynamic behavior of service networks. In other words, they can only capture static snapshots of service-based economies but do not include any mechanism to model reactions and effects that services have on other services and the notion of time
To address the emerging importance of services and the relevance of relationships, we have developed and introduced the concept of Open Semantic Service Network (OSSN). OSSN are networks which relate services with the assumption that firms make the information of their services openly available using suitable models. Services, relationships and networks are said to be open (similar to LOD), when their models are transparently available and accessible by external entities and follow an open world assumption. Networks are said to be semantic when they explicitly describe their capabilities and usage, typically using a conceptual or domain model, and ideally using Semantic Web standards and techniques. One limitation of OSSNs is that they were conceived without accounting for the dynamic behavior of service networks. In other words, they can only capture static snapshots of service-based economies but do not include any mechanism to model reactions and effects that services have on other services and the notion of time
1. www.genssiz.org
Linked-USDL
13 November 2012
Jorge Cardoso
Dept. Engenharia Informatica/CISUC
University of Coimbra
Coimbra, Portugal
jcardoso@dei.uc.pt
2012 Information Systems Management 1
2. Research on services
• Software and IT perspective
– WSDL, SOA, ITIL, …
• Sales, communications and business
models perspective
– Marketing, pricing, channels, …
• Design perspective [CM2012]
– Blueprinting, personas, customer journey, …
[CM2012] Cardoso, J. and Miller, J. A Internet-Based Self-Services: from Analysis and Design to Deployment. In
2012 Information Systems Management
The 2012 IEEE International Conference on Services Economics (SE 2012), IEEE Computer Society, Hawaii, 2
USA, 2012.
3. Software and IT perspective
• Service architectures
– SOA and SoaML
• Service description languages
– WSDL , OWL-S, and WSMO
• Business-oriented descriptions
– e3value, e3service, business models
• Best practices
– ITIL and CMMI for Services
2012 Information Systems Management 3
4. SoaML
OWL-S
WSDL
Services as _functions_
Services as _business_
ITIL
2012 Information Systems Management 4
e3value
5. _Business services_
Consulting IT Services Cloud services
Manual Semi-automatic Fully Automated
2012 Information Systems Management 5
7. Open Services
• Service versus Web service
– Aggregates, structures and configures people, resources, and information to create new value for
consumers.
• Social process
– Firms, groups and individuals (i.e. the community) are equal participants which freely cooperate to
provide information on services.
• Self-governance
– Service are common good which the community tries to create by using forms of decision-making and
autonomy that are widely distributed.
• Openness and free-access
– The services created, being the elements of value created by the community, are freely accessible on a
universal basis.
• Autonomy and distribution
– The participants of the community have the autonomy to advertise their know-how, capabilities and skills
in the form of services to the world.
• Semantic services
– Services are said to be semantic since they explicitly describe their services using a conceptual or
domain model, shared vocabularies.
2012 Information Systems Management
[CPL+2012] Cardoso, J.; Pedrinaci, C.; Leidig, T.; Rupino, P. and Leenheer, P. D Open semantic service networks. In The 7
International Symposium on Services Science (ISSS 2012), pages 1-15, Leipzig, Germany, 2012.
8. USDL
• Unified Service
Description Language
• Master data model for services
• Describe various types of services
– professional to electronic services
• Holistic
– business aspects such as ownership and provisioning,
pricing and legal aspects, in addition to technical
aspects.
2012 Information Systems Management 8
9. USDL History
• a-USDL/2009
– Initial version of USDL [CBM+2010] ready in 2009.
– Later renamed to a-USDL (pronounced alpha-USDL).
– http://www.genssiz.org/research/service-modeling/alpha-usdl/
• USDL/2011
– A W3C Incubator group was created USDL was adapted and
extended based on industry feedback at the end of 2011.
– http://www.w3.org/2005/Incubator/usdl/
• Linked-USDL/--
– In order to make the specification gain a wider acceptance, a version
called Linked-USDL emerged using Semantic Web principles Iits
development is still in progress.
– http://linked-usdl.org/
[CBM+2010] Cardoso, J.; Barros, A.; May, N. and Kylau, U. Towards aSystems Service Description Language for the Internet of Services: 9
2012 Information Unified Management
Requirements and First Developments. In IEEE International Conference on Services Computing, IEEE Computer Society Press, Florida, USA, 2010.
19. Notation
• Turtle allows the semi-colon to separate predicate-
object pairs for the same subject.
• A list of such pairs is terminated with a period.
@prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#>.
@prefix dc: <http://purl.org/dc/elements/1.1/#>.
@prefix exterms: <hhttp://www.example.org/terms/>.
<http://www.example.org/index.html>
exterms:creation-date "August 16, 1999";
dc:language "en";
dc:creator <http://www.example.org/staffid/85740>.
2012 Information Systems Management 19
21. USDL is an ontology
<http://linked-usdl.org/ns/usdl> a owl:Ontology;
dc:title "Linked-USDL Core";
dc:description """<p>This vocabulary provides …most of the original
USDL specification with some useful simplifications. """;
dc:modified "2012-09-20"^^xsd:date;
vann:preferredNamespaceUri "http://www.linked-usdl.org/ns/usdl#";
vann:preferredNamespacePrefix "usdl";
foaf:page <http://linked-usdl.org/ns/usdl.html>;
dc:creator
<http://linked-usdl.org/ns/usdl#cpedrinaci>,
<http://linked-usdl.org/ns/usdl#jcardoso>,
<http://linked-usdl.org/ns/usdl#tleidig> .
2012 Information Systems Management 21
22. usdl:Service
usdl:Service a rdfs:Class, owl:Class;
rdfs:isDefinedBy <http://linked-usdl.org/ns/usdl>;
rdfs:label "service";
rdfs:comment "A usdl:Service is a 'black box' description of a service for
the purpose of describing the service in a way that it can serve as an
interface between the provider and the consumer. The description contains
functional properties of the service, described by the interaction protocol as
well as non-functional properties described by qualitative or quantitative
values. Any composite implementation of a service that is internal is
invisible, however arbitrarily complex an actual service composition may be,
it can be described using supplemental service network vocabularies,
which are beyond the USDL Core vocabulary.";
rdfs:subClassOf gr:ProductOrService .
.
2012 Information Systems Management 22
23. usdl:ServiceOffering
usdl:ServiceOffering a rdfs:Class, owl:Class;
rdfs:isDefinedBy <http://linked-usdl.org/ns/usdl>;
rdfs:label "service offering";
rdfs:comment "A service offering is an offering made by a
gr:BusinessEntity of one or more services to the public or specific
customers. It usually gives defines a price and terms and conditions
including service level agreements";
rdfs:subClassOf gr:Offering .
2012 Information Systems Management 23
24. usdl:ServiceModel
usdl:ServiceModel a rdfs:Class, owl:Class;
rdfs:isDefinedBy <http://linked-usdl.org/ns/usdl>;
rdfs:label "service model";
rdfs:comment "A ServiceModel is used to represent 'classes' of
services, i.e. services that share a number of characteristics.
ServiceModel enables the capturing of these characteristics.";
rdfs:subClassOf
usdl:Service,
gr:ProductOrServiceModel .
2012 Information Systems Management 24
25. usdl:hasServiceModel
usdl:hasServiceModel a rdf:Property;
rdfs:isDefinedBy <http://linked-usdl.org/ns/usdl>;
rdfs:label "has service model";
rdfs:comment "Refers to the service model that specifies
properties valid for all services of this model";
rdfs:domain usdl:Service;
rdfs:range usdl:ServiceModel;
rdfs:subPropertyOf gr:hasMakeAndModel .
2012 Information Systems Management 25
26. usdl:Condition
usdl:Condition a rdfs:Class, owl:Class;
rdfs:isDefinedBy <http://linked-usdl.org/ns/usdl>;
rdfs:label "Condition";
rdfs:comment """<p>The class of conditions for a milstone.
Preconditions or postcondition</p>""".
2012 Information Systems Management 26
27. usdl:hasClassification
usdl:hasClassification a rdf:Property;
rdfs:subPropertyOf dc:subject;
rdfs:isDefinedBy <http://linked-usdl.org/ns/usdl>;
rdfs:label "classification";
rdfs:comment "Indicates a classification of a service.";
rdfs:domain usdl:Service;
rdfs:range skos:Concept.
2012 Information Systems Management 27
29. usdl:includes
usdl:includes a rdf:Property;
rdfs:isDefinedBy <http://linked-usdl.org/ns/usdl>;
rdfs:label "includes";
rdfs:comment """A ServiceOffering bundles a number of services
and associates concrete service levels and pricing for for the
purpose of selling to customers. The ServiceOffering is the client's
view on services on a service marketplace. Services are usually
purchased via a specific ServiceOffering.""";
rdfs:subPropertyOf gr:includes;
rdfs:domain usdl:ServiceOffering;
rdfs:range usdl:Service .
2012 Information Systems Management 29
30. usdl:receives
• Physical
• Human beings
• Information
• Knowledge
• Constraints
• Money
2012 Information Systems Management 30
31. usdl:receives
usdl:receives a rdf:Property;
rdfs:isDefinedBy <http://linked-usdl.org/ns/usdl>;
rdfs:label "receives";
rdfs:comment """<p>Input required for the interaction</p>""";
rdfs:domain usdl:InteractionPoint;
rdfs:range rdfs:Resource.
2012 Information Systems Management 31
32. usdl:yields
• Physical resources
• Information
• Knowledge
• Waste
• Money
2012 Information Systems Management 32
33. usdl:yields
usdl:yields a rdf:Property;
rdfs:isDefinedBy <http://linked-usdl.org/ns/usdl>;
rdfs:label "yields";
rdfs:comment """<p>Outcome yield by an interaction</p>""";
rdfs:domain usdl:InteractionPoint;
rdfs:range rdfs:Resource.
2012 Information Systems Management 33
34. InteractionPoints
• Blueprint
– line of interaction
• E.g. face-to-face
actions between
employees and
customers
2012 Information Systems Management 34
35. usdl:InteractionPoint
usdl:InteractionPoint a rdfs:Class, owl:Class;
rdfs:isDefinedBy <http://linked-usdl.org/ns/usdl>;
rdfs:label "Represents an interaction point";
rdfs:comment "An InteractionPoint represents an actual step in
accessing and performing operations of the service. On a technical
level this could translate into calling a Web Service operation. On a
professional level, it could mean that consumer and provider meet in
person to exchange service parameters or resources involved in the
service delivery (e.g. documents that are processed by the
provider). An interaction can be initiated by the consumer or the
provider." .
2012 Information Systems Management 35
36. usdl:hasInteractionPoint
usdl:hasInteractionPoint a rdf:Property;
rdfs:isDefinedBy <http://linked-usdl.org/ns/usdl>;
rdfs:label "has interaction";
rdfs:comment """<p>Interactions that are part of the interaction
protocol</p>""";
rdfs:domain usdl:Service;
rdfs:range usdl:InteractionPoint .
2012 Information Systems Management 36
37. usdl:hasPrecondition
usdl:hasPrecondition a rdf:Property;
rdfs:isDefinedBy <http://linked-usdl.org/ns/usdl>;
rdfs:label "has precondition";
rdfs:comment """<p>Preconditions to be fulfilled to perform the
Interaction or InteractionProtocol.</p>""";
rdfs:domain usdl:InteractionPoint;
rdfs:range usdl:Condition .
2012 Information Systems Management 37
38. usdl:hasPostcondition
usdl:hasPostcondition a rdf:Property;
rdfs:isDefinedBy <http://linked-usdl.org/ns/usdl>;
rdfs:label "has postcondition";
rdfs:comment """<p>Postcondition that holds if the phase was
performed successfully</p>""";
rdfs:domain usdl:InteractionPoint;
rdfs:range usdl:Condition .
2012 Information Systems Management 38
39. Interaction Type
• Type
– Human-Machine
– Machine-Human
– Machine-Machine
– Human-Human
2012 Information Systems Management 39
40. usdl:hasInteractionType
usdl:hasInteractionType a rdf:Property;
rdfs:isDefinedBy <http://linked-usdl.org/ns/usdl>;
rdfs:label "has interaction type";
rdfs:comment "How can a customer participate in an interaction.
Possible values are: Human-Machine, Human-Human,
Machine-Human, Machine-Machine";
rdfs:domain usdl:InteractionPoint;
rdfs:range <http://www.w3.org/2000/01/rdf-schema#Literal>.
2012 Information Systems Management 40
42. usdl:hasInteractionSpace
usdl:hasInteractionSpace a rdf:Property;
rdfs:isDefinedBy <http://linked-usdl.org/ns/usdl>;
rdfs:label "has interaction space";
rdfs:comment "Does the interaction between customer and
provider occurs at the same physical place?
Or the interaction is mediated by technology?
Possible values are: Presential, Remote";
rdfs:domain usdl:InteractionPoint;
rdfs:range <http://www.w3.org/2000/01/rdf-schema#Literal>.
2012 Information Systems Management 42
43. Interface
• Specifies
– Inputs
– Outputs
• Has a technical
realization or
implementation
– Will be added in the
future
2012 Information Systems Management 43
44. usdl:hasInterface
usdl:hasInterface a rdf:Property;
rdfs:isDefinedBy <http://linked-usdl.org/ns/usdl>;
rdfs:label "has interface";
rdfs:comment """<p>Interactions can have an interface such as
phone, fax, emaill, Web form, Web service, etc. </p>""";
rdfs:domain usdl:InteractionPoint;
rdfs:range usdl:Interface .
2012 Information Systems Management 44
45. Participants, role, agents
• Participant
– Agent
– Role
• Customer
• Provider
• Partners
InteractionPoint
2012 Information Systems Management 45
46. usdl:hasParticipant
usdl:hasParticipant a rdf:Property;
rdfs:isDefinedBy <http://linked-usdl.org/ns/usdl>;
rdfs:label "has participant";
rdfs:comment "Captures the participants involved in a
concrete Interaction.";
rdfs:domain usdl:InteractionPoint;
rdfs:range usdl:Participant.
2012 Information Systems Management 46
47. usdl:Participant
usdl:Participant a rdfs:Class, owl:Class;
rdfs:isDefinedBy <http://linked-usdl.org/ns/usdl>;
rdfs:label "Participant";
rdfs:comment "Participant is a class to capture the
participation of Entities in a certain Interaction".
2012 Information Systems Management 47
48. usdl:hasAgent
usdl:hasAgent a rdf:Property;
rdfs:isDefinedBy <http://linked-usdl.org/ns/usdl>;
rdfs:label "has agent";
rdfs:comment "Captures the participants involved in a
concrete Interaction.";
rdfs:domain usdl:Participant;
rdfs:range gr:BusinessEntity.
2012 Information Systems Management 48
49. usdl:hasRole
usdl:hasRole a rdf:Property;
rdfs:isDefinedBy <http://linked-usdl.org/ns/usdl>;
rdfs:label "has role";
rdfs:comment "Role played in a particular Interaction.";
rdfs:domain usdl:Participant;
rdfs:range usdl:Role.
2012 Information Systems Management 49
50. usdl:Role
usdl:Role a skos:Concept;
rdfs:isDefinedBy <http://linked-usdl.org/ns/usdl>;
rdfs:label "Types of Roles";
rdfs:comment "The kinds of Role that an entity may
play within a certain Interaction".
2012 Information Systems Management 50
51. Some important roles
usdl:Provider a usdl:Role;
rdfs:label "Provider";
skos:prefLabel "Provider";
skos:altLabel "Supplier";
skos:definition "A Provider is the entity responsible for providing the Service".
usdl:Consumer a usdl:Role;
rdfs:label "Consumer";
skos:prefLabel "Consumer";
skos:definition "A Consumer is the entity actually using the Service".
usdl:Partner a usdl:Role;
rdfs:label " Partner";
skos:prefLabel "Partner";
skos:definition "An business partner is any other participant that acts on behalf of the
provider as a third party".
2012 Information Systems Management 51
52. Example http://aws.amazon.com/ec2/
2012 Information Systems Management 52
53. :pricing_EC2_Small_EU_Windows_ReservedInstance_Light_1yr a price:PricePlan ;
dcterms:description "Price plan for a 'Small' EC2 Reserved Instance in Europe with Windows, light utilization and a one year
contract duration."@en ;
price:hasContractDuration
@prefix price: <http://www.linked-usdl.org/ns/usdl-pricing#>
[ a gr:QuantitativeValue ;
gr:hasValueInteger "1" ;
gr:hasUnitOfMeasurement "ANN" ] ;
price:hasBillingCycle
[ a gr:QuantitativeValue ;
gr:hasValueInteger "1" ;
gr:hasUnitOfMeasurement "MON" ] ;
price:hasPriceComponent
:priceComponent_Small_EU_Windows_ReservedInstance_Light_1yr_General_Upfront ,
:priceComponent_Small_EU_Windows_ReservedInstance_Light_1yr_General_Hourly ,
:priceComponent_Small_EU_Windows_ReservedInstance_Light_1yr_General_Upfront a price:PriceComponent ;
dcterms:title "General costs upfront"@en ;
dcterms:description "One-time fee for general usage of the instance."@en ;
price:isLinkedTo
…
price:hasPrice
[ a gr:UnitPriceSpecification ; Outdated
gr:hasCurrency "USD" ;
gr:hasCurrencyValue "69" ;
gr:hasUnitOfMeasurement "C62" ] .
:priceComponent_Small_EU_Windows_ReservedInstance_Light_1yr_General_Hourly a price:PriceComponent ;
dcterms:description "Hourly fee for general usage of the instance."@en ;
price:isLinkedTo
:resource_EC2_DataCentre_EU ,
:resource_EC2_Windows ;
price:hasPrice
[ a gr:UnitPriceSpecification ;
gr:hasCurrency "USD" ;
gr:hasCurrencyValue "0.069" ;
2012 Information Systems Management
gr:hasUnitOfMeasurement "HUR" ] . 53
54. Core
Outdated
2012 Information Systems Management 54
55. Core
Outdated
2012 Information Systems Management 55
57. SLA
Outdated
2012 Information Systems Management 57
58. SLA
Outdated
2012 Information Systems Management 58
59. :slp_Support_Silver a usdl:ServiceLevelProfile ;
dcterms:title "Bronze support service level profile" ;
sla:hasServiceLevel :slo_Support_Silver_ResponseTime .
:slo_Support_Silver_ResponseTime a sla:GuaranteedState ;
dcterms:title "Response time" ;
sla:serviceLevelExpression
[ a sla:ServiceLevelExpression ;
dcterms:description "Maximum period in which response
is sent."@en ;
sla:hasVariable :var_Support_Silver_ResponseTime ] .
Outdated
:var_Support_Silver_ResponseTime a sla:Variable ;
rdfs:label "Fastest guaranteed response" ;
sla:hasDefault
[ a support:ResponseTime ;
gr:hasValue "4" ;
gr:hasUnitOfMeasurement "HUR" ] .
2012 Information Systems Management 59
60. Legal @prefix legal: <http://www.linked-usdl.org/ns/usdl-legal#>
:legal_Amazon a legal:TermsAndConditions ;
dcterms:title "Amazon Web Services LLC's legal statements"@en ;
dcterms:description "Amazon Web Services LLC's legal statements are accessible at
'http://aws.amazon.com/legal/'. Please consult this website for further information"@en ;
legal:hasClause
[ a legal:Clause ;
legal:name "AWS Customer Agreement" ;
legal:text "http://aws.amazon.com/agreement"@en ] ,
[ a legal:Clause ;
legal:name "AWS Services" ;
legal:text "http://aws.amazon.com/serviceterms"@en ] ,
[ a legal:Clause ;
legal:name "AWS Acceptable Use Policy" ;
legal:text "http://aws.amazon.com/aup"@en ] ,
[ a legal:Clause ;
legal:name "AWS Trademark Guidelines" ;
Outdated
legal:text "http://aws.amazon.com/trademark-guidelines"@en ] ,
[ a legal:Clause ;
legal:name "AWS Sites" ;
legal:text "http://aws.amazon.com/terms"@en ] ,
[ a legal:Clause ;
legal:name "Privacy Policy" ;
legal:text "http://aws.amazon.com/privacy"@en ] ,
[ a legal:Clause ;
legal:name "AWS Tax Help" ;
legal:text "http://aws.amazon.com/tax-help"@en ] .
2012 Information Systems Management 60
61. Programming Java
• Goto http://jena.apache.org/
• Download Java Core (apache-jena-2.7.3)
• Use Eclipse, for example.
• Add Jena JARS
• Write some code
• Compile and run!
• RDF Validator and Converter
– http://www.rdfabout.com/demo/validator/
2012 Information Systems Management 61
62. References
• [CM2012] Cardoso, J. and Miller, J. A Internet-Based Self-Services: from
Analysis and Design to Deployment. In The 2012 IEEE International
Conference on Services Economics (SE 2012), IEEE Computer Society,
Hawaii, USA, 2012.
• [CPL+2012] Cardoso, J.; Pedrinaci, C.; Leidig, T.; Rupino, P. and Leenheer,
P. D Open semantic service networks. In The International Symposium on
Services Science (ISSS 2012), pages 1-15, Leipzig, Germany, 2012.
• [CBM+2010] Cardoso, J.; Barros, A.; May, N. and Kylau, U. Towards a
Unified Service Description Language for the Internet of Services:
Requirements and First Developments. In IEEE International Conference
on Services Computing, IEEE Computer Society Press, Florida, USA, 2010.
2012 Information Systems Management 62