Adopting a Canonical Data Model - how to apply to an existing environment wit...Phil Wilkins
This document discusses strategies for implementing a canonical data model in an existing SOA (service-oriented architecture) environment. It covers assumptions about the current SOA estate, the value of adopting a canonical model, technical strategies needed like interface versioning and transition states, and challenges around abstraction versus endpoint needs. The key points are that a canonical model provides semantic and structural consistency across services, reduces design effort, and enables more information-rich integrations, but the transition requires addressing issues like supporting multiple interface versions and legacy systems.
This document discusses data model transformation, which is a solution for services that need to interact even when using different data formats to represent the same information. It describes how embedding transformation logic directly in applications can limit flexibility and reusability. The document recommends using an external transformation service instead to convert data between formats while keeping provider and consumer concerns separate. It provides examples of how WSO2 products implement external transformation using mediators or the data services server with XSLT.
This PPT is to describe detail overview of schemas and its different types of schemas.
It also explains the how to validate and generate instance from Schema thro visual studio
The document discusses the benefits of using a canonical data model (CDM) to standardize terminology and data across business units. A CDM defines common business entities, attributes, and semantics to reduce inconsistencies between different custom data models. This standardization improves business communication, increases software reusability, reduces the number of integration points and transformations needed, and lowers integration time and costs. However, CDMs can be very large and generic, may impact performance, and usually do not contain business validations.
Canonical Modeling for API InteroperabilityTed Epstein
The document discusses challenges with API interoperability due to a lack of common data models. It proposes using canonical data models and realization models to decouple common data definitions from variable message representations. Realization models formalize how canonical models can be adapted for different contexts while maintaining interoperability. This approach is demonstrated through a tax preparation application example and supports generating client libraries that work directly with canonical models, avoiding data mapping issues of traditional approaches.
The document discusses data modeling approaches for APIs and REST architectures. It covers topics like the emergence of internal REST services and the API economy, modeling concepts like resources and hypermedia, and strategies for developing canonical data models that can support variations across different APIs and domains. The presentation argues that data modelers should get involved in API initiatives to help apply modeling best practices and avoid issues stemming from poorly designed or incompatible APIs.
BizTalk Server – Basics principles of mapsSandro Pereira
Maps or transformations are one of the most common components in the integration processes. They act as essential translators in the decoupling between the different systems to connect. In this article, as we explore the BizTalk Mapper Designer, we will explain its main concepts, covering slightly themes such as product architecture, BizTalk Schemas and some of the most widely used standards in the translation of messages.
Sandro Pereira gave a presentation on BizTalk Server and Azure BizTalk Services. BizTalk Server has evolved over 15 years and 15,000 customers to integrate enterprise applications and enable B2B integration. Azure BizTalk Services provides a platform for cloud-based integration of applications and partners with built-in API management, hosting, and workflows. The presentation demonstrated how BizTalk Services can be used to integrate applications and partners in a modern, cloud-friendly way.
The document discusses the need for standardized protocols to enable communication between semantic web clients and servers. It proposes two such protocols: RDF Net API and Topic Map Fragment Processing. RDF Net API defines operations like query, get statements, insert statements, and remove statements. It also defines HTTP and SOAP bindings. Topic Map Fragment Processing allows clients to retrieve and update fragments of topic maps. These protocols aim to fulfill the requirements for semantic web servers to enable querying, updating, and interacting with semantic web data in a distributed environment.
Ahmad Arabi Katbi is an experienced IT manager and architect seeking new leadership challenges. He has over 18 years of experience managing IT infrastructure and service delivery, including 14 years working in Qatar. He specializes in improving operational performance, managing infrastructure support, and leading project management and delivery. Katbi has extensive technical skills and experience working with hardware, operating systems, databases, messaging solutions, and virtualization technologies. He has successfully led several strategic IT projects around consolidation, compliance, private cloud implementation, and platform migrations.
The document discusses next generation data warehousing and business intelligence (BI) analytics. It outlines some of the challenges with scaling traditional BI systems to handle large and growing volumes of data. It then proposes using a massively parallel processing (MPP) database like Greenplum to enable scalable dataflow and embed analytics processing directly into the data warehouse. This would help address issues of data volume, processing time, and refreshing aggregated data for analytics servers. It presents an application profile for typical BI systems and discusses Greenplum's scaling technology using parallel queries and data streams. Finally, it introduces the draft gNet API for implementing parallel dataflows and analytics procedures directly in the MPP database.
This document provides a safe harbor statement for any forward-looking statements made in salesforce.com presentations. It notes that actual results could differ from forward-looking statements if risks and uncertainties materialize or assumptions prove incorrect. It lists various risks and uncertainties including those associated with new products and services, operating losses, fluctuations in operating results, service interruptions, intellectual property litigation, mergers and acquisitions, and the company's relatively limited operating history. The document states that additional information on risk factors is included in salesforce.com's annual report.
OData (Open Data Protocol) is an ISO/IEC approved, OASIS standard that defines a set of best practices for building and consuming RESTful APIs. OData helps you focus on your business logic while building RESTful APIs without having to worry about the various approaches to define request and response headers, status codes, HTTP methods, URL conventions, media types, payload formats, query options, etc. OData also provides guidance for tracking changes, defining functions/actions for reusable procedures, and sending asynchronous/batch requests.
The Open Data Protocol (OData) enables the creation of REST-based data services, which allow resources, identified using Uniform Resource Identifiers (URIs) and defined in a data model, to be published and edited by Web clients using simple HTTP messages.
This document provides an overview of Microsoft BizTalk Server. It defines BizTalk as a premier messaging and integration tool that allows connecting diverse software and graphically creating and modifying business processes. The document outlines BizTalk's tools and capabilities, when it should be used, its architecture and common terms. It also discusses BizTalk's user base, evolution, development tools and installation process. Finally, it mentions some competitors to BizTalk.
Dreamforce14 Multi Org Collaboration ArchitectureRichard Clark
This document discusses architectures for multi-org and multi-community collaboration on Salesforce. It describes the challenges of having disparate Chatter conversations and managing master data across orgs. The author then introduces Passport applications that can integrate Chatter across orgs and communities by creating "ghost users" to synchronize posts and maintain a single feed. Implementing these solutions addresses the key weaknesses of multi-org/community architectures.
This document discusses a resource-oriented approach to data services using REST, Python and RDF. It describes how data can be transformed into data services by creating data resources that represent the data and can be composed into transformation pipelines. The pipelines themselves are also represented as resources, allowing new data services to be incrementally composed from existing ones. The document also provides an overview of the SnapLogic open source data integration toolkit.
Pavan Kapanipathi's talk at IBM's Frontiers of Cloud Computing and Big Data Workshop 2014. http://researcher.ibm.com/researcher/view_group_subpage.php?id=5565
Due to the increased adoption of social web, users, specifically Twitter users are facing information overload. Unless a user is willing to restrict the sources (eg number of followings), important information relevant to users' interests often go unnoticed. The reasons include (1) the postings may be at a time the user is not looking for; (2) the user unaware and hence not following the information source; (3) and the information arrives at a rate at which the user cannot consume. Furthermore, some information that are temporally relevant, discovered late might be of no use.
My research addresses these challenges by
(1) Generating user profiles of interests from Twitter using Wikipedia. The interests gleaned from users' Twitter data can be leveraged by personalization and recommendation systems in order to reduce information overload/Volume for users.
(2) Filtering twitter data relevant to dynamically evolving entities. Including Volume, this addresses the velocity challenge in delivering relevant information in real-time. The approach is deployed on Twitris to crawl for dynamic event-relevant tweets for analysis. The prominent aspect of the approaches is the use of crowd-sourced knowledge-base such as Wikipedia.
Amit Sheth, "Semantics-Empowered Understanding, Analysis and Mining of Nontraditional and Unstructured Data,"
WSU & AFRL Window-on-Science Seminar on Data Mining, August 05, 2009.
http://wiki.knoesis.org/index.php/Seminar_on_Data_Mining#Semantics_empowered_Understanding.2C_Analysis_and_Mining_of_Nontraditional_and_Unstructured_Data
Our paper presented at AMIA 2014 Annual Symposium. Paper is available at:
http://www.knoesis.org/library/resource.php?id=2002
Citation: Ashutosh Jadhav, Amit Sheth, Jyotishman Pathak 'Analysis of Online Information Searching for Cardiovascular Diseases on a Consumer Health Information Portal', AMIA Annual Symposium 2014, Washington DC, November 15-19, 2014
Examples of Applied Semantic Technologies to Solve Variety Challenge of Big Data: Application of Semantic Sensor Network
(SSN) Ontology
Pramod Anantharam - Kno.e.sis
The document discusses integrating sensor and social data to understand city events. It describes collecting data from multiple sources, including sensors and social media. Statistical models are used to analyze the sensor data and identify anomalies, which are then correlated with events extracted from social media using spatial and temporal proximity. The approach is evaluated on traffic data from San Francisco, integrating data from traffic sensors and Twitter to extract and corroborate traffic events.
Best Paper Award winning paper presented at ASONAM 2015.
Derek Doran, Samir Yelne, Luisa Massari, Maria-Carla Calzarossa, LaTrelle Jackson, Glen MoriartyDept. of CSE, Professional Psych, Wright State University, USADept. of Electrical, Computer, and Biomedical Eng., University of Pavia, Italy
7 Cups of Tea, Inc.
http://knoesis.wright.edu/doran
Lu Chen, Wenbo Wang, Amit Sheth. Are Twitter Users Equal in Predicting Elections? A Study of User Groups in Predicting 2012 U.S. Republican Presidential Primaries. The 4th International Conference on Social Informatics (SocInfo2012), December 5-8, 2012, Lausanne, Switzerland.
http://knoesis.org/library/resource.php?id=1787
NIDA National Early Warning System Network
http://wiki.knoesis.org/index.php/NIDA_National_Early_Warning_System_Network_(iN3)
Ohio Center of Excellence in Knowledge-Enabled Computing at Wright State (Kno.e.sis)
Center overview: http://bit.ly/coe-k
Invitation: http://bit.ly/COE-invite
C. Henson, K. Thirunarayan, A. Sheth and P. Hitzler, Representation of Parsimonious Covering Theory in OWL-DL, OWLED2011, June 2011.
http://bit.ly/k-pct
Amit P. Sheth, “Relationships at the Heart of Semantic Web: Modeling, Discovering, Validating and Exploiting Complex Semantic Relationships,” Keynote at the 29th Conference on Current Trends in Theory and Practice of Informatics (SOFSEM 2002), Milovy, Czech Republic, November 22–29, 2002.
Keynote: http://www.sofsem.cz/sofsem02/keynote.html
Related paper: http://knoesis.wright.edu/?q=node/2063
The knowledge-driven integration and exploration of biomedical literature and experimental data on Chagas disease can generate new hypotheses. A system called iExplore allows users to navigate linked relationships between the Biomedical Knowledge Repository (literature facts) and the Parasite Knowledge Repository (experimental data) on Trypanosoma cruzi to infer potential new findings, such as genes inhibited by a drug that could be candidates for further study. This knowledge-driven exploration process leverages semantic web technologies to combine and explore complementary information sources in an interactive and scalable way.
The Ohio Center of Excellence in Knowledge-enabled Computing at Wright State University:
1) Shares the second position globally in impact on the World Wide Web and has the largest academic research group in the US working on semantic web, social media, big data, and health applications.
2) Has exceptional student success with internships and jobs at top companies and a total of 100 researchers including 15 highly cited faculty and 45 PhD students, largely funded through $2M+ annually in research funding.
3) Provides world-class resources for multidisciplinary projects across information technology and domains like biomedicine, with collaboration from industry partners like Google and IBM.
The document discusses the need for standardized protocols to enable communication between semantic web clients and servers. It proposes two such protocols: RDF Net API and Topic Map Fragment Processing. RDF Net API defines operations like query, get statements, insert statements, and remove statements. It also defines HTTP and SOAP bindings. Topic Map Fragment Processing allows clients to retrieve and update fragments of topic maps. These protocols aim to fulfill the requirements for semantic web servers to enable querying, updating, and interacting with semantic web data in a distributed environment.
Ahmad Arabi Katbi is an experienced IT manager and architect seeking new leadership challenges. He has over 18 years of experience managing IT infrastructure and service delivery, including 14 years working in Qatar. He specializes in improving operational performance, managing infrastructure support, and leading project management and delivery. Katbi has extensive technical skills and experience working with hardware, operating systems, databases, messaging solutions, and virtualization technologies. He has successfully led several strategic IT projects around consolidation, compliance, private cloud implementation, and platform migrations.
The document discusses next generation data warehousing and business intelligence (BI) analytics. It outlines some of the challenges with scaling traditional BI systems to handle large and growing volumes of data. It then proposes using a massively parallel processing (MPP) database like Greenplum to enable scalable dataflow and embed analytics processing directly into the data warehouse. This would help address issues of data volume, processing time, and refreshing aggregated data for analytics servers. It presents an application profile for typical BI systems and discusses Greenplum's scaling technology using parallel queries and data streams. Finally, it introduces the draft gNet API for implementing parallel dataflows and analytics procedures directly in the MPP database.
This document provides a safe harbor statement for any forward-looking statements made in salesforce.com presentations. It notes that actual results could differ from forward-looking statements if risks and uncertainties materialize or assumptions prove incorrect. It lists various risks and uncertainties including those associated with new products and services, operating losses, fluctuations in operating results, service interruptions, intellectual property litigation, mergers and acquisitions, and the company's relatively limited operating history. The document states that additional information on risk factors is included in salesforce.com's annual report.
OData (Open Data Protocol) is an ISO/IEC approved, OASIS standard that defines a set of best practices for building and consuming RESTful APIs. OData helps you focus on your business logic while building RESTful APIs without having to worry about the various approaches to define request and response headers, status codes, HTTP methods, URL conventions, media types, payload formats, query options, etc. OData also provides guidance for tracking changes, defining functions/actions for reusable procedures, and sending asynchronous/batch requests.
The Open Data Protocol (OData) enables the creation of REST-based data services, which allow resources, identified using Uniform Resource Identifiers (URIs) and defined in a data model, to be published and edited by Web clients using simple HTTP messages.
This document provides an overview of Microsoft BizTalk Server. It defines BizTalk as a premier messaging and integration tool that allows connecting diverse software and graphically creating and modifying business processes. The document outlines BizTalk's tools and capabilities, when it should be used, its architecture and common terms. It also discusses BizTalk's user base, evolution, development tools and installation process. Finally, it mentions some competitors to BizTalk.
Dreamforce14 Multi Org Collaboration ArchitectureRichard Clark
This document discusses architectures for multi-org and multi-community collaboration on Salesforce. It describes the challenges of having disparate Chatter conversations and managing master data across orgs. The author then introduces Passport applications that can integrate Chatter across orgs and communities by creating "ghost users" to synchronize posts and maintain a single feed. Implementing these solutions addresses the key weaknesses of multi-org/community architectures.
This document discusses a resource-oriented approach to data services using REST, Python and RDF. It describes how data can be transformed into data services by creating data resources that represent the data and can be composed into transformation pipelines. The pipelines themselves are also represented as resources, allowing new data services to be incrementally composed from existing ones. The document also provides an overview of the SnapLogic open source data integration toolkit.
Pavan Kapanipathi's talk at IBM's Frontiers of Cloud Computing and Big Data Workshop 2014. http://researcher.ibm.com/researcher/view_group_subpage.php?id=5565
Due to the increased adoption of social web, users, specifically Twitter users are facing information overload. Unless a user is willing to restrict the sources (eg number of followings), important information relevant to users' interests often go unnoticed. The reasons include (1) the postings may be at a time the user is not looking for; (2) the user unaware and hence not following the information source; (3) and the information arrives at a rate at which the user cannot consume. Furthermore, some information that are temporally relevant, discovered late might be of no use.
My research addresses these challenges by
(1) Generating user profiles of interests from Twitter using Wikipedia. The interests gleaned from users' Twitter data can be leveraged by personalization and recommendation systems in order to reduce information overload/Volume for users.
(2) Filtering twitter data relevant to dynamically evolving entities. Including Volume, this addresses the velocity challenge in delivering relevant information in real-time. The approach is deployed on Twitris to crawl for dynamic event-relevant tweets for analysis. The prominent aspect of the approaches is the use of crowd-sourced knowledge-base such as Wikipedia.
Amit Sheth, "Semantics-Empowered Understanding, Analysis and Mining of Nontraditional and Unstructured Data,"
WSU & AFRL Window-on-Science Seminar on Data Mining, August 05, 2009.
http://wiki.knoesis.org/index.php/Seminar_on_Data_Mining#Semantics_empowered_Understanding.2C_Analysis_and_Mining_of_Nontraditional_and_Unstructured_Data
Our paper presented at AMIA 2014 Annual Symposium. Paper is available at:
http://www.knoesis.org/library/resource.php?id=2002
Citation: Ashutosh Jadhav, Amit Sheth, Jyotishman Pathak 'Analysis of Online Information Searching for Cardiovascular Diseases on a Consumer Health Information Portal', AMIA Annual Symposium 2014, Washington DC, November 15-19, 2014
Examples of Applied Semantic Technologies to Solve Variety Challenge of Big Data: Application of Semantic Sensor Network
(SSN) Ontology
Pramod Anantharam - Kno.e.sis
The document discusses integrating sensor and social data to understand city events. It describes collecting data from multiple sources, including sensors and social media. Statistical models are used to analyze the sensor data and identify anomalies, which are then correlated with events extracted from social media using spatial and temporal proximity. The approach is evaluated on traffic data from San Francisco, integrating data from traffic sensors and Twitter to extract and corroborate traffic events.
Best Paper Award winning paper presented at ASONAM 2015.
Derek Doran, Samir Yelne, Luisa Massari, Maria-Carla Calzarossa, LaTrelle Jackson, Glen MoriartyDept. of CSE, Professional Psych, Wright State University, USADept. of Electrical, Computer, and Biomedical Eng., University of Pavia, Italy
7 Cups of Tea, Inc.
http://knoesis.wright.edu/doran
Lu Chen, Wenbo Wang, Amit Sheth. Are Twitter Users Equal in Predicting Elections? A Study of User Groups in Predicting 2012 U.S. Republican Presidential Primaries. The 4th International Conference on Social Informatics (SocInfo2012), December 5-8, 2012, Lausanne, Switzerland.
http://knoesis.org/library/resource.php?id=1787
NIDA National Early Warning System Network
http://wiki.knoesis.org/index.php/NIDA_National_Early_Warning_System_Network_(iN3)
Ohio Center of Excellence in Knowledge-Enabled Computing at Wright State (Kno.e.sis)
Center overview: http://bit.ly/coe-k
Invitation: http://bit.ly/COE-invite
C. Henson, K. Thirunarayan, A. Sheth and P. Hitzler, Representation of Parsimonious Covering Theory in OWL-DL, OWLED2011, June 2011.
http://bit.ly/k-pct
Amit P. Sheth, “Relationships at the Heart of Semantic Web: Modeling, Discovering, Validating and Exploiting Complex Semantic Relationships,” Keynote at the 29th Conference on Current Trends in Theory and Practice of Informatics (SOFSEM 2002), Milovy, Czech Republic, November 22–29, 2002.
Keynote: http://www.sofsem.cz/sofsem02/keynote.html
Related paper: http://knoesis.wright.edu/?q=node/2063
The knowledge-driven integration and exploration of biomedical literature and experimental data on Chagas disease can generate new hypotheses. A system called iExplore allows users to navigate linked relationships between the Biomedical Knowledge Repository (literature facts) and the Parasite Knowledge Repository (experimental data) on Trypanosoma cruzi to infer potential new findings, such as genes inhibited by a drug that could be candidates for further study. This knowledge-driven exploration process leverages semantic web technologies to combine and explore complementary information sources in an interactive and scalable way.
The Ohio Center of Excellence in Knowledge-enabled Computing at Wright State University:
1) Shares the second position globally in impact on the World Wide Web and has the largest academic research group in the US working on semantic web, social media, big data, and health applications.
2) Has exceptional student success with internships and jobs at top companies and a total of 100 researchers including 15 highly cited faculty and 45 PhD students, largely funded through $2M+ annually in research funding.
3) Provides world-class resources for multidisciplinary projects across information technology and domains like biomedicine, with collaboration from industry partners like Google and IBM.
Student Achievement Review (initially presented during Inauguration Function of the Ohio Center of Excellence in Knowledge-Enabled Computing at Wright State (Kno.e.sis)) - updated since
Center overview: http://bit.ly/coe-k
Invitation: http://bit.ly/COE-invite
Given the growth of social media and rapid evolution of Web of Data, we have unprecedented opportunities to improve crisis response by extracting social signals, creating spatio-temporal mappings, performing analytics on social and Web of Data, and supporting a variety of applications. Such applications can help provide situational awareness during an emergency, improve preparedness, and assist during the rebuilding/recovery phase of a disaster. Data mining can provide valuable insights to support emergency responders and other stakeholders during crisis. However, there are a number of challenges and existing computing technology may not work in all cases. Therefore, our objective here is to present the characterization of such data mining tasks, and challenges that need further research attention for leveraging social media and Web of Data to assist crisis response coordination.
The document describes semantic provenance modeling for scientific data and experiments. It discusses developing an upper-level provenance ontology called Provenir to serve as a foundation for domain-specific provenance ontologies. It also covers tracking provenance information for scientific workflows and experiments in a modular, multi-ontology approach.
The document outlines Pablo Mendes' PhD dissertation defense on adaptive semantic annotation of entities and concepts in text. It discusses Pablo Mendes' conceptual model for knowledge base tagging, the DBpedia knowledge base and DBpedia Spotlight system, core evaluations of the system, and case studies applying the system to tweets, audio transcripts, and educational material. The presentation concludes by thanking the audience.
Literature-Based Discovery (LBD) refers to the process of uncovering hidden connections that are implicit in scientific literature. Numerous hypotheses have been generated from scientific literature, which influenced innovations in diagnosis, treatment, preventions and overall public health. However, much of the existing research on discovering hidden connections among concepts have used distributional statistics and graph-theoretic measures to capture implicit associations. Such metrics do not explicitly capture the semantics of hidden connections. ...
While effective in some situations, the practice of relying on domain expertise, structured background knowledge and heuristics to complement distributional and graph-theoretic approaches, has serious limitations. ..
This dissertation proposes an innovative context-driven, automatic subgraph creation method for finding hidden and complex associations among concepts, along multiple thematic dimensions. It outlines definitions for context and shared context, based on implicit and explicit (or formal) semantics, which compensate for deficiencies in statistical and graph-based metrics. It also eliminates the need for heuristics a priori. An evidence-based evaluation of the proposed framework showed that 8 out of 9 existing scientific discoveries could be recovered using this approach. Additionally, insights into the meaning of associations could be obtained using provenance provided by the system. In a statistical evaluation to determine the interestingness of the generated subgraphs, it was observed that an arbitrary association is mentioned in only approximately 4 articles in MEDLINE, on average. These results suggest that leveraging implicit and explicit context, as defined in this dissertation, is an advancement of the state-of-the-art in LBD research.
Ph.D. Committee: Drs. Amit Sheth (Advisor), TK Prasad, Michael Raymer,
Ramakanth Kavuluru (UKY), Thomas C. Rindflesch (NLM) and Varun Bhagwan (Yahoo! Labs)
Relevant Publications (more at: http://knoesis.wright.edu/students/delroy/)
D. Cameron, R. Kavuluru, T. C. Rindflesch, O. Bodenreider, A. P. Sheth, K. Thirunarayan. Leveraging Distributional Semantics for Domain Agnostic Literature-Based Discovery (under preparation)
D. Cameron, O. Bodenreider, H. Yalamanchili, T. Danh, S. Vallabhaneni, K. Thirunarayan, A. P. Sheth, T. C. Rindflesch. A Graph-based Recovery and Decomposition of Swanson’s Hypothesis using Semantic Predications. Journal of Biomedical Informatics (JBI13), 46(2): 238–251, 2013
D. Cameron, R. Kavuluru, O. Bodenreider, P. N. Mendes, A. P. Sheth, K. Thirunarayan. Semantic Predications for Complex Information Needs in Biomedical Literature International Bioinformatics and Biomedical Conference (BIBM11), pp. 512–519, 2011 (acceptance rate=19.4%)
D. Cameron, P. N. Mendes, A. P. Sheth, V. Chan. Semantics-empowered Text Exploration for Knowledge Discovery. ACM Southeast Conference (ACMSE10), 14, 2010
The document discusses model-driven business process management (BPM) using template-driven approaches. It proposes that templates can [1] align business concepts with implementations through shared XML representations, [2] enhance interoperability by providing common understandings of data through contextual rules, and [3] support agile development through dynamically configurable templates. The OASIS Content Assembly Mechanism (CAM) is presented as a template standard that can address interoperability challenges by leveraging context and making information exchanges more predictable and adaptable.
The document discusses model-driven business process management (BPM) using template-driven approaches. It proposes using XML templates and the OASIS Content Assembly Mechanism (CAM) to [1] align business concepts with implementations, [2] generate documentation to communicate rules to stakeholders, and [3] enable agile information exchanges through reusable templates. CAM allows adding validation rules to templates extracted from XSDs to make exchanges more robust and interoperable compared to static schemas. The approach aims to make BPM more context-aware, self-adaptive, and able to flexibly support changing requirements.
The New Enterprise Alphabet - .Net, XML And XBRLJorgen Thelin
The document discusses new enterprise technologies like .NET, XML, and XBRL that are enabling greater interoperability between businesses. It covers key concepts like service-oriented architecture (SOA) and web services that allow applications from different vendors to communicate. Interoperability profiles play an important role in achieving business interoperability by defining subsets of specifications for specific domains or environments. While challenges remain, initiatives like web services specifications and Microsoft's focus on standards are helping to realize the vision of an interconnected, agile enterprise.
The document introduces MOND TM software, which provides a common data model and semantic mapping capabilities to enable quick and easy integration and maintenance of transformations between different platforms and data sources. It discusses challenges with traditional integration approaches and how MOND TM addresses these challenges through features such as template maps and rules, a semantics engine, support for various data formats and protocols, and packaged integration of common standards. The document also outlines the value propositions of MOND TM such as reduced costs, increased flexibility, automation and compliance. It concludes with answering some frequently asked questions about the software.
This document is a CV cover sheet for Manuel Diego Lara Huiza. It lists his name, location in Milan Italy, and relevant skills including C#, SQL, NHibernate, REST services, and SOLID principles. His career history includes roles as a senior software developer for Esprinet S.p.A. and SB Italia, where he worked on projects involving WCF, ElasticSearch, and NHibernate. Previous roles include web developer for Repower, where he developed backend systems in SQL Server and WCF services, and software developer roles focusing on C# development.
The document discusses using service level agreements (SLAs) as derivatives contracts for data centers and virtual resource markets. It proposes treating SLAs like software that goes through a development lifecycle from initiation to evaluation. Standard models and tools are needed to compose reusable SLA components as the virtual resource market develops.
The document discusses several technology topics including:
1. SOA and its benefits such as facilitating interoperability and promoting technology reuse.
2. Cloud computing and common questions around it such as what cloud computing is, how many clouds there will be, and what's new in cloud computing.
3. An example scenario of a company called FredsList gradually adopting more cloud capabilities for their listings website, from basic storage to search, photos, analytics and performance optimization.
This document contains the resume of Subbarao P, who has 3.5 years of experience working with WebMethods Integration Platform. He has expertise in building and maintaining B2B applications and EAI integrations using WebMethods, and experience with various adapters and protocols. The resume lists three projects he worked on, including maintaining Coca-Cola's global B2B integration infrastructure and developing new interfaces for an upgrade project.
This document discusses modeling search computing applications using a model-driven approach. It proposes representing different aspects like queries, services, and results as models. Transformations are used to move between different levels of abstraction and generate executable query plans from high-level queries. The approach aims to replace programming with model-driven development for flexibility and efficiency in defining search applications.
The document discusses service-oriented architecture (SOA) and provides definitions and explanations of key SOA concepts and terminology. It describes SOA as breaking applications into reusable services and requiring analysis to identify business processes and data that can be exposed as services. It also notes that SOA promises increased business agility by making it possible to assemble components in new ways in response to changing business needs.
The document discusses challenges that organizations face after a merger, including multiple disconnected systems and applications. It proposes adopting a service-oriented architecture (SOA) using Pipeline Pilot as a solution. Pipeline Pilot provides reusable components and web services that allow for rapid application development. This helps streamline systems, reduce costs, and provide flexibility needed to adapt to changing business needs in a post-merger environment.
This is a presentation of a research paper on comparative study of Component based Software Engineering and Service Oriented Architecture. It covers technologies of both paradigms as well as technical discussions and justifications on SOA. It also covers modern components.
It is a presentation of a research paper on Component Based Software Engineering vs Service Oriented Architecture. It deals with basic comparative study of CBSE and SOA , SOA technologies and Service Components, Modern Components. It also covers discussions and justifications of performance issues of web services.
Semantic Web Process Lifecycle: Role of Semantics in Annotation, Discovery, C...Amit Sheth
“Semantic Web Process Lifecycle: Role of Semantics in Annotation, Discovery, Composition and Orchestration,” Keynote/Invited Talk, WWW 2003 Workshop on E-Services and the Semantic Web, Budapest, Hungary, May 20, 2003.
Here is the paper based on this talk:
Kaarthik Sivashanmugam, Kunal Verma,Amit Sheth, and John Miller, 'Adding Semantics to Web Services Standards,'International Conference on Web Services 2003 (ICWS'03), Las Vegas, NV, June 23-26, 2003.
http://knoesis.org/library/resource.php?id=00174
How to Get Cloud Architecture and Design Right the First TimeDavid Linthicum
The document discusses best practices for designing cloud architecture and getting cloud implementation right the first time. It covers proper ways to leverage, design, and build cloud-based systems and infrastructure, going beyond hype to advice from those with real-world experience making cloud computing work. The document provides guidance on common mistakes to avoid and emerging architectural patterns to follow.
This document provides an overview of FDMEE (Financial Data Quality Management, Enterprise Edition) capabilities presented by Tony Scalese from Edgewater Ranzal. The summary includes:
FDMEE has evolved over the past 20 years from its origins as Upstream to support more flexible data integration, transformations, and analytics capabilities compared to prior versions. FDMEE supports capabilities like parallel processing, calculation scripts, batch automation, and scheduling to improve performance. It can directly integrate data from sources like ERPs and perform transformations.
1) Salesforce.com's multitenant architecture allows multiple customers to use the same application instance running on the same server infrastructure, lowering costs while maintaining performance and security.
2) All customer data and configurations are stored separately in the same database using unique customer IDs to isolate each tenant's data.
3) This approach provides significant benefits including automatic upgrades, high performance at scale through query optimization, and faster innovation since all customers use the same codebase.
This document discusses best practices for migrating to a service-oriented architecture (SOA). It recommends embracing heterogeneity and complexity by abstracting across different software systems using standards like XML and web services. A successful SOA migration requires changing organizational structures and skills to focus on reusable services, incremental changes, and architectural best practices. Service contracts that separate interface from implementation are also key to enabling reuse and flexibility.
The document describes the architecture for building a JAX-WS web service that calculates order subtotals using JBoss Drools and Apache jUDDI integration. The proposed solution includes major components like a business rule engine (BRE) to house rules for calculations, a service registry for discovery, and connectors. The requirements involve calculating order subtotals based on items, taxes, discounts, and shipping. The architecture is designed around loose coupling, with interfaces, canonical definitions, and externalization of business rules and data formats.
A measles outbreak originating in West Texas has been linked to confirmed cases in New Mexico, with additional cases reported in Oklahoma and Kansas. The current case count is 817 from Texas, New Mexico, Oklahoma, and Kansas. 97 individuals have required hospitalization, and 3 deaths, 2 children in Texas and one adult in New Mexico. These fatalities mark the first measles-related deaths in the United States since 2015 and the first pediatric measles death since 2003.
The YSPH Virtual Medical Operations Center Briefs (VMOC) were created as a service-learning project by faculty and graduate students at the Yale School of Public Health in response to the 2010 Haiti Earthquake. Each year, the VMOC Briefs are produced by students enrolled in Environmental Health Science Course 581 - Public Health Emergencies: Disaster Planning and Response. These briefs compile diverse information sources – including status reports, maps, news articles, and web content– into a single, easily digestible document that can be widely shared and used interactively. Key features of this report include:
- Comprehensive Overview: Provides situation updates, maps, relevant news, and web resources.
- Accessibility: Designed for easy reading, wide distribution, and interactive use.
- Collaboration: The “unlocked" format enables other responders to share, copy, and adapt seamlessly. The students learn by doing, quickly discovering how and where to find critical information and presenting it in an easily understood manner.
CURRENT CASE COUNT: 817 (As of 05/3/2025)
• Texas: 688 (+20)(62% of these cases are in Gaines County).
• New Mexico: 67 (+1 )(92.4% of the cases are from Eddy County)
• Oklahoma: 16 (+1)
• Kansas: 46 (32% of the cases are from Gray County)
HOSPITALIZATIONS: 97 (+2)
• Texas: 89 (+2) - This is 13.02% of all TX cases.
• New Mexico: 7 - This is 10.6% of all NM cases.
• Kansas: 1 - This is 2.7% of all KS cases.
DEATHS: 3
• Texas: 2 – This is 0.31% of all cases
• New Mexico: 1 – This is 1.54% of all cases
US NATIONAL CASE COUNT: 967 (Confirmed and suspected):
INTERNATIONAL SPREAD (As of 4/2/2025)
• Mexico – 865 (+58)
‒Chihuahua, Mexico: 844 (+58) cases, 3 hospitalizations, 1 fatality
• Canada: 1531 (+270) (This reflects Ontario's Outbreak, which began 11/24)
‒Ontario, Canada – 1243 (+223) cases, 84 hospitalizations.
• Europe: 6,814
This presentation was provided by Bill Kasdorf of Kasdorf & Associates LLC and Publishing Technology Partners, during the fifth session of the NISO training series "Accessibility Essentials." Session Five: A Standards Seminar, was held May 1, 2025.
CBSE - Grade 8 - Science - Chemistry - Metals and Non Metals - WorksheetSritoma Majumder
Introduction
All the materials around us are made up of elements. These elements can be broadly divided into two major groups:
Metals
Non-Metals
Each group has its own unique physical and chemical properties. Let's understand them one by one.
Physical Properties
1. Appearance
Metals: Shiny (lustrous). Example: gold, silver, copper.
Non-metals: Dull appearance (except iodine, which is shiny).
2. Hardness
Metals: Generally hard. Example: iron.
Non-metals: Usually soft (except diamond, a form of carbon, which is very hard).
3. State
Metals: Mostly solids at room temperature (except mercury, which is a liquid).
Non-metals: Can be solids, liquids, or gases. Example: oxygen (gas), bromine (liquid), sulphur (solid).
4. Malleability
Metals: Can be hammered into thin sheets (malleable).
Non-metals: Not malleable. They break when hammered (brittle).
5. Ductility
Metals: Can be drawn into wires (ductile).
Non-metals: Not ductile.
6. Conductivity
Metals: Good conductors of heat and electricity.
Non-metals: Poor conductors (except graphite, which is a good conductor).
7. Sonorous Nature
Metals: Produce a ringing sound when struck.
Non-metals: Do not produce sound.
Chemical Properties
1. Reaction with Oxygen
Metals react with oxygen to form metal oxides.
These metal oxides are usually basic.
Non-metals react with oxygen to form non-metallic oxides.
These oxides are usually acidic.
2. Reaction with Water
Metals:
Some react vigorously (e.g., sodium).
Some react slowly (e.g., iron).
Some do not react at all (e.g., gold, silver).
Non-metals: Generally do not react with water.
3. Reaction with Acids
Metals react with acids to produce salt and hydrogen gas.
Non-metals: Do not react with acids.
4. Reaction with Bases
Some non-metals react with bases to form salts, but this is rare.
Metals generally do not react with bases directly (except amphoteric metals like aluminum and zinc).
Displacement Reaction
More reactive metals can displace less reactive metals from their salt solutions.
Uses of Metals
Iron: Making machines, tools, and buildings.
Aluminum: Used in aircraft, utensils.
Copper: Electrical wires.
Gold and Silver: Jewelry.
Zinc: Coating iron to prevent rusting (galvanization).
Uses of Non-Metals
Oxygen: Breathing.
Nitrogen: Fertilizers.
Chlorine: Water purification.
Carbon: Fuel (coal), steel-making (coke).
Iodine: Medicines.
Alloys
An alloy is a mixture of metals or a metal with a non-metal.
Alloys have improved properties like strength, resistance to rusting.
How to Set warnings for invoicing specific customers in odooCeline George
Odoo 16 offers a powerful platform for managing sales documents and invoicing efficiently. One of its standout features is the ability to set warnings and block messages for specific customers during the invoicing process.
How to Manage Opening & Closing Controls in Odoo 17 POSCeline George
In Odoo 17 Point of Sale, the opening and closing controls are key for cash management. At the start of a shift, cashiers log in and enter the starting cash amount, marking the beginning of financial tracking. Throughout the shift, every transaction is recorded, creating an audit trail.
The *nervous system of insects* is a complex network of nerve cells (neurons) and supporting cells that process and transmit information. Here's an overview:
Structure
1. *Brain*: The insect brain is a complex structure that processes sensory information, controls behavior, and integrates information.
2. *Ventral nerve cord*: A chain of ganglia (nerve clusters) that runs along the insect's body, controlling movement and sensory processing.
3. *Peripheral nervous system*: Nerves that connect the central nervous system to sensory organs and muscles.
Functions
1. *Sensory processing*: Insects can detect and respond to various stimuli, such as light, sound, touch, taste, and smell.
2. *Motor control*: The nervous system controls movement, including walking, flying, and feeding.
3. *Behavioral responThe *nervous system of insects* is a complex network of nerve cells (neurons) and supporting cells that process and transmit information. Here's an overview:
Structure
1. *Brain*: The insect brain is a complex structure that processes sensory information, controls behavior, and integrates information.
2. *Ventral nerve cord*: A chain of ganglia (nerve clusters) that runs along the insect's body, controlling movement and sensory processing.
3. *Peripheral nervous system*: Nerves that connect the central nervous system to sensory organs and muscles.
Functions
1. *Sensory processing*: Insects can detect and respond to various stimuli, such as light, sound, touch, taste, and smell.
2. *Motor control*: The nervous system controls movement, including walking, flying, and feeding.
3. *Behavioral responses*: Insects can exhibit complex behaviors, such as mating, foraging, and social interactions.
Characteristics
1. *Decentralized*: Insect nervous systems have some autonomy in different body parts.
2. *Specialized*: Different parts of the nervous system are specialized for specific functions.
3. *Efficient*: Insect nervous systems are highly efficient, allowing for rapid processing and response to stimuli.
The insect nervous system is a remarkable example of evolutionary adaptation, enabling insects to thrive in diverse environments.
The insect nervous system is a remarkable example of evolutionary adaptation, enabling insects to thrive
GDGLSPGCOER - Git and GitHub Workshop.pptxazeenhodekar
This presentation covers the fundamentals of Git and version control in a practical, beginner-friendly way. Learn key commands, the Git data model, commit workflows, and how to collaborate effectively using Git — all explained with visuals, examples, and relatable humor.
"Basics of Heterocyclic Compounds and Their Naming Rules"rupalinirmalbpharm
This video is about heterocyclic compounds, which are chemical compounds with rings that include atoms like nitrogen, oxygen, or sulfur along with carbon. It covers:
Introduction – What heterocyclic compounds are.
Prefix for heteroatom – How to name the different non-carbon atoms in the ring.
Suffix for heterocyclic compounds – How to finish the name depending on the ring size and type.
Nomenclature rules – Simple rules for naming these compounds the right way.
Common rings – Examples of popular heterocyclic compounds used in real life.
Odoo Inventory Rules and Routes v17 - Odoo SlidesCeline George
Odoo's inventory management system is highly flexible and powerful, allowing businesses to efficiently manage their stock operations through the use of Rules and Routes.
The Pala kings were people-protectors. In fact, Gopal was elected to the throne only to end Matsya Nyaya. Bhagalpur Abhiledh states that Dharmapala imposed only fair taxes on the people. Rampala abolished the unjust taxes imposed by Bhima. The Pala rulers were lovers of learning. Vikramshila University was established by Dharmapala. He opened 50 other learning centers. A famous Buddhist scholar named Haribhadra was to be present in his court. Devpala appointed another Buddhist scholar named Veerdeva as the vice president of Nalanda Vihar. Among other scholars of this period, Sandhyakar Nandi, Chakrapani Dutta and Vajradatta are especially famous. Sandhyakar Nandi wrote the famous poem of this period 'Ramcharit'.
This chapter provides an in-depth overview of the viscosity of macromolecules, an essential concept in biophysics and medical sciences, especially in understanding fluid behavior like blood flow in the human body.
Key concepts covered include:
✅ Definition and Types of Viscosity: Dynamic vs. Kinematic viscosity, cohesion, and adhesion.
⚙️ Methods of Measuring Viscosity:
Rotary Viscometer
Vibrational Viscometer
Falling Object Method
Capillary Viscometer
🌡️ Factors Affecting Viscosity: Temperature, composition, flow rate.
🩺 Clinical Relevance: Impact of blood viscosity in cardiovascular health.
🌊 Fluid Dynamics: Laminar vs. turbulent flow, Reynolds number.
🔬 Extension Techniques:
Chromatography (adsorption, partition, TLC, etc.)
Electrophoresis (protein/DNA separation)
Sedimentation and Centrifugation methods.
THE 4 X 4 SEMANTIC MODEL: Semantics to Empower Services Science: Using Semantics at Middleware, Web Services and Business Levels
1. THE 4 X 4 SEMANTIC MODEL “ Semantics to Empower Services Science: Using Semantics at Middleware, Web Services and Business Levels ” Keynote at 9th International Conference on Enterprise Information Systems , Funchal, Madeira – Portugal, 12-16, June 2007. Amit Sheth* Kno.e.sis center, Wright State University, Dayton, OH Thanks: paper with Karthik Gomadam
2. Outline Motivation The Four Tiers Modeling, Enactment, Partner Services and Execution The Four Types Of Semantics Data, Functional, Non-Functional and Execution The 4 X 4 Model Unifying the four tiers using the four types of semantics The 4 X 4 Model In Action
3. Motivation Organizations are often involved in complex business transactions with various partners across the world For example, the business decisions are made in the US, technical and support services are in India and suppliers come from China. Variety of factors can affect the business objectives of an organization. Business processes need to more agile and dynamic
4. Motivation Supplier 1: Supplier 2: Technical Services Partner Gaming Manufacturer Initially, Supplier 1 is cheaper. If the manufacturer cannot relate to this change and react to it, the process of part procurement will be sub-optimal. The change in system, however must be done by Technical Services partner in India. CHALLENGE is to: Create enactment consistent with business objectives Correlate and reflect changes across different participating entities Be able to create agile and dynamic processes Change in Chinese Currency Makes supplier two cheaper!!
5. The Hard Problem Create partner-level requirements that are consistent with those of the business process Verify the correctness of the enactment with respect to the business process modeling Select and configure the partners at run time Identify and adapt efficiently to the various events that affect the optimality of the business process
6. Outline Motivation The Four Tiers Modeling, Enactment, Partner Services and Execution The Four Types Of Semantics Data, Functional, Non-Functional and Execution The 4 X 4 Model Unifying the four tiers using the four types of semantics The 4 X 4 Model In Action
7. The Four Tiers What do I want to do? How am I going to it? Who are my partners in this? What is my environment for execution?
8. The Four Tiers Business Specifications Tier (referred to as business process tier in the paper) Functional and non-functional aspects of the business specification are captured at this level. Example: Develop a SOA based solution for procuring various components to manufacture gaming hardware requests with the following constraints / requirements Must support XGP graphic processing Minimum 100 Gb disk space Product must never be out of inventory with retailers Level 3 security
9. The Four Tiers Workflow Tier Actual workflow enactment of the specification. Partners based on “ What they do” are identified. Not Who Example: Partners for the parts ordering specification are Suppliers for Graphics processor, Gaming Chip, Disk drive, Forecasting partner (to give retailer stock information and demand forecasting). Process level specification is broken down into partner level specification What to do when something goes wrong with this enactment (Adaptation and event identification)
10. The Four Tiers Workflow Tier (Contd..) Example partner requirement Disk Drive Partner: Must be able to do a purchase order for hard drives Will send PORequest according to Rosetta PO and expect a POResponse conforming to RosettaNet Communication must be over secure 128 bit encrypted channel. (Non-functional requirement) Disk capacity must be at least 100 Gb (non-functional)
11. The Four Tiers Partner Services Tier Captures the capabilities and requirements of potential partner services. Example of Disk drive service Accept input in Rosetta RequestPO and ebXML RequestPO formats and output in Rosetta POResponse format (data) Request purchase order for Hard drives (Functional) 128 Bit SSL communication Drives with capacities 80, 100 and 120 Gb
12. The Four Tiers Middleware Services Tier Captures the services offered by containing middleware systems. Includes capabilities related to deployment, security, load balancing, message routing and forwarding, service selection and switch, policy based message handling and event management.
13. Outline Motivation The Four Tiers Of A Business Process Modeling, Enactment, Partner Services and Execution The Four Types Of Semantics Data, Functional, Non-Functional and Execution The 4 X 4 Model Unifying the four tiers using the four types of semantics The 4 X 4 Model In Action
14. What does Semantics bring to the table? Better Reuse Semantic descriptions of services to help find relevant services Better Interoperability Beyond syntax to semantics, mapping of data exchanged between the services (very time consuming without semantics, just as XML in WSDL gives syntactic interoperability, SAWSDL gives semantic interoperability) Configuration/Composition Enable dynamic binding of partners Some degree of automation across process lifecycle Process Configuration (Discovery and Constraint analysis) Process Execution (Addressing run time heterogeneities like data heterogeneities.)
15. What does Semantics bring to the table? Better Reuse Semantic descriptions of services to help find relevant services Better Interoperability Beyond syntax to semantics, mapping of data exchanged between the services (very time consuming without semantics, just as XML in WSDL gives syntactic interoperability, SAWSDL gives semantic interoperability) Configuration/Composition Enable dynamic binding of partners Some degree of automation across process lifecycle Process Configuration (Discovery and Constraint analysis) Process Execution (Addressing run time heterogeneities like data heterogeneities.)
16. Semantics to Web Services: The ingredients Conceptual Model/Ontology An agreed upon model that captures the semantics of domain Common Nomenclature Domain Knowledge (facts) XML based service description Standards and specifications like WSDL for web service description, WS-Agreement for capturing agreements etc. Annotate the service description
18. Annotating types modelReference to establish a semantic association liftingSchemaMapping and loweringSchemaMapping to provide mappings between XML and semantic model <wsdl:types> (...) < complexType name=“Address"> <sequence> < element name=“StreetAd1“ type="xsd:string"/> < element name=“StreetAd2" type="xsd:string"/> ........... </sequence> < /complexType > (...) </wsdl:types> Address StreetAddress xsd:string xsd:string OWL ontology hasCity hasStreetAddress hasZip WSDL complex type element semantic match
19. Why use SAWSDL Build on existing Web Services standards using only extensibility elements Mechanism independent of the semantic representation language (though OWL is supported well) SAWSDL provides an elegant solution Help integration by providing mapping to agreed upon domain models (ontologies, standards like Rosetta Net, ebXML) Better documentation by adding functional annotation Ease in tool upgrades e.g. wsif / axis invocation Is a W3C candidate recommendation
20. What can we support or demonstrate today API for handling SAWSDL documents: SAWSDL4J Tool for annotating WSDL services to produce SAWSDL: Radiant and for discovery: Lumina Using SAWSDL with UDDI for Discovery: MWSDIr Using SAWSDL with Apache Axis for Data Mediation Using SAWSDL with WS-BPEL for run-time binding Early Examples of SAWSDL annotated services: biomedical research Also: Semantic Tools for Web Services by IBM alphaWorks WSMO Studio , more mentioned by Jacek
25. User specified mappings from Web service message element to semantic model concept (say OWL Ontology) upcast : from WS message element to OWL concept Downcast : from OWL concept to WS message element Execution: Data Mediation <POOntology:has_StreetAddress rdf:datatype="xs:string"> { fn:concat($a/streetAddr1 , " ", $a/streetAddr2 ) } </POOntology:has_StreetAddress>
27. Web services interoperate by re-using these mappings. Ontologies now a vehicle for Web services to resolve message level heterogeneities Execution: Data Mediation
28. Four types of semantics Data Semantics: What are the inputs and outputs of a service Functional Semantics: What does a service do? Non-Functional Semantics: The non-functional requirements and capabilities of a service Execution Semantics: What is the execution context and the task skeleton (execution states) associated with this service
34. Semantics for Technical Services Semantics Required for Web Processes Development / Description / Annotation Execution, Adaptation and Mediation BPWS4J, activeBPEL, WSMX METEOR-S WSDL, WSDL-S, SAWSDL, WSMO, OWL-S METEOR-S (MWSAF) Execution Semantics QoS Semantics Functional Semantics Data / Information Semantics Composition, Configuration and Negotiation BPEL, WS-Agreement, WS-Policy METEOR-S (MWSCF) Publication / Discovery (Semantic) UDDI METEOR-S (MWSDI)
35. Outline Motivation The Four Tiers Of A Business Process Modeling, Enactment, Partner Services and Execution The Four Types Of Semantics Data, Functional, Non-Functional and Execution The 4 X 4 Model Unifying the four tiers using the four types of semantics The 4 X 4 Model In Action
36. Semantics for the 4 X 4 Model Currently, each tier has its own standard modeling language, e.g. UML or BPMN at Business Process Tier, BPEL for Workflow Enactment Tier, SAWSDL/ WSDL at Partner Services Tier and config files/WSDL at Middleware Services Tier Becomes hard to correlate different pieces of the puzzle A semantically enriched model that allows us to capture the semantics at each of the four tiers
37. The 4 X 4 Model The 4 X 4 model does not intend to replace any of the current languages. It is a way to add additional description. Can be represented by using semantic templates. That brings us to What are semantic Templates?
38. Semantic templates A way of capturing data / functional /non-functional / execution semantics
39. Example of a semantic template in the supply chain domain
41. Why the semantics? Business Specification Tier: Need is to capture the functional and non-functional specification. Hence we capture functional and non-functional semantics. Workflow enactment Tier: Captures the data flow, control flow and the partner level specifications. Also addresses adaptation. Hence we need all four types of semantics.
42. Why the semantics? Partner Services Tier: Must allow description of partner services including inputs, outputs, what the service offers and the non-functional guarantees and requirements. Data, Functional and Non-Functional semantics Middleware Services Tier: Must advertise middleware level capabilities and the policies associated with them. Data mediation can be thought of a middleware level service. Adaptation capabilities must be built into middleware. All four semantics are needed at this level.
43. Outline Motivation The Four Tiers Of A Business Process Modeling, Enactment, Partner Services and Execution The Four Types Of Semantics Data, Functional, Non-Functional and Execution The 4 X 4 Model Unifying the four tiers using the four types of semantics The 4 X 4 Model In Action
45. 4 X 4 Model in Action Semantic Templates for capturing process and partner level specifications SAWSDL used for SOAP based WS in Semantic publishing and discovery of services Dynamic binding Adaptation Data mediation SA-REST (XML + Microformats) Smashups Integration of REST based services Enhanced policy descriptions Service selection Process adaptation (Adaptation policies)
46. 4 x4 Model in Action: Summary Example A Manufacturer needs to order various components Model business specifications Model Partner specifications Capture adaptation rules and events Needs to include human elements Needs to capture the risk involved in various actions and estimate the probability of various events. Enact and execute business process How to capture and understand the System, Service and Human aspects ? The 4 x 4 Model presents an unified model that integrates the different tiers, that allows to semantically relate the different components across different layers
47. Illustrating Dynamic Configuration Being able to bind partners to a workflow during execution time Key tasks include Modeling Creating process and partner level specifications Workflows created with partners described using semantic template Execution Discovery of partners (To be able to discover, we need to address publication as well) Address data heterogeneity Optimization and Adaptation
48. Conclusions: The 4 x 4 Model in a Nutshell The four tiers in Business process modeling are identified as Business Process Tier, Workflow Enactment tier, Partner Services Tier and Middleware Services Tier Four types of semantics in SOA lifecycle Data, Functional, Non-Functional and Execution 4 x 4 Model integrates the four tiers in business process modeling with the four types of semantics Creates a unified construct to relate the different tiers Can be captured using Semantic Templates For SOAP services, Semantic Templates are defined using SAWSDL and Policy constructs For REST services, Semantic Tempaltes are defined using XML and Microformats (RDFA)
49. Conclusion: What does Semantics Bring to the Table? Better Reuse Semantic descriptions of services to help find relevant services Allows to study data, functional and non-functional variations between the different tiers Better Interoperability Beyond syntax to semantics, mapping of data exchanged between the services (very time consuming without semantics, just as XML in WSDL gives syntactic interoperability, SAWSDL gives semantic interoperability) Functional mediation to address different interaction protocols Configuration/Composition Enable dynamic binding of partners Create (S)Mashups dynamically Optimization and adaptation during run time Verify enactments against corresponding business process specifications
50. Some degree of automation across process lifecycle Process Configuration (Discovery and Constraint analysis) Process Execution (Addressing run time heterogeneities and exceptions) Conclusion: What does Semantics Bring to the Table?
Editor's Notes
#8: In Role of Semantics for Workflow Enactment Tier: change consistence to consistency. In Technologies for Business Process Tier, add BPMN
#10: What Who point: In the insurance example, the fact that we need a DMV partner, a credit bureau and cc processing are identified. Who are the actual partners that we will bind to is not. This is deferred to execution time. This is important to understand the dynamism of the 4 X 4.
#11: What Who point: In the insurance example, the fact that we need a DMV partner, a credit bureau and cc processing are identified. Who are the actual partners that we will bind to is not. This is deferred to execution time. This is important to understand the dynamism of the 4 X 4.
#12: What Who point: In the insurance example, the fact that we need a DMV partner, a credit bureau and cc processing are identified. Who are the actual partners that we will bind to is not. This is deferred to execution time. This is important to understand the dynamism of the 4 X 4.
#30: Intalio n3 : Completer BPMS..design, deploy, execute, analyze and optimize processes…brochure says it supports BPML specification
#45: This picture illustrates the coming together of the 4 tiers of business process and how the 4 types of semantics facilitates this. At the heart of this modeling, is the grounding to ontologies. Further this slide also illustrates the interaction between the different tiers. The specifications in the process tier are enacted as workflows in the enactment tier. These workflows are deployed in a middleware that provides deployment and messaging services. The partner services are also deployed in middleware systems. In addition to these, the middleware services tier providers services such as discovery and mediation and message routing. Process Modeling Tier: Conventional workflow specifications or Mashup/Smashup specifications are captured at this tier. Conventional workflow specifications are captured using semantic templates for SOAP services while Smashup specifications are captured using micro-format enhanced SAREST. Workflow Enactment Tier: Based on the process level specifications, partner level specifications are created and workflows are enacted with these partner level specifications. The various tasks in the workflow are described by the operations in the corresponding semantic template. For example, in a supply chain workflow for procuring various components, the partner level specifications for each component is captured. A workflow is then created where a task corresponding to a functional requirement in the partner level specifications. In the context of light weight services, Smashups are created to enact out service compositions. Service compositions are captured as client side objects, which are annoated with micro formats. The service at the server side based on the semantics of the client side objects that are sent to it, invokes the relevant services in the order while making sure of the interaction and role. Service discovery and process configuration is done using the partner level specifications. Adaptation strategies such as events that are relevant, event subscription and notification management are done based on the functional and non-functional processs and partner level specifications. Partner service tier: IN the classical service context, partner services capture their capabilities and requirements in SAWSDL. In case of light weight services, annotated pages with RDFA and annotated XML inputs/ output allows for publication and discovery of these services. Middleware Services Tier: The capabilities of the middleware to support semantic web services, deployment, message processing, event handling and data mediation can be captured. As we can see in the example, the middleware services tier provides container services for both the enacted workflow as well as for partner services.