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Highlights from “Future of XML Vocabularies” Symposium –April 2005

Highlights from “Future of XML Vocabularies” Symposium –April 2005. Justice XML Vocabularies for social networks RFID in supply chains oBIX– open building information exchange. Justice XML (JML) The Global Justice XML Data Model. Ellen Perry, MTG Management Consultants, L.L.C.

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Highlights from “Future of XML Vocabularies” Symposium –April 2005

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  1. Highlights from “Future of XML Vocabularies” Symposium –April 2005 • Justice XML • Vocabularies for social networks • RFID in supply chains • oBIX– open building information exchange

  2. Justice XML (JML)The Global Justice XML Data Model Ellen Perry, MTG Management Consultants, L.L.C. Tom Carlson, National Center for State Courts

  3. Our Criminal Justice System Enter System Prosecute/Pretrial Adjudication Sentencing Corrections 1967

  4. Activity Investigate IncidentRpt Incident Arrest ArrestWarrant Book Confine ArrestRpt Charge Prosecute Acquit BookingRpt Indict Adjudicate Sentence ChargeDoc Sentence Order Fine Incarcerate Supervise CaseFile Protect Order Parole Pardon Release Reusable Information Objects Justice XML

  5. XML Vocabularies for Online Communities: Past, Present, and Future By William Barnhill

  6. Vocabulary Challenges • Tool and content authors in domain are often not graph theory experts, and want to read/write raw data • No well-defined set of required information to describe a person • Vocabulary will likely be extended within a short time for specific types of networks • For many networks, keeping data within communities of trust is a necessity • The amount of data within a Social Network can be very large, requiring efficient parsing

  7. Features for expressiveness • Typed nodes (types may include "person", "resource", "organization", "knowledge", etc) • Multiple sets of nodes of the same type (to express multiple units within the company, etc) • Multiple typed attributes per node • Typed edges • Multiple typed attributes per edge • Multiple graphs (sets of edges), and dynamic network data, expressed within the same file

  8. Some XML vocabularies for possible use by Social Software • DyNetML • XFN • Feed variants (Attention, RSS, Atom) • OWL/RDF • XDI

  9. The Multi-Layer Data Model Vocabulary And Schemas For EPC/RFID A Joint Research Effort Between Raining Data Corporation And MIT Web Services WAN SIG Tentative Release Date July 2005

  10. Next-Gen Supply Chain And The Technology Evolution • The Opportunity: • 90% Of Real Gains In Deploying RFID/EPC Solutions Will Happen In The COLLABORATION Zone. • The Challenge: • Using XML And Web Services Technologies To Work Together In A Standards-Based Manner To Improve The Velocity And Flow Of Funds, Goods And Information Throughout Complex Global Supply Chains While Reducing Production, Distribution and Inventory Costs.

  11. The Next-Gen Supply Chain – EPC/RFID EPC NETWORK FUNCTIONAL STACK FEDERATED EPC NETWORK

  12. The Multi-Layer Data Model Layers COARSE GRAINED XML XML GRANULARITY OF INFORMATION AND EVENTS XQUERY FINE GRAINED

  13. Connecting Buildings to the Enterprise Paul Ehrlich, PE President Building Intelligence Group Co-Chair of the OASIS oBIX Technical Committee

  14. Facility Management • Facility management covers real time control and monitoring of all mechanical and electrical systems in a building • Heating, ventilation, air conditioning (HVAC) • Fire alarm and security systems • Electrical distribution and metering • Other systems (medical gas, generators, etc.) • FMS Definition... • “A facility management system should be a comprehensive resource… a collection of data that helps you mange your business, whether it be the utilities, energy, human resources, work orders or inventories. “

  15. What kind of data? • Simple: Room Temperature of Lobby • Lengthy: List of people currently in East Wing with time of entry • Complex: Current state of all systems across an entire university campus • Reports: Variation of internal humidity of sports hall over the last 6 months

  16. How is the data accessed? • Data is accessed at a ‘Datapoint’ and exposed by a ‘Point Service’ • Datapoints are revealed by a ‘Discovery Service’ • Data trends are reported by a ‘History Service’ • Critical events are signalled by the ‘Alarm Service’

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