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Build UDEF Tools in the Cloud: II
The Open Group Conference, London, May 9-11, 2011UDEF Tools Workshop, May 9, 2011
Brand NiemannDirector and Senior Data Scientist, Semantic Community
http://semanticommunity.net May 9, 2011
http://semanticommunity.info/UDEF/Tools_Demo_for_London_Conference
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UDEF Workshop in London:Invitation to Participate
• For London we need to show the content of two or more different standards that attempt to address the same domain - in this case person data. It would also be helpful to identify at least one use case where someone might want to migrate data from one to another. We need to demonstrate how to analyze and map each to the UDEF and convert to the XML format that will enable use of the gap analysis tool. We will then demonstrate use of the gap analysis tool. See the gap analysis section for a brief summary.– http://www.opengroup.org/udefinfo/use/conops.htm#conops
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Distributed UDEF Architecture 1.1
• The white paper is to be the foundation for further development of distributed UDEF which (among others) is a requirement for the following parallel activities of The Open Group:– QLM workgroup needs distributed UDEF for semantic interoperability.– Jericho forum needs extended UDEF for federated identity
management interoperability.– TOGAF next version will need distributed UDEF for
Enterprise Interoperability.• Contact:
– Arnold van Overeem: [email protected]• My Comments: Semantic Interoperability, Federated Identity
Management Interoperability and TOGAF Next Version are all of great interest to me!
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http://www.opengroup.org/projects/udef/protected/revdoc.tpl?grid=3164
Overview• 1. Background• 2. Person
– A. Wikipedia– B. Federal Enterprise Architecture Data Reference Model Person:
Person Harmonization Workgroup– C. SEMIC.EU Person Information Ontology– D. David C. Hay Enterprise Model Patterns: Describing the World
• 3. Using UDEF To Harmonize Person– A. Spreadsheet – Gathering and Harmonizing– B. Spotfire – Mapping Relations and Visualizing
• 4. Some Conclusions and Recommendations• 5. Backup Slides
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1. Background• Convergence of Semantic Naming and Identification Technologies?: A
Joint Open Group, Federal Semantic Interoperability Community of Practice (SICoP), and Federal Metadata Management Consortium Conference, April 27, 2006, at the Hilton Crystal City, Arlington, Virginia.
• Federal Semantic Interoperability Community of Practice, 2003 - 2009. Restarting in 2011.
• Open Group Enterprise Vocabulary Workshops (May 20 and June 3, 2009).
• National Information Exchange Model (Donna Roy) and Universal Core Semantic Layer (Jim Schoening)
• Data.Gov Forums: Cross Domain Linking, Cross Domain Vocabularies, Domain Specific Vocabularies, and URI Schemes
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1. Background• Announcement: UDEF Deployment Workshop Planning Meeting:
– The Open Group Conference in San Diego in the week of 7 February 2011 will include a UDEF Deployment Workshop planning meeting. The purpose of this meeting will be to make plans for a UDEF Deployment Workshop to be held in conjunction with the Open Group conference in London in the week of May 9. The workshop itself will feature inter-operating products and systems that use the UDEF. Those systems may be physically at the conference or connected via the Internet. The planning meeting is for workshop participants to meet face-to-face to agree on the scenario and deployment details.
• Participated in the January 21, 2011, Teleconference and Provided a Brief Introduction and Demo (see next slide).
• Invited to provide a set of slides for the February 7th Meeting and to Participate Remotely.
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1. Background• Data Architecture Subcommittee - Open Government Vocabulary)
Working Group (January 12, 2011):– Cory Casanave Conclusion: The UK Government has done some great work
in this area that we can build on, it can be accessed here: http://www.cabinetoffice.gov.uk/medi...sector_uri.pdf
– In summary, all vocabularies, terms and concepts should have a URI. Each URI should point to both data and a web page that shows the data about that vocabulary, term or concept. Doing this one simple thing makes our vocabularies universally accessible on the semantic web.
– OGV WG Recommendation: Use the UK document as a basis for a US policy on minting URIs. All open government vocabularies should use permanent URIs.
• My Note: Cory’s recommendation is exactly what I have been doing in the wiki and I reference that key UK document:• http://semanticommunity.info/UDEF/Designing_URI_Sets_for_the_UK_Pub
lic_Sector 8
1. Background
• Editorials for Federal Computer Week:– 1. Making Individuals Into Information Architects and Preservationists.– 2. Data Services - What Data.gov and Many Other Things Should Be.– 3. Federal Cloud Computing: It can really happen if we can do our own IT!– 4. Gov 2.0 Platform Data Services with Cloud Computing: OMB Earmarks
Database.– 5. Gov 2.0 Platform Data Services with Cloud Computing: HealthDataGov.– 6. What’s In a Name for Open Government Data Sets?: Everything!– 7. Build Health Care Data Analytics in the Cloud: How patient and provider
data can be used to promote economic growth, improved health care, and save taxpayer’s money.
– 8. The Open Government Research and Development Summit: Ed Tufte Should Have Been in the House and Sooner!
9http://semanticommunity.info/A_Gov_2.0_spin_on_archiving_2.0_data
2. Person
• A. Wikipedia:– The concept of a person can be very challenging to define.
• A person (plural: persons or people; from Latin: persona, meaning "mask") is a human being, or an entity that has certain capacities or attributes associated with personhood, for example, in a particular moral or legal context.
• Such capacities or attributes can include agency, self-awareness, a notion of the past and future, and the possession of rights and duties, among others.
• However, the concept of a person is difficult to define in a way that is universally accepted, due to its historical and cultural variability and the controversies surrounding its use in some contexts.
10http://en.wikipedia.org/wiki/Person
2. Person
• B. Federal Enterprise Architecture Data Reference Model Person: Person Harmonization Workgroup– Data Architecture Subcommittee Meeting, January
11, 2007.– Bob Ridgely, OESAE Technical Advisor for Data
Administration & Enterprise Architecture.• SAA Disciplines: Lexicon of Terms, Rigorously enforced naming standards, Logical
value tables, Business Data Models (views of Enterprise Data Models that support specific business functions or projects.), and Availability of the above on the SSA intranet website.
– Kay Sybert, Enterprise Data Modeler to the SSA.• See her May 5th updates on Wiki Page on Title Slide.
11http://semanticommunity.info/@api/deki/files/2465/=Person01112007.ppt
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2. Person
• B. Federal Enterprise Architecture Data Reference Model Person: Person Harmonization Workgroup– Gathering Information:
• We asked those on the workgroup to share their models of PERSON with us.– We received documents from the Department of the Interior (DOI), the
Veterans’ Administration (VA), the Federal Aviation Administration (FAA), and the Environmental Protection Agency (EPA).
– Analyzing the Data:• We compared the entities and attributes from all the documentation.• We created an Excel Workbook.
– The first sheet contains all the entities and attributes from each model.– The second sheet contains a mapping of the entities from the other agencies
to those of the Social Security Administration (SSA)– The third sheets contains the entities, attributes, and their definitions from
the SSA FEADRM Model.
2. Person
• B. Federal Enterprise Architecture Data Reference Model Person: Person Harmonization Workgroup– Producing a FEA DRM PERSON Model:
• We started with an extract of the SSA Enterprise Data Model (EDM). We model using entity relationship diagrams (ERD) in the ERwin tool.
• We adjusted it to make it less SSA-centric and to include granularity required to span agencies.
• We named it ‘Federal Enterprise Architecture Data Reference Model Person’ and defined it as “This Business Data Model (BDM) is a view of the United States Government Enterprise Data Model (EDM) containing the data required to support the characterization and relationships of a uniquely identified person.”
• You can view it as a PDF document. The ERD starts on page 3 and the subject areas are in alphabetical order (see next slide). If you have ERwin, contact us and we can send you the model in that format.
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2. Person
14
http://semanticommunity.info/@api/deki/files/10786/=Person_Concepts_and_UDEF_Mappings.xlsx
2. Person
15http://semanticommunity.info/@api/deki/files/2479/=Person01112007.pdf
Federal Enterprise Architecture Data Reference Model PersonTHIS BUSINESS MODEL IS A VIEW OF THE UNITED STATES GOVERNMENT ENTERPRISE MODEL CONTAINING THE DATA REQUIRED TO SUPPORT THE CHARACTERIZATION AND RELATIONSHIPS OF A UNIQUELY IDENTIFIED PERSON.Prepared by Social Security Administration, Data Administration 6/19/2006 9:58 AM
2. Person
• B. Federal Enterprise Architecture Data Reference Model Person: Person Harmonization Workgroup– Observations:
• A data model should have a point of view, we should have a common one at the Federal level.
• Everyone should be modeling business data rather than creating logical data base models.
• PERSON is probably the area in which resides most of the non-administrative sharable data. This is what we at SSA call “common shared.”
• The definition of business concepts represented by entities at the “top” of the data model should not be in terms so rigorously tied to the business of any one agency.
• Data that are “regulated” require formal agreement to be sharable.• PERSON cannot be addressed in a vacuum. The concepts of organization, party, and
role should be addressed at the same time.
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2. Person
• B. Federal Enterprise Architecture Data Reference Model Person: Person Harmonization Workgroup– Challenges:
• Allowing aliases in naming without underlying concept creep.• Identifying an authoritative source for a concept.• Formalizing a vocabulary for naming.• Agreeing on the description notation at the Business Reference Model
level.• Managing configurations and versions.• Structuring a process for DRM governance.
– Some Proposed Next Steps:• Initiate contacts to evaluate NIEM.• Establish guidelines for data exchange.
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2. Person
18http://www.semic.eu/semic/view/Asset/Asset.SingleView.xhtml?id=59710
C. SEMIC.EU Person Information Ontology
2. Person• C. Just answering the easy question: Does the implementation of the
SEMIC.EU Core Person assure semantic interoperability? We have to answer: no. Using Core Concepts like the European concept of a person must be seen as a first building block to achieve interoperability and free data exchange in Europe. Stakeholders with a European focus on data exchange, initiatives and projects will find mappings and tailored implementations from other Member States initiatives or practical implementations of other domains. The availability of practical knowledge, of further implementations, and specified mappings between the SEMIC.EU Core Concept of person and its proven translations to other European languages, legal contexts and specific domains must be seen as the real genesis of benefit and the step forward in achieving interoperability throughout Europe.
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http://semanticommunity.info/Build_SEMIC.EU_in_the_Cloud/SEMIC.EU_Core_Person_Specification
2. Person• C. Figure 1 shows that when defining
a data exchange specification with a broad, almost universal audience the balance between the two extreme positions “Flexibility” and “Interoperability” has to be well defined. On the one hand harmonisation and standardisation of data can enable interoperability to a large extent. On the other hand being too restrictive may lead to an elaborated data model with an “academic semantic interoperability” that no real use case is able to implement.
20http://semanticommunity.info/Build_SEMIC.EU_in_the_Cloud/SEMIC.EU_Core_Person_Specification
2. Person• C. The authors decided to set the
balance between “Interoperability due to Standardisation” and “serviceability and acceptance thanks to certain liberty in implementing” as follows:– a. Name of the elements– b. Semantic meaning– c. Multiplicity in general
(Cardinalities None, One, More)– d. Suggestions for abstract data
types (String, Number, Date)
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2. Person
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http://semanticommunity.info/@api/deki/files/10786/=Person_Concepts_and_UDEF_Mappings.xlsx
2. Person
• D. David C. Hay New Book and Web Site:– Enterprise Model Patterns: Describing the World and Essential Strategies– See his April 29th updates on Wiki Page on Title Slide.
• D. Library: Introduction to Semantic & Ontology:– Data Modelling, RDF, and OWL (Part One: An Introduction to Ontologies) (Apr 2006)– Data Modeling, RDF, & OWL (Part Two: Converting Data Model Entity Classes and
Attributes to OWL) (Jul 2006)– Data Modeling, RDF, & OWL (Part Three: Converting Data Model Relationships to OWL)
(Oct 2006)– Semantics, Ontologies, and Data Modeling (Jun 2008)
• SemTech 2007 Presentation! Link to Slides for Library of Congress Government Data Model
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2. Person
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D. Figure 1-7: Zooming in a Data Model 15
D. Unfortunately, there is no “Google Data Models” tool that allows us dynamically to zoom in and out of the models’ abstraction layers. But it is to be hoped that perhaps this book will provide a guide to what such a tool might look like. Pages XXX-XXXi.
15 Scroll bar Copyright 2010, Google.
2. Person
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Accountin
g
Facility
Level 0
Level 1
Level 2
Metadata
Level 3
Parties Geography Assets Activities Timing
Info
rmatio
n
Resourc
e
Template
FacilitiesHuman
ResourcesMarketing Contracts
Manufacturing
CriminalJustice
Biotechnology BankingOil
ExplorationHighway
Maintenance
D. This book is organized in terms of several specifically defined Levels of Abstraction. Figure 3-1 shows the structure in graphic form.
NIEM Person
People
Laboratory
2. Person
• D. Enterprise Model Patterns: Describing the World– Part Two: Abstraction Level One: The Enterprise Model – This section focuses on the four primary
components of any corporate, enterprise-wide conceptual model: people and organizations, geography, physical assets, activities, and time.
– Part Five: Abstraction Level Three: Industry Models – This section covers the elements that make certain industries unique. In each case, a company in that industry can use the Level One Enterprise Model for most of its requirements. There are only a few specialized areas of interest. Examples of these are described within this section.• PART FIVE Abstraction Level 3: Some Industry-Specific Examples• The Examples (5) • Advice
– CHAPTER 18 Criminal Justice» Cases
• Evidence and Status• Linking to the Enterprise Model• Events
» People and Organizations• Characteristics and Categories• Employment• Roles
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2. Person• D. Chapter 18. Criminal Justice: The model presented here is based on the “Global Justice
XML Data Model” (GJXDM), developed for the United States Department of Justice in 2007. That model (and its successor, the National Enterprise Information Model) were developed using XML. That notation is ideal for data communication, but has no ability to capture the semantics of the terms it is communicating. This model was derived from the documentation of GJXDM. It looks suspiciously like the Enterprise (Level 1) Model, although one would never suspect that, looking at the XML code of its original rendering.
• D. A Word of Advice: As a modeler, you are expected ultimately to produce a model that accurately and powerfully represents the business being modeled. But neither the industry model fragments in Section Five, nor the functional model fragments in Section Four are the final correct answers. What they are intended to do is to provide insights into the process required to come up with that definitive model, using the patterns of Levels 1 and 2.
• D. Summary: The specialized models in Parts Four and Five of this book are just that—specialized. On the face of it each of them doesn’t seem to apply to many of the readers of this book. But they are presented not just as potential solutions to the problems that some of you encounter. More significantly, they are intended to broaden the views of all. One of the great things about data modeling is that it is a wonderful way to learn about the world.
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2. Person• D. Chapter 18. Criminal Justice:
– The model presented here is based on something called the “Global Justice XML Data Model” (GJXDM)—developed in XML by the United States Department of Justice. Since the objective of the model was to address problems of inter-communications among departments, XML was chosen because of its strength in creating communications structures. Unfortunately, XML is not as good at helping people understand the behind of those communications. The model created here is an attempt to reveal more graphically the semantic structure of GJXDM. It was done as an exercise, so it has not yet been blessed by anyone in the justice community. There is no consensus about the “truth” of the model. Your author contends, however, that it is a much better vehicle for acquiring such a consensus than is XML.
– Subsequently the Justice Department teamed up with the Department of Homeland Security to create the “National Information Exchange Model” (NIEM). This entails a more sophisticated approach to XML to make it a bit more constrained, and therefore a bit more readable at least to the relational database community. It has also been extended beyond the realm of Justice Department concerns to be more available to other agencies in other fields. It is to be hoped that at some point a more graphic version of the NIEM model will be available to allow for validation by the non-technical community that it must serve.
– You will note, by the way, that while the language of the model shown here is mostly specific to the justice community, the underlying structure is very similar to the Enterprise Model of Level 1.
– The model is in two primary parts: one describes cases, and the other describes the people and organizations involved in pursuing them.
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2. Person
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D. Figure 18-9: Roles
D. Figure 18-9 finally links the People and Organizations part of the model to the Cases part of the model shown previously. In it we see that people and organizations play multiple roles in carrying out both Cases and Activities.
3. Using UDEF To Harmonize Person
30
http://semanticommunity.info/@api/deki/files/10786/=Person_Concepts_and_UDEF_Mappings.xlsx
3. Using UDEF To Harmonize Person
• Contents of Spreadsheet:– Cover Page – Initial Harmonization– UDEF V17_1 Person Objects– NIEM Person Type– UCore-SL 1.0– SEMIC.EU Person– US SSA DRM Person
• Note: More work is needed before this spreadsheet is ready for Spotfire - Mapping Relations and Visualizing.
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4. Some Conclusions and Recommendations
• Semantic Interoperability, Federated Identity Management Interoperability and TOGAF Next Version are all of great interest to me!
• A. Wikipedia: The concept of a person can be very challenging to define.• B. Federal Enterprise Architecture Data Reference Model Person: Person
Harmonization Workgroup led by Bob Ridgely at the US Social Security Administration appears to be the best work we have in the US.
• C. The SEMIC.EU Core Concept of person is the real genesis of benefit and the step forward in achieving interoperability throughout Europe.
• D. David Hay’s new book “Enterprise Model Patterns: Describing the World” provides the broader context needed for Person and the specifics for how to improve the Global Justice XML Data Model and NIEM and other Person models.
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4. Some Conclusions and Recommendations
• My Experiences (Editorial for Federal Computer Week in process):– Standardizing “Eforms for Egov” for Mark Forman with the eGrants Schema and
Web Services as Chair of the Federal CIOC’s Web Services Working Group;• Move everybody up in interoperability instead of ‘rip-n-replace’.
– Standardizing SOA and Semantic Interoperability for the Federal CIO Council with multiple pilots, ontology, and semantic technologies as Co-chair of the Federal CIOC’s SOA and SICoP Communities of Practice; and• ‘Show me a SOA’ and get the ‘Medici Effect: the model-driven approach and the best and brightest will
find one another and collaborate to innovate, facilitated by the technology itself”.
– Standardizing cloud computing for Vivek Kundra and Aneesh Chopra for desktops, Gov 2.0 platforms, data centers, and health data as Director and Senior Data Scientist of the Semantic Community and formerly senior enterprise architect and senior data scientist for the US EPA.• ‘Think outside the box’ and foster open collaboration with open standards in multiple pilots.
– I especially want to put the recent Federal CIOC’s reports on NIEM into a broader perspective:• See http://semanticommunity.info/National_Information_Exchange_Model/Assessment_Report
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4. Some Conclusions and Recommendations
Program Champion CoP Leader Standards
eForms for eGov Mark Forman, OMB Rick Rogers, Fenestra Technologies
eGrants XML Schema and Web Services
Federal SOA CoP Roy Maybury, DoD Cory Casanave, Model Driven Solutions
Web Services and Open Group MDA and SoAML
Federal Semantic Interoperability CoP
David Wennergren, Navy CIO
Rick Morris, US Army, and Mills Davis, Project10X
W3C Semantic Web in Semantic Technologies
Cloud Computing Desktop for OGD & Data.gov/semantic
Vivek Kundra, Federal CIO
Brand Niemann, US EPA and Semantic Community
Web Oriented Architecure (MindTouch)
Gov 2.0 Platform for Data Science Products and 5 Stars of LOD
Aneesh Chopra, Federal CTOTim Berners-Lee, W3C Director
Brand Niemann, US EPA and Semantic Community
Open and Quality Data Visualizations (Spotfire)
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Data Modeling with Context
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Data Modeling with Context
• Data Modeling with a Broader Context:– Source, Description, and URL– Topic, Description, and URL– Sub-topic and URL– Table, URL, Headnote, Symbol, Footnotes, Source,
& More Information – Data Element 1, URL, Data Element 2, URL, etc.
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Smart Mapping: Automatic Creation of Information Models
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Smart Mapping: Automatic Creation of Information Models
• Spotfire 3.3 Information Services users can automatically generate 1-to-1 mappings of the existing tables and columns in their Data Sources. Just generate a Data Source in Spotfire, then right click it and select “Create Default Information Model…” This helps a lot when the work has already been done to nicely model and expose tables for business applications such as Spotfire, so the mapping step is more about transparency than transformation. For example, if you use Spotfire Application Data Services, you do the work in ADS to expose Spotfire-ready tables and columns, so a simple transparent mapping of those elements through Spotfire Information Services can now be accomplished in one click. Note that the automated creation will work through nested levels of data objects in the data source you supply.
• The result is a folder structure that matches the catalogs, schemas etc. that were selected with a column element for each column and an information link for each table containing those column elements. Procedures will get a procedure element and an information link of their own if they return data.
38
http://semanticommunity.info/@api/deki/files/10975/=Whats_New_in_Spotfire_3.3.pdf
Backup Slides
• From The Open Group San Diego Conference, UDEF Deployment Workshop Planning Meeting Presentation, February 7, 2011:– Build UDEF Tools in the Cloud: I• 2. The UDEF Project• 3. UDEF Definitions• 4. Spotfire• 5. Some Next Steps
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2. The UDEF Project
• Known familiarly as 'the Dewey Decimal Classification System for Data', the Universal Data Element Framework (UDEF) provides a conceptual naming convention framework with associated structured unique identifiers for indexing and aligning semantically equivalent concepts. It is a key tool for semantic interoperability and information management.
• The UDEF is a standard way of indexing enterprise information that can produce big cost savings. The UDEF project is the most important activity of the Semantic Interoperability Work Group.
Source: http://www.opengroup.org/projects/udef/40
3. UDEF Definitions
• High-Level Definitions:– http://www.opengroup.org/udefinfo/htm/en_defs.htm
• Properties:– http://www.opengroup.org/udefinfo/htm/en_propertie
s.htm• Objects:
– http://www.opengroup.org/udefinfo/htm/en_objects.htm
• Note: Clicked on Full Property Tree and Full Object Tree, Expanded, and Copied to Spreadsheet and to Wiki. Then Imported Into Spotfire and Built a Pilot Application. 41
3. UDEF Definitions
42
http://www.opengroup.org/udefinfo/htm/en_defs.htm
3. UDEF Definitions
43
http://www.opengroup.org/udefinfo/htm/en_objects.htm
3. UDEF Definitions
44http://semanticommunity.info/@api/deki/files/1172/=UDEF.xls
3. UDEF Definitions
45http://semanticommunity.info/UDEF/UDEF_Full_Property_Tree
4. Spotfire
46http://goto.spotfire.com/g/?KXLMSEWRM9
See Terms of Use.Limited to ThreeSpreadsheets of Less Than 10 MB.
4. Spotfire
47
PC Desktop
4. Spotfire
48Web Player
5. Some Next Steps
• Get Feedback and Address It.• Explore Using the UDEF Working Spreadsheets
to Make Real-Time Updates in Spotfire (Private).• Prepare for the London Meeting.• Explore Possible Collaboration with the NCIOC
Cloud Computing Work Group and Pattern Repository Pilot:– See
http://semanticommunity.info/Network_Centricity
49
