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October 19, 20051 The Semantic Web: What is it and why should you care? Semantic Arts, Inc. Dave McComb for Toronto IRMAC/DAMA Oct 19, 2005.

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Presentation on theme: "October 19, 20051 The Semantic Web: What is it and why should you care? Semantic Arts, Inc. Dave McComb for Toronto IRMAC/DAMA Oct 19, 2005."— Presentation transcript:

1 October 19, The Semantic Web: What is it and why should you care? Semantic Arts, Inc. Dave McComb for Toronto IRMAC/DAMA Oct 19, 2005

2 October 19, Objectives Semantics > Good Definitions Exotic Terminology Pursue this further

3 October 19, Semantic Web Semantic Technology Semantic Methodology, Design & Approach

4 October 19, Part 1: Intro, Concepts and Methods Part 2: Semantic Metadata and Annotated Data Part 3: Semantic Web Part 4: Demos

5 October 19, Semantic Concepts, Discipline and Methods Part 1: Intro, Concepts and Methods

6 October 19, Semantics The study of meaning (sometimes the study of the meaning of words)

7 October 19, 20057

8 8

9 9 Structure and Metadata You can now deal with thousands, even millions of transactions, by knowing only a small amount of metadata

10 October 19, Drowning in Metadata Thousands -> millions of bits of metadata Meta metadata? XMI/MOF/ CWM Millions -> Billions of instances in hundreds of databases Commit to share ontologies to get back to thousands/ tens of thousands of concepts

11 October 19, Operative Semantics Some of these fields are known to the system and cause overt changes in behavior

12 October 19, Others are more subtle This one shows up on the detailed P&L reports This one shows up in the AP list of bills to pay This one shows up on the check

13 October 19, None of this is mentioned in the user manual or on line help text

14 October 19, Scale issues

15 October 19, Carver Mead

16 October 19, Flat Earth Schema We need to get up out of the weeds Higher level, business concepts

17 October 19, Semantic Framework

18 October 19, Anna wierzbicka Semantics: Primes and Universals Anna Wierzbicka

19 October 19, Semantic Primes Anna Wierzbicka

20 October 19, First Prime Discrete Physical Object –Something to which you could (potentially) attach a unique bar code

21 October 19, Physical Items

22 October 19, Semantic Primes for Business –People –Animals –Physical Made Items –Buildings –Landmarks –Physical Container –Homogenous Material –Legal Entities –Historical Events –Conversion –Scheduled Events –Defined Events –Measurement –Estimate –Monetary Amount –Reference Value –Decision –Request –Rights –Permission –Offer –Order (Directive) –Contract/Order –Messages –Documents –Inventions –Programs

23 October 19, Garn? Narn Role of context

24 October 19, Context How many addresses do you have in your database? One of our clients has 116. How many types of addresses are there?

25 October 19, Context Where When Relationships Purpose What differentiates the 116? Context, such as

26 October 19, Categories How Categories Inform Us

27 October 19, Example Categories Inventory system (categories disguised as attributes): Attractive Insurance spare Fast/Slow Moving A/B/C High/Low Value Degradable

28 October 19, Example Categories Inventory system (categories disguised as entities): Equipment Kits Parts Tools Serialized Parts Raw Material Assemblies Phantoms

29 October 19, Example Categories Inventory system (categories disguised as states): Obsolete Reserved Out of Stock In Inspection Discontinued On Order

30 October 19, Example Categories Inventory system (categories disguised as relations): On consignment In Use Stock for this warehouse Preferred Supplier Issued to

31 October 19, What are we doing??? We categorize things all the time. As data modelers we set up other peoples categories for them. We decide whether their categories will be expressed as: –Entities –Attributes (codes, enums, flags and labels) –States –Relations –Classes –Types –etc.

32 October 19, Category Definition Encarta: a group or set of things, people, or actions that are classified together because of common characteristics Cambridge (English): a type, or a group of things having some features that are the same Cambridge (American): a grouping of people or things by type in any systematic arrangement. (The light trucks weigh less than 5,000 pounds and are in a category that includes minivans, pickups, and sport utility vehicles) Infoplease: any general or comprehensive division; a class Encyclopedia.com: philosophical term that literally means predication or assertion

33 October 19, Operative Definition of Categories Semantic Arts:A description of a set of things that contains: –A set of testable membership criteria that can either improve or reduce our confidence in the membership –A set of additional information that can be inferred from the membership –A set of behaviors that can be applied to members of the category –A set of questions that can be applied to the instance to gather property or relationship values

34 October 19, Hidden Categories Almost every IF…THEN… or CASE… statement contains a category So does the procedures manual You are aware of some of them

35 October 19, Categories and Behavior The reason to create a new category is if the distinction (the new category) will be treated differently, behaviorally –By a program, or –By a human

36 October 19, Categories and Behavior The reason to subsume categories (through a taxonomy or just collapse them) is if they can be treated the same, behaviorally

37 October 19, Wrap on Discipline

38 October 19, Part 2: Semantic Metadata and Annotated Data

39 October 19, Metadata and Annotated Data

40 October 19, Content: FOAF Friend Of A Friend Ontology for contacts

41 October 19, Content: Dublin Core

42 October 19, So, how do we do this?

43 October 19, Business Vocabulary Not whether, but –when: as you come across the terms, or up front? –what source: source documents, interviews or existing systems? –how: defining terms or concepts?

44 October 19, Business Vocabulary Schema Jargon

45 October 19, Injured workers -- representatives Information contained in the claim files and records of injured workers, under the provisions of this title, shall be deemed confidential and shall not be open to public inspection (other than to public employees in the performance of their official duties), but representatives of a claimant, be it an individual or an organization, may review a claim file or receive specific information therefore upon the presentation of the signed authorization of the claimant.

46 October 19, Employers -- Representatives Employers or their duly authorized representatives may review any files of their own injured workers in connection with any pending claims.

47 October 19, Claimant A claimant may review his or her claim file if the director determines, pursuant to criteria adopted by rule, that the review is in the claimant's interest.

48 October 19, Patient Except as otherwise provided by law, all treatment records shall remain confidential. Treatment records may be released only to the persons designated in this section, or to other persons designated in an informed written consent of the patient….[much more]

49 October 19, Child Victims Information revealing the identity of child victims of sexual assault who are under age eighteen is confidential and not subject to public disclosure. Identifying information means the child victim's name, address, location, photograph, and in cases in which the child victim is a relative or stepchild of the alleged perpetrator, identification of the relationship between the child and the alleged perpetrator.

50 October 19, Dilberts Boss Understands This

51 October 19, How to Sources –Documents –Existing systems –Controlled Vocabularies –Interviews Techniques –Distinctionary –Concept -> Term

52 October 19, Documents Information contained in the claim files and records of injured workers, under the provisions of this title, shall be deemed confidential and shall not be open to public inspection (other than to public employees in the performance of their official duties), but representatives of a claimant, be it an individual or an organization, may review a claim file or receive specific information therefore upon the presentation of the signed authorization of the claimant.

53 October 19, Existing systems

54 October 19, Vocabulary Item: A variety of language unique to an individual Idiolect

55 October 19, Every System We Design or Buy … … is another ideolect

56 October 19, Interviews Enumerate types Look for counter examples Look for similarities Synonyms

57 October 19, Warning: Definitions are hard to get consensus on And often not worth it

58 October 19, Example good Definition Customer: Groups or individuals who have a business relationship with the organization--those who receive and use or are directly affected by the products and services of the organization. Customers include direct recipients of products and services, internal customers who produce services and products for final recipients, and other organizations and entities that interact with an organization to produce products and services.

59 October 19, Another Problems with Definitions Homonym problem –Same lexical word means different things

60 October 19, SUMO and WordNet

61 October 19, Concept Avoids the generalized definition trap Drastically speeds up discovery (have you ever tried to get a group of experts to agree on the meaning of a set of terms) Finesses the homonymy problem Term or Terms

62 October 19, Process Tease apart the facets of a given definition. People will generally agree with the facets. They wont necessarily agree on the same combination of facets mapping to the base word you started with. Ask: what could we call each bundle of facets that they care about? e.g., mother

63 October 19, Key Concept: The Distinctionary Is: a glossary Is distinct from other glossaries: structurally, each definition first specifies the more general type of thing the word is, and then provides a way to distinguish this thing from others that are similar.

64 October 19, Example Patient: A patient is a role between a human being and a healthcare delivery institution. It is different from other roles between a human and a healthcare delivery institution in that the human had been the recipient of the delivery of diagnostic or corrective health care services.

65 October 19, Taxonomies

66 October 19, Taxonomy A taxonomy is a system for classifying and organizing large amounts of information Seth Earley

67 October 19, DMOZ Home –Gardening –Personal Finance –Cooking Baking Casseroles Camping –Dutch Oven

68 October 19, Formal Taxonomy isa?

69 October 19, Subsumption v. Inheritance Dynamic v. Static

70 October 19, Ontology --Frame based

71 October 19, Ontology Definition A specification of a conceptualization Tom Gruber Taxonomy: Ontology :: Tree: Network

72 October 19,

73 October 19, Limits of Taxonomy Disjointedness

74 October 19, Concept: A Small Ontology GP (Genealogy Primitives) Person M/F Spouse Parent

75 October 19, Consider my family Database

76 October 19, What kinds of queries could I do? Any view qualified by the attributes –(show everyone born before 1/1/1990) Some join based queries –(show all of Daves children) But it gets much more complex after that

77 October 19, Committing to an Ontology Person Gender PersonSpouse

78 October 19, Concept: Committing & Sharing GP (Genealogy Primitives) GC (Genealogy Concepts) My Family Commits to Person M/F Spouse Parent Dave is male Dave is Addies parent Addie is female Naomi is Daves parent Naomi is Toms parent Father… Uncle… Cousin… Second Cousin, etc. … Key concept: queries/ inference can be executed using ontological definitions Im not even aware of

79 October 19, Good Resource Ontology Development 101: A Guide to creating your first ontology Natalya Noy and Deborah McGuinness ontology-tutorial-noy-mcguinness.pdf

80 October 19, Description Logics

81 October 19, Description Logics This is where the rigor comes in. Three things that take some getting used to: –Classes and Instances interchangeable –Allowing the system to do some of the design work for you –Open world logic Plus some very strange terminology and symbology

82 October 19, Description Logics ( DL ) Points of Departure As much as possible, minimize the number of concepts that have to be accepted axiomatically. Emphasize formal definitions for all the rest.

83 October 19, DL Definitions

84 October 19, Classes and Instances Database designers make an early design decision as to what is going to be metadata (classes, columns, etc.) and what is going to be instance data. For ontologists, this is a continually moving target. Additionally, properties (which could be equivalent to attributes or relationships) are free floating and can be attached to classes, but dont belong to them in the same way as with database models.

85 October 19, Allowing the System to Do some Design Declared Inferred

86 October 19, Open World In closed world (i.e., SQL), absence of information is assumed to be negation. If the query doesnt find it, it doesnt exist. In open world (DL), things are assumed to be possible until proven otherwise. In DL, classes are assumed to overlap unless they are explicitly declared to be disjoint. Domain and range are used for reasoning, not constraining.

87 October 19, Motherhood Sue is Johns biological mother Sarah is Johns biological mother Therefore? George Washingtons mother

88 October 19,

89 October 19, Other strange vocabulary DL TermEnglishDescriptionMeaning PartialNecessaryPrimitive, or defined classes If something is a member of this class then it is necessary to fulfill these conditions CompleteNecessary & Sufficient Derived or defined classes If something fulfills these conditions, then it is a member of this class TBoxTermsMetadataReasoning in the ontology ABoxAssertionsinstancesReasoning over the data

90 October 19, Summary

91 October 19, Semantic Arts, Inc.


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