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Topic Maps - Human-oriented semantics?

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A two-hour overview of the Topic Maps technology, standards, and applications.

A two-hour overview of the Topic Maps technology, standards, and applications.

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  • 1. Topic Maps – semantics for humans?
    WNRI Seminars on Semantic Technologies, 2010-12-15
    Lars Marius Garshol
    <larsga@bouvet.no>
    http://twitter.com/larsga
  • 2. Agenda
    What are semantic technologies?
    Introduction to Topic Maps
    Topic Maps and classification
    A short history of Topic Maps
    The standards
    Topic Maps and RDF
    Example applications
    Software
    Learn more
  • 3. What makes a technology semantic?
  • 4. Semantics?
    Semantics
    the study of meaning (orig. the meaning of words)
    Semantic technologies
    describe not just data, but also the meaning of data
    in traditional technology meaning is only in code and human interpretation
    John Searle, "The Chinese Room"
  • 5. Non-semantic data
    What is this?
    How many entities are represented here?
    What is entities and what is properties?
  • 6. The schema
    People often say that the schema defines the semantics
    But it's not really very semantic, is it?
    XML is not a semantic technology
  • 7. Topic Maps example
    Separates entities from properties
    Relations are clearly visible
    We know the names of all entities
    Can query for all 人 and get all instances
    The full meaning remains obscure
    Types

    subtype
    subtype
    男性
    女性
    出来事
    type-instance
    type-instance
    源氏
    夕顔
    参加
    参加
    夕顔との出会い
  • 8. Semantic technology
    Far richer description of concepts
    arbitrarily complex description of classes and properties
    Vocabularies can be reused across applications
    Data can be automatically merged
    Some of the meaning in the data can be modelled
  • 9. Semantic technologies
    Topic Maps
    ISO standard, much used in portals
    emphasis on "human" semantics
    RDF
    W3C standard, foundation of the "semantic web"
    heavy use of logic in the stack of standards
    Other alternatives
    many other technologies want to be seen as semantic; how many of them are is disputable
    only widely-accepted standards really matter
  • 10. What are Topic Maps?
    Uses for Topic Maps
    Introduction
  • 11. What is Topic Maps?
    A technology for knowledge integration
    describes concepts and their relations
    allows documents to be attached to the concepts
    concepts can be matched across different topic maps
    matching allows topic maps to be merged seamlessly
  • 12. What can Topic Maps be used for?
    Primary usage
    organizing information so you can find what you are looking for
    common example: portal or intranet
    less common: online publishing
    However, Topic Maps is really just a way to organize information
    can therefore be used for nearly anything
    Other uses
    e-learning
    real knowledge management
    decision support systems
    ...
  • 13. From documents to topics
    The TAO of Topic Maps
    How to make a topic map
  • 14. How to find the needle in this haystack?
  • 15. The Topic Maps approach
    (index)
    (content)
    topic map
    documents
    Create a conceptual map of the information being organized
    concepts and relations
    connections to documents (landscape)
    Like a book with an index
    or landscape and a map
  • 16. Creating a topic map
    Analyze the documents
    Select the key concepts (topics)
    Analyze the key concepts (topic types)
    Identify their relationships (associations)
    For each topic, connect relevant documents (occurrences)
    Voila!
  • 17. 1. Document analysis
    Key concepts
    What is it?
    Evaluation report from the MODE project
    MODE, (Evaluation)
    CV of Jane Doe
    Jane Doe, (CV)
    Budget for IT group
    IT group, (Budget)
  • 18. 2.-3. Topics, with types
    Person
    Department
    Project
    Jane Doe
    IT group
    MODE
  • 19. 4. Adding associations
    employed in
    worked on
    part of
    worked on
    Consumer
    products
    part of
    employed in
    Documentation
    Roger Roe
    Jane Doe
    IT group
    MODE
  • 20. 5. Adding occurrences
    Jane Doe
    CV
    budget
    evaluation
    worked on
    employed in
    IT group
    MODE
  • 21. 6. The TAO of Topic Maps
    worked on
    MODE
    Jane Doe
    Topics
    represent things of interest
    Associations
    represent relations between topics
    Occurrences
    connect topics to information resources with relevant information
  • 22. How to find information?
    Metadata as solution
    Metadata as problem
    Metadata
  • 23. Metadata
    The obvious solution to the problem is to describe the documents
    that is, to attach metadata to the documents
    metadata in this context is “information about a document”
    So how does this help?
    it’s useful for managing the content
    it provides a better starting point for search
    it means better search results can be displayed
    it helps the user determine whether or not a
    search hit is interesting
    But is it what the user is looking for?
    the user starts out wanting to know more about
    a subject
    traditional metadata, however, focuses on the
    document
    if aboutness is provided at all, it gets squeezed into a single field
    Title: Recurrent Herpes Simplex Sciatica and its Treatment with Amantadine Hydro...
    Author: D.A. Fisher
    Date: 1982-05
    Format: text/html
    Keywords: sciatic neuralgia, aman...
  • 24. What’s wrong with keywords?
    The main problem is that their use is uncontrolled
    This leads to problems like
    authors misspelling keywords,
    authors using different keywords for the same thing, and
    authors using keywords that make no sense
    A secondary problem is that short of guessing, there is no way for the user to find out what keywords have been used
    The main benefit is that it’s cheap and simple
  • 25. Taking control over the vocabulary
    The obvious solution is to create a list of legal keywords
    this is what’s known as a controlled vocabulary
    in a controlled vocabulary keywords are called terms
    this requires somewhere to keep the list, and a process for adding new terms
    Benefits
    gets rid of the misspelling problem
    gets rid of the problem with authors using different terms for the same thing
    Disadvantages
    introduces some overhead
    a flat list is difficult to manage
    users can still search using the wrong terms
    users will still have difficulty finding terms if the list is long
    authors will have the same problem
  • 26. Organizing the terms
    The solution is clearly to organize the terms somehow
    In one sense we’re now back to the problem we had originally with documents
    the solution is also the same: we need to describe the terms somehow
    the difficulty is: what can you say about terms?
    The good news is that there are many traditional and well-known ways to approach this
  • 27. Two worlds
    amantadine hydrochloride
    sciatic neuralgia
    Title: Recurrent Herpes Simplex Sciatica and its Treatment with Amantadine Hydro...
    Author: D.A. Fisher
    Date: 1982-05
    Format: text/html
    Keywords: sciatic neuralgia, amantadine hydrochloride
    ?
    ?
    ?
    Metadata
    Subject-based classification
  • 28. Describing the terms
    Tags
    Taxonomies
    Thesauri
    Classification approaches
  • 29. Subject-based classification
    There are many possible organizing principles for documents
    By
    author
    time period
    genre
    etc
    Subject-based classification classifies documents by their subject
    the subject is what the document is about
    that is, the subject matter of the document
    Subject-based classification does not have any particular structure
    it's just an approach, and there are many different ways to do it
  • 30. Folksonomies and tags
    Tags have recently become popular on the web
    used by web 2.0 sites like Flickr, Technorati, del.icio.us, ...
    also much used in blogs to categorize the posts
    Tags are effectively a controlled vocabulary of keywords
    except the control is often extremely lax
    The same benefits and problems
    del.icio.us for example has tags like xtm, topic_maps, topicmaps, topic_map, and topicmap
  • 31. Taxonomies
    BT
    Organizes the keywords into a tree
    the most general at the top, more specific as you go down
    common structure used by Yahoo!, LOS, Dewey classification...
    Requires relationships between terms
    the relationships state that one term is more specific than another
    http://www.dmoz.org
  • 32. A taxonomy example
    Nervous system disease
    Autonomous nervous system disease
    Peripheral nervous system disease
    Cauda equina syndrome
    Diabethic neuropathy
    Sciatic neuralgia
  • 33. Thesauri
    USE
    BT
    BT
    RT
    SN
    Thesaurus
    Taxonomy
    Folksonomy
    An extension of taxonomies
    come from the library world; much used in publishing
    the main extension is that thesauri add more relationships
    What thesauri contain:
    BT the same relationship as in taxonomies
    RT related term, which goes across the hierarchy
    USE refers to a term that should be used instead of the current one
    SN scope note, a definition of the term
  • 34. A thesaurus example
    Nervous system disease
    Autonomous nervous system disease
    USE
    Peripheral neuropathy
    Peripheral nervous system disease
    Cauda equina syndrome
    Diabetic complications
    Diabetic neuropathy
    Sciatic neuralgia
    RT
  • 35. Faceted classification
    The term “faceted classification” has been used to mean many different things
    originally invented by S. R. Ranganathan in the 1930s
    Faceted classification
    defines a number of facets or dimensions
    defines a set of terms within each facet
    sometimes these terms are arranged in a taxonomy
    documents are classified against each facet separately
  • 36. Colon Classification
    Ranganathan's original faceted classification system
    Consisted of five facets:
    Personality The main subject of the document
    Matter The material or substance the document deals with
    Energy The processes or activities described
    Space The location described
    Time The time period described
    This has sometimes been referred to as “PMEST”
  • 37. An example of use
    The Norwegian wine monopoly describes its products using these facets:
    type: red wine, white wine, beer, ...
    country of origin: France, Norway, ...
    price
    matches food: pasta, cheese, fish, beef, ...
    bottle size
  • 38.
  • 39. Ontology in Topic Maps
    A Topic Maps model of some specific aspect of the world
    Worked on
    MODE
    Project
    Person
    CV
    Jane Doe
    ontology
    instances
    worked on
    CV
  • 40. Taxonomies and thesauri revisited
    From the Topic Maps perspective taxonomies are an ontology
    terms become topics (of type “term” or “concept”)
    relations become associations (of various types)
    scope notes become occurrences
    However, in Topic Maps it’s possible to be more precise
    Nervous system disease
    Autonomous nervous system disease
    USE
    Peripheral nervous system disease
    Peripheral neuropathy
    Body part
    Cauda equina syndrome
    Disease
    Diabetic neuropathy
    Drug
    Amantadine hydrochloride
    Sciatic neuralgia
    Peripheral neuropathy
    Part of
    Attacks
    Treats
  • 41. Expressivity progression
    Topic Maps
    Taxonomies, thesauri
    Flat list, tags
    Expressivity
    No model
    Closed model
    Open model
  • 42. Metadata revisited
    Metadata can also be represented in Topic Maps
    create topics for the documents
    map fields to names, occurrences, or associations
    Big pharma
    Amantadine hydrochlorine
    Sciatic neuralgia
    attacks
    about
    author of
    Peripheral nervous system
    treated by
    D.A. Fisher
    This part is untrue!
    produced by
    works for
    Recurrent Herpes Simplex and its...
    Date: 1982-05
    Format: text/html
  • 43. Benefits of Topic Maps
    Richer, more expressive model
    multiple paths to the information you seek
    typed associations provide “signposts” along the path
    Improved support for search
    search for concepts, rather than just documents
    associations can be used for filtering
    Merges classification and metadata into a single model
    greater expressivity (again)
    simpler architecture: just one system to relate to
    Maps directly to web portals
    easy to build and maintain web portal based on the topic map
  • 44. Conclusion
    Traditional findability solutions
    metadata: describes documents
    classifications: gather and loosely organize keywords/terms
    Traditional solutions focus on documents
    Users focus on subjects
    Topic Maps
    open model for describing anything
    focus on subjects
    easily supports both metadata and existing classifications
  • 45. What it actually looks like
    Deeper into Topic Maps
  • 46. Advanced concepts
    Association roles
    Reification
    Scope
    Identity
  • 47. Associations have no direction
    Puccini
    Angeloni
    pupil of
  • 48. Instead associations have roles
    Puccini
    Angeloni
    pupil of
    pupil
    teacher
  • 49. Richer relationships
    father
    child
    Lars Marius
    Bjørg
    Knut
    parenthood
    mother
  • 50. Roles, role players and role types
    person
    pupil
    teacher
    teacher-of
    person
    topic type
    role type
    role type
    association type
    topic type
    association
    role player
    role player
    role
    role
    puccini
    angeloni
    N.B. role == association role and role type == association role type
  • 51. Symmetric relationships
    country
    neighbor
    neighbor
    borders-with
    country
    topic type
    role type
    role type
    association type
    topic type
    association
    role player
    role player
    role
    role
    norway
    sweden
  • 52. Reification
    From latin “re” = “thing”
    i.e. “thingification”
    In Topic Maps, for “thing” read “topic”
    So reification is about turning something into a topic
    Specifically it is about turning topic map constructs that are not already topics (i.e., names, occurrences, associations, association roles, and topic maps) into topic
    Useful for annotation of Topic Maps constructs
  • 53. Reification example
    Ontopia
    start date
    2000
    2007
    LMG's employment
    end date
    employed by
    Lars Marius Garshol
    Obviously, this is no longer the case. But how can we express that?
  • 54. The semantics of reification
    Many possible interpretations of what the reifying topic represents:
    the same thing as the association
    the association as Topic Maps construct
    the assertion of this particular association
    Topic Maps reification is case (a)
    RDF reification is not formally defined, but is case (c)
  • 55. Scope
    Every statement in a topic map has a scope
    that is, a set of topics representing the context in which the statement is valid
    the empty set is known as "the unconstrained scope"
    Abugida
    Alphasyllabary
    Bright
    Daniels
    Tibetan script
  • 56. Applications of scope
    Multilinguality
    scope names and occurrences with language topics
    Authority
    scope statements with the authority that supports them
    Provenance
    scope statements with their source
    Time
    scope statements with the era in which they were true
  • 57. Multiple topics in scope
    The context is the intersection of the topics
    a statement scoped with "Thursdays" and "LMG" is true on Thursdays according to LMG
    Implication: adding topics to the scope narrows the context of validity
    given
    a statement s in scope a, and
    s' in scope a, b
    we can see that s' is actually redundant
  • 58. Topics and subjects
    A topic is a representation of a subject
    topic: Topic Maps construct representing subject
    subject: real-world thing
    subject
    topic
    Patrick Durusau
    "subject: anything whatsoever, regardless of whether it exists or has any other specific characteristics, about which anything whatsoever may be asserted by any means whatsoever" --ISO/IEC 13250-2:2006
  • 59. Subject identification
    Topics can have globally unique identifiers attached to them
    these identifiers really identify the subject of the topic, and not the topic itself
    the identifiers are URIs
    However, these are of two different kinds...
  • 60. Subject locators
    A subject locator is a URI that points to the information resource which is the subject
    Patrick Durusau
    depicted-in
    Photo of Patrick
    taken-at
    Leipzig
    http://larsga.geirove.org/photoserv.fcgi?t121182
    subject locator
    http://larsga.geirove.org/photoserv.fcgi?t121182
    same as URI of photo
  • 61. Subject identifiers
    A subject identifier is a URI which refers to an information resource describing the subject
    Patrick Durusau
    depicted-in
    http://psi.ontopedia.net/Patrick_Durusau
    Photo of Patrick
  • 62. Merging
    In Topic Maps, two topics must be merged if they have the same
    subject identifier,
    subject locator, or
    reified construct
    The rationale is that if this is the case they must represent the same subject
  • 63. Example
    Patrick Durusau
    depicted-in
    Photo of Patrick
    http://psi.ontopedia.net/Patrick_Durusau
    taken-at
    Leipzig
    editor-of
    ISO/IEC 13250-5
    Patrick Durusau
    editor-of
    http://psi.ontopedia.net/Patrick_Durusau
    ODF
  • 64. Example
    editor-of
    ISO/IEC 13250-5
    Patrick Durusau
    depicted-in
    editor-of
    Photo of Patrick
    http://psi.ontopedia.net/Patrick_Durusau
    taken-at
    ODF
    Leipzig
  • 65. On merging
    Merging is not a special operation
    happens every time Topic Maps data is loaded
    Allows exchange of fragments
    identifiers ensure that fragments are reassembled simply by being loaded
    Allows reuse of data
    define identifiers for vocabulary (pieces of ontology)
    or for individual entities
  • 66. Examples of use
    Subclassing
    SIs for this are defined in the standard
    can be interchanged between tools
    Hierarchy definition
    SIs for this were defined years ago; widely used today
    Schema language
    SIs defined in TMCL (about which more later)
    Countries and languages
    SIs defined by OASIS
    ...
  • 67. LOS
    A common classification for public information in Norway
    published by Norge.no (Norway.no)
    http://norge.no/los/
    Consists of
    a taxonomy of subjects,
    a taxonomy of geographic locations, and
    a set of classified resources
    Defines PSIs for the subjects and locations
    Used by
    Bergen Kommune
  • 68. Grep
    The Norwegian National Curriculum
    basically the official definition of what children should learn in school
    published as a topic map by the Ministry of Education
    uses PSIs for all elements
    Currently starting to be used
    NRK project used it
    others are connecting to it, too
    an aggregator service is being built
  • 69. Linked Open Data?
    This is linked open data
    using URIs to automatically connect statements from disparate sources
    Represented in different ways
    some use RDF
    some use Topic Maps
    and some, probably, use other things
    Called "Global Knowledge Federation" in the TM community
    the concept remains the same
    interchange across technologies is possible
  • 70. HyTime
    The Davenport project
    ISO
    A bit of history
  • 71. HyTime
    An ISO standard for hypertext first published as ISO/IEC 10744:1992
    very ambitious and complex
    based on SGML (precursor of XML)
    many kinds of hyperlinks
    including links with any number of anchors, where each anchor is associated with a role type specifying its meaning...
    contains a metamodel for representing content to allow detailed addressing into any form of resource
    ...
  • 72. Small beginnings
    1991
    The Davenport Group: project to merge back-of-book indexes to UNIX documentation from different publishers
    First attempt known as SOFABED (failed)
    1993
    CApH was set up, to use HyTime to solve the problem
    turned SOFABED into Topic Navigation Maps
    1996
    picked up by ISO committee responsible for SGML
  • 73. ISO and TopicMaps.Org
    1998
    Topic Maps standard submitted for final ballot
    an SGML architectural form based on HyTime
    SGML syntax today known as HyTM
    W3C publishes XML
    2000
    ISO publishes ISO/IEC 13250:2000 (still in SGML)
    TopicMaps.Org created to produce an XML version of Topic Maps
    2001
    XTM 1.0 published by TopicMaps.Org in March
  • 74. ISO
    2001
    work begins on data models for Topic Maps
    an infoset-based model, close to XTM 1.0
    a graph-based model, far more abstract
    lots of politics, holding up all other work
    first commercial engine released (Ontopia)
    2002
    ISO publishes ISO/IEC 13250:2002 (with XTM 1.0)
    the first Norwegian portals start appearing
    2006
    ISO publishes ISO/IEC 13250-2:2006 – Topic Maps – Data Model
  • 75. A little ISO history
    Topic Maps Data Model
    The Topic Maps Standards
  • 76. The new ISO 13250
    A multi-part standard, consisting of
    Part 1: Overview of Basic Concepts
    Part 2: Data Model
    Part 3: XTM syntax
    Part 4: Canonical XTM
    Part 5: Reference Model
    Part 6: Compact Syntax
    Part 7: Graphical Notation
  • 77. Roadmap to the TM standards
    ISO 18048
    QUERY LANGUAGETMQL
    ISO 13250
    XTM SYNTAX
    CXTM SPEC
    CTM SYNTAX
    GTM NOTATION
    ISO 19756
    CONSTRAINT LANGUAGETMCL
    DATA MODELTMDM
    REFERENCE MODELTMRM
  • 78. The Topic Maps Data Model (TMDM)
    Created to define meaning and structure of topic maps
    Syntaxes map to this structure, as do TMQL and TMCL
    Defines the meaning of topic map concepts using prose
    Defines “subject”, “topic”, “scope”, “association”, ...
    Defines their structure using the information set model
    Just like XML Infoset
    Describes the kinds of things that exist in topic maps, and their properties
    Adds constraints on the model
    Rules for allowed values
    Also defines when merging happens, and how
  • 79. How TMDM works
    One information item type defined for each topic map construct
    Complete list shown below
    One set of properties defined for each construct
    Example below: all topic map objects have item identifiers
  • 80. Association
    Associations have the following properties:
    [type]: topic defining the association type
    [scope]: set of topics making up the scope of the association
    [roles]: set of association role items
    [reifier]: topic reifying the association
    [source locators]: URIs pointing back to element(s) the association came from
    [parent]: the topic map
    Merge if equal values for [type], [scope] & [roles]
  • 81. Merging rules in TMDM
    One merging rule defined for each information type
    Equality rule says which properties to compare (as for association)
    Merging rule says how to merge two equal information items
    For topics, the equality rule is that two topics are equal if
    same value in [subject identifiers] property of both, or
    same value in [subject locators] property of both, or
    same value in [source locators] property of both, or
    some extra conditions
    Merging topics is done by
    creating a new topic item, whose properties contain the union of the old values,
    then replacing all occurrences of the old items throughout the model with the new one
  • 82. XTM 2.0 syntax
    <topicMap version="2.0" xmlns="http://www.topicmaps.org/xtm/">
    <topic id="xtm">
    <subjectIdentifier href="http://psi.example.org/xtm/2.0"/>
    <instanceOf>
    <topicRef href="#syntax"/>
    </instanceOf>
    <name>
    <value>XTM 2.0</value>
    </name>
    <occurrence>
    <type>
    <topicRef href="#status"/>
    </type>
    <resourceData>International Standard</resourceData>
    </occurrence>
    </topic>
    </topicMap>
  • 83. CTM syntax
    http://psi.example.org/xtm/2.0 isa syntax;
    - "XTM 2.0";
    status: "International Standard".
  • 84. TMCL example
    op:Image isa tmcl:topic-type;
    is-abstract();
    has-name(tmdm:topic-name, 1, 1);
    has-occurrence(ph:time-taken, 1, 1);
    plays-role(op:Image, ph:taken-at, 1, 1);
    plays-role(op:Image, ph:taken-during, 0, 1);
    plays-role(ph:depiction, ph:depicted-in, 0, *);
    # ...
  • 85. Topic Maps and RDF
  • 86. Things
    A thing in the real world
    S
    A symbol in the computer domain
    The heart of RDF and Topic Maps is the same:
    symbols representing real-world things
    Both RDF and Topic Maps consist of statements about these things
  • 87. Technical comparison
    Topic Maps and RDF
    are graph-based data models,
    have well-defined identity tests and merging operators,
    have XML-based interchange syntaxes (as well as human-friendly ones),
    are standards, and
    have standardized schema and query languages
    Differences
    RDF is lower-level than Topic Maps,
    Topic Maps support reification, complex context, and n-ary relationships, and
    Topic Maps distinguish different kinds of URI references
  • 88. Topic Maps vs RDF
    OWL
    TMQL
    TMCL
    SPARQL
    RDFS
    Topic Maps
    RDF
    XTM
    CTM
    RDF/XML
    n3
  • 89. Timeline
    MCF-XML
    RDF Schema
    PICS-NG
    MCF
    RDF WD
    OWL
    RDF Rec
    '91
    '92
    '93
    '94
    '95
    '96
    '97
    '98
    '99
    '00
    '01
    '02
    '03
    '04
    ISO work starts
    XTM to ISO
    Standard finished
    ISO 13250:2003
    SOFABED model
    ISO 13250:2000
    XTM 1.0
    Davenport Group
    TopicMaps.Org
    Topic navigation maps
  • 90. Assertions
    RDF has one kind of assertion: the statement
    subject, predicate, object
    Topic maps have three kinds
    (1) Names
    (2) Occurrences
    (3) Associations
    “...”
    “...”
    http://www...
  • 91. Handling of identity
    Topic Maps
    subject locator
    subject identifier
    item identifier
    RDF
    uri
    blank node
    The distinction between a URI referring to a description
    of the subject, and a URI referring to the subject cannot
    be expressed in RDF.
  • 92. TMCL vs RDFS/OWL
    TMCL
    schema language
    validation semantics only
    very little reasoning or logic
    designed to support validation and introspection
    RDFS/OWL
    ontology description languages
    reasoning semantics only
    strong basis in logic
    OWL is essentially Description Logic
  • 93. Semantic Portals
    eLearning
    Business Process Modelling
    Product Configuration
    Information Integration
    Metadata Management
    Business Rules Management
    IT Asset Management
    Asset Management (Manufacturing)
    ...
    Applications of Topic Maps
  • 94. forskning.no
    Norwegian government portal to popular science and research information
    basically an online popular science journal
    owned by the Norwegian Research Council
    Purpose:
    To present science and research
    information to young adults
    Intended to raise interest and
    recruitment
  • 95. Content of forskning.no
    The main content is articles about science and research subjects
    There is also a classification system used as a navigational structure
    The site is entirely topic map-driven
    Navigation structure is a topic map
    Articles are represented as topics
    Even images are topics...
  • 96. Medicine
    Science
    Odontology
    Human body
    Volcanoes
    Clinical Med.
    Hormones
    The Brain
    Neurology
    Oncology
    The Dual Classification
  • 97. The subject
    Subjects
    Fields
    People
    Articles
    A Subject
  • 98. Article
    Subjects
    Fields
    Next article
    People
    An Article
  • 99. Person
    Title
    Home page
    Mentioned in
    Employer
    A Person
  • 100. The Project
    Wide ontology; research covers everything
    Ontology was created by reusing an existing thesaurus, automatically converted
    A series of 4-5 workshops established the basic principles
    Finally, the publishing application was built by Bouvet
    software used is ZTM (Python-based, open source)
  • 101. Maintenance
    Maintained by central editorial staff in Oslo
    Articles written by distributed network of authors
    Authors write and submit articles online
    Articles enter workflow and are added by editors
    Editors also add connections to topic map
  • 102. forskning.no admin interface
  • 103. forskning.no admin interface, 2
  • 104. forskning.no admin interface, 3
  • 105. City of Bergen
    Second biggest city in Norway
    250,000 inhabitants and 20,000 employees
    spends roughly 3 million USD annually on the portal project
    goal: to make all city services available through the portal
    Strong technology platform
    Oracle Portal + Oracle RDBMS
    Escenic as CMS
    Ontopia as Topic Maps engine
    DB2TM for data integration
  • 106. Bergen: who does what?
    Most of the site is produced by Ontopia
    Some parts by Escenic
    Some are independent
    And some are service-specific portlets
    Static
    Escenic
  • 107. Bergen architecture
    Service Catalog
    Oracle Portal
    Fellesdata
    Ontopia
    Dexter
    DB2TM
    TMSync
    Agresso
    Escenic
    Ontopoly
    LOS
    Editors
  • 108. NRK/Skole
    Norwegian National Broadcasting (NRK)
    media resources from the archives
    published for use in schools
    integrated with the National Curriculum
    In production
    opened late 2008
    Technologies
    Ontopia
    DB2TM conversion
    MySQL database
    Tomcat application server
  • 109. Curriculum-based browsing (1)
    Curriculum
    Social studies
    High school
  • 110. Curriculum-based browsing (2)
    Gender roles
  • 111. Curriculum-based browsing (3)
  • 112. One video (prime minister’s husband)
    Metadata
    Subject
    Person
    Related
    clips
    Description
  • 113. GREP
    Norwegian national curriculum
    published as a topic map
    has global IDs on all topics
    NRK/Skole clips attached to knowledge goals
    global IDs are in the topic map
    Therefore...
    Grade
    Subject
    Section
    Goal
    GREP
    Clip
    NRK/Skole
  • 114. ndla.no
    Portal organizing learning resources into the curriculum
    to be integrated with NRK/Skole
  • 115. Hafslund
    ERP
    Billing
    Archive
    ...
    SDshare
    SDshare
    SDshare
    SDshare
    Topic Map
    auto-tagging
  • 116. SDshare
    ERP
    SDshare
    Server
    Client
    Fragments
  • 117. Using Ontopia
    DB2TM converts to Topic Maps
    a simple XML mapping file
    this is enough to provide full sync
    Generic SDshare implementation
    listens for change events
    produces corresponding feeds
    ERP
    DB2TM
    Ontopia
    SDshare
    Server
  • 118. Hafslund – points to note
    Extremely loose coupling
    ontology can be freely changed
    Very simple integration
    in many cases just an XML configuration file
    Very flexible architecture
    adding new sources is trivial
    Has more uses than just archiving
    once the data is collected...
  • 119. E-learning
    Topic maps are associative knowledge structures
    They reflect how people acquire and retain knowledge
    BrainBank is used by students to describe what they have learned
    Initial users are 11-13 year olds who haveno idea what a topic map is…
    They capture the key concepts, name them, describe them, and associate them with others
    This helps them
    Capture the essence,
    Describe what they have learned,
    Keep track of their knowledge, and
    Lets the teacher help them
    BrainBank was built using Ontopia
    An application of the Web Editor Framework
    Demonstrates user-friendliness of TM editing
  • 120. Business process modelling
    A multinational petrochemical company uses Ontopia for managing business process models
    The flexibility of the Topic Maps model allows arbitrary relationships to be captured easily
    Processes are modelled in terms of
    The steps involved, their preconditions, their successors, etc
    Processes can be related through
    Composition (one process is part of another),
    Sequencing (one process is followed by another),
    Specialization (one process is a special caseof a more general process)
  • 121. Product configuration
    A Scandinavian telecom company uses Ontopia to manage product configuration
    Products belong to families
    Features belong to either products or product families
    Features are grouped in feature sets
    There are dependencies between features
    etc.
    The system models dependencies in
    a topic map
    Product configuration engineers use this to configure products using a user-friendly interface
    After each change, interface gives feedback on whether selection was valid
    Features
    Product
    families
    Versioning
    System
    data
    Products
  • 122. Product configuration (2)
    Feature 1
    The features are arranged in a tree
    trees vary in size (700-2500 features)
    two kinds of parent-child relationships (mandatory or optional)
    Configuration rules run across
    three different kinds of rules
    expressed as associations
    In addition: variables
    these have different values for different products
    Feature 2
    conflicts-with
    requires
    Feature 3
    Feature 4
    Feature 5
  • 123. Product configuration (3)
    The network of dependencies is already quite complex
    Now throw versioning into the mix!
    Managing all this data is not easy
    The system is driven by inference rules
    These work on the topic map
    Easily capture complex logic
    Also integrates with product documentation
    Very complex topic map
    at the last count ~20,000 topics and ~1,000,000 associations
    running complex queries on this really exercises the query engine
  • 124. Business rules management (1)
    The US Department of Energy has used Ontopia to manage guidance rules for security classification
    Information about the production of nuclear weapons is subject to thousands of rules
    Rules are published in 100s of documents
    Most documents are derived from more general documents
  • 125. Business rules management (2)
    Guidance topics form a complex web of relationships that is captured in a topic map
    Concepts are connected to if-then-else rules
    This constitutes a knowledge base (KB)
    KB used with an inference engine to automatically
    classify information (documents, emails, ...), and
    redact information (PDF, email, ...)
    Benefits:
    Model expressive enough to capture thecomplexity of the rules
    Status as ISO standard ensures stability and longevity
    Master
    topic
    Parent
    topic
    Child
    topic
    Guidance
    topic
    Derived
    topic
    Responsible
    person
    Concept
    Workflow
    state
  • 126. IT asset management
    The University of Oslo is using the OKS to manage IT assets
    Servers, clusters, databases, etc are described in a TM
    This is used to answer questions like
    Service X is down, who do I call?
    If I take Y down, what else goes?
    If operating system Z is upgraded, what apps are affected?
    System driven by composite topic map
    Partly autogenerated
    Partly handcoded
    Two applications provide accessto the knowledge base
    Whitney: online
    Houson: offline (for use in emergencies)
    Houdini
    Whitney
    Syntax control
    OKS schema validation
    Versioning with CVS
    Navigator framework
    UIOTM FW
    OKS API
    OKS Engine
    RDBMS backend
    XTM
    usit.ltm(handcoded)
    oracle.ltm(generated)
    CVS
  • 127. Asset management: Manufacturing
    The Y-12 plant at DoE is using the OKS to map its plant
    The purpose is to get an overview of
    equipment,
    processes,
    materials required,
    parts already built,
    etc.
  • 128.
  • 129. Topic Maps software
  • 130. Two main kinds
    Big application suites
    complete frameworks for building solutions
    engines at the core with end-user tools on top
    Smaller, open source tools
    many are just engines
    some are more specific tools for a single purpose
  • 131. Ontopia
    Open source Java-based suite of tools
    engine + query engine
    generic ontology designer + instance editor
    conversion tools (RDBMS, RDF, XML, ...)
    presentation frameworks (JSP, portlets, ...)
    CMS integrations
    automatic classification
    graphical visualization
    web service interfaces
    browser
    ...
  • 132. Web3
    Commercial .NET-based suite
    engine + query engine
    Sharepoint integration
    built-in security model
    web service interfaces
    presentation framework
  • 133. Topincs
    Web-based knowledge management tool
    wiki-like, but TMCL-based
    collaborative
    complex presentation features
    version 5.1 allows embedded programming in the TM
  • 134. Wandora
    Open source Java-based application suite
    core engine
    presentation framework
    extensive set of input converters
    many export formats
    ontology designer + instance editor
  • 135. topicWorks
    Commercial Java-based application suite
    core engine
    sophisticated data navigator
    Excel plugin
    ready-made ontologies
  • 136. ZTM
    Open source Topic Maps-based CMS
    written in Python, on top of Zope
    used for a large number of portals (e.g vestforsk.no)
    very advanced CMS features
    enables very rapid development
  • 137. Atom2
    Commercial suite
    high-performance engine + query engine
    ontology designer + instance editor
    presentation framework
    CMS-like functionality
  • 138. TopicMapsLab
    SesameTM
    TMAPI implementation on top of Sesame triple store
    tmql4j
    TMQL query engine on top of TMAPI
    Aranuka
    object mapping library
    Onotoa
    graphical TMCL modelling tool
    Maiana
    social Topic Maps browser
    MajorTom
    virtual merging Topic Maps engine
    ...
  • 139. Various engines
    TM++ C++
    tmjs JavaScript
    QuaaxTM PHP
    Mappa Python
    RTM Ruby
    SharpTM C#
    TM2JDBC Java
    Isidorus Common Lisp
    tinyTiM Java
    ...
  • 140. Sources
    Learn more
  • 141. Papers
    Topic Maps in Encyclopedia of Library Science
    http://www.ontopedia.net/pepper/papers/ELIS-TopicMaps.pdf
    The TAO of Topic Maps
    http://www.ontopia.net/topicmaps/materials/tao.html
    Metadata? Thesauri? Taxonomies? Topic Maps!
    http://www.ontopia.net/topicmaps/materials/tm-vs-thesauri.html
  • 142. Conferences
    Software 2011 – Topic Maps track
    http://www.dataforeningen.no/forside.168724..html
    TMRA conferences
    http://tmra.de
  • 143. Other
    Topic Maps Snippets
    http://topicmaps.bouvet.no/blog/
    Planet Topic Maps
    http://planet.topicmaps.org/
    TopicMaps.org
    http://www.topicmaps.org
    TopicMaps Lab
    http://www.topicmapslab.de
    Index of Topic Maps software
    http://www.garshol.priv.no/tmtools/