Towards a Digital Library Theory: A Formal Digital Library Ontology

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Towards a Digital Library Theory A Formal
Digital Library Ontology

• Marcos André Gonçalves, Layne T. Watson, and
  Edward A. Fox
• Virginia Tech, Blacksburg, VA 24061 USA,
  fox_at_vt.edu
• (For ACM SIGIR Mathematical/Formal Methods in
  Information Retrieval, MF/IR 2004, Sheffield, UK,
  Aug. 29, 2004)

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Outline

• Background The 5S Model
• Motivation for this Work
• Digital Library Formal Ontology
• Taxonomy of DL Services
• Applications of the Theory
• Conclusions and Future Work

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Background The 5S Model

• Why 5S?
• DLs are not benefiting from formal theories as
  have other CS fields DB, IR, PL, etc.
• DL construction difficult, ad-hoc, lacking
  support for tailoring/customization
• Conceptual modeling, requirements analysis, and
  methodological approaches are rarely supported in
  DL development.
• Lack of specific DL models, formalisms,
  languages

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Background The 5S Model

• Informally, DLs can be defined as complex
  information systems that
• help satisfy info needs of users (societies)
• provide info services (scenarios)
• organize info in usable ways (structures)
• (re)present info in usable ways (spaces)
• communicate info with users (streams)

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Background The 5S Model
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Background 5S and DL formal definitions and
compositions (April 2004 TOIS)
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Background The 5S Model

• Summary of TOIS 2004 Formal Definitions
• A digital library is a 10-tuple (Streams,
  Structs, Sps, Scs, St2, Coll, Cat, Rep, Serv,
  Soc) in which
• Streams is a set of streams, which are sequences
  of arbitrary types (e.g., bits, characters,
  pixels, frames)
• Structs is a set of structures, which are tuples,
  (G, ?), where G (V, E) is a directed graph and
  ? (V ? E) ? L is a labeling function
• Sps is a set of spaces each of which can be a
  measurable, measure, probability, topological,
  metric, or vector space.

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Background The 5S Model

• Scs sc1, sc2, , scd is a set of scenarios
  where each sck lte1k(p1k), e2k(p2k), ,
  ed_kk(pd_kk)gt is a sequence of events that also
  can have a number of parameters pik. Events
  represent changes in computational states
  parameters represent specific locations in a
  state and respective values.
• St2 is a set of functions ? V? Streams? (? ?
  ?) that associate nodes of a structure with a
  pair of natural numbers (a, b) corresponding to a
  portion (span/segment) of a stream.
• Coll C1, C2, , Cf is a set of DL collections
  where each DL collection Ck do1k, do2k, ,
  dof_kk is a set of digital objects. Each digital
  object dok (hk, Stm1k, Stt2k, ?k) is a tuple
  where Stm1k ? Streams, Stt2k ? Structs, ?k ?
  St2, and hk is a handle which represents a
  unique identifier for the object.

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Background The 5S Model

• Cat DMC_1, DMC_2, , DMC_f is a set of
  metadata catalogs for Coll where each metadata
  catalog DMC_k (h, msshk), and msshk mshk1,
  mshk2, , mshkn_hk is a set of descriptive
  metadata specifications. Each descriptive
  metadata specification mshki is a structure with
  atomic values (e.g., numbers, dates, strings)
  associated with nodes.
• A repository Rep (Ci, DMC_i) (i1 to f) is a
  set of pairs (collection, metadata catalog) it
  is assumed there exist operations to manipulate
  the family of pairs (e.g., get, store, delete).
• Serv Se1, Se2, , Ses is a set of services
  where each service Sek sc1k, .., scs_kk is
  described by a set of related scenarios.
• Soc (C, R) where C is a set of communities and
  R is a set of relationships among communities.
  SM sm1, sm2, , smj, and Ac ac1, ac2, ,
  acr are two such communities where the former
  is a set of service managers responsible for
  running DL services and the latter is a set of
  actors that use those services.
• Being basically an electronic entity, a member
  smk of SM distinguishes itself from actors by
  defining or implementing a set of operations
  op1k, op2k, , opnk ? smk

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Background
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Motivation

• Previous definitions emphasize syntactic aspects,
  i.e., how digital library concepts are composed
  or built from previously defined concepts.
• Complete a formal DL theory by
• Making explicit the implicit relationships that
  exist among the DL formal concepts defined in
  Gonc04
• Providing set of axiomatic rules that precisely
  define and constrain the semantics of the
  relationships
• Categorizing and classifying DL services on the
  basis of the ontology
• Research questions
• How should DL services be built from the other DL
  components
• Which are the fundamental and elementary DL
  services ?
• How can services be built/composed from other DL
  services?
• We will explore semantic relations and rules of
  the DL domain by using ontologies.

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Digital Library Formal Ontology

• An ontology is a tuple ? (Ontol_Concepts,
  Ontol_Rels) where
• Ontol_Concepts is a family of ontological
  concepts,
• Ontol_Rels is a family of relations.
• Relations in Ontol_Rels are operationally
  realized by one or more rules (e.g., first-order
  logic axioms) which intentionally specify or
  constrain which elements of a concept can
  participate in a relation.
• Ontol_Rules is a family of rules of a particular
  ontology.

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Digital Library Formal Ontology

• Relationships
• Intra-Model
• Video contains Audio (MM)
• Metadata Catalog describes Collection (LIS)
• Probabilistic Space is_a Measure Space
• Service extends Service (reuse)
• Service Manager inherits_from Service Manager
  (OO)
• Inter-Model
• Event executes Operation
• Actor participates_in Scenario
• Service Manager runs Service
• Service employs/produces Streams ? Structures ?
  Spaces

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Digital Library Formal Ontology

• Concepts Se, Sc, e Key Se service Sc
  scenario e event.
• Relations
• contains ? Sc ? e
• Symbolic Rule. ? x, y (x contains y ? Sc(x) ?
  e(y) ? ?j (j ?x.Dom ? y x(j)) )
• precedes ? e ? e ? Sc happens_before ? e ? e ?
  Sc
• Symbolic Rule 1. ? x, y, z (x precedesz y ? e(x)
  ? e(y) ? Sc(z) ? ? i, j (z contains x ? z
  contains y ? x z(i) ? yz(j) ? i 1 j))
• Symbolic Rule 2. ? x, y, z (x happens_beforez y ?
  e(x) ? e(y) ? Sc(z) ? ? i, j (z contains x ? z
  contains y ? x z(i) ? yz(j) ? i lt j))
• includes ? Se ? Se ? Sc ? Sc extends ? Se ? Se
  ? Sc ? Sc
• Symbolic Rule 1. ?x, y (x includes y ? Sc(x) ?
  Sc(y) ? (?z e(z) ? y contains z ? x contains
  z) ? (?p, q e(p) ? e(q) ? p precedesy q ? p
  precedesx q))
• Symbolic Rule 2. ?x, y (x extends y ? Sc(x) ?
  Sc(y) ? (?z e(z) ? y contains z ? x contains
  z) ? (?p, q e(p) ? e(q) ? p happens_beforey q ?
  p happens_beforex q))
• Symbolic Rule 3. ?x, y (x extends y ? Se(x) ?
  Se(y) ? y ? x ? (x? y ? ?p, q Sc(p) ? Sc(q) ? p
  ? x ? q ? y ? p extends q))

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Digital Library Formal Ontology
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Digital Library Formal Ontology

• Consistency Rules
• Catalog-Collection
• A complete catalog has at least one set of
  metadata specifications for each digital object
  in the collection it describes (surjective
  partial function).
• In a consistent catalog, each set of metadata
  specifications describes (exactly) one digital
  object in the related collection (total
  function).
• Scenarios-Society
• A scenario x is consistent with regards to a
  set of service managers Y if each operation
  executed by each event in the scenario is defined
  in some service manager y ? Y.

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Digital Library Formal Ontology

• Characterizing employs/produces relationships
• In the table each service is characterized by
• parameters (input, output)
• of the initial and final events
• of the scenarios that compose those services
• All other previous definitions and keys apply
  here.
• That set is complemented with the following
  definitions

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Services Related Definitions

• A query q is the representation of user interest
  or information need.
• Hyptxt is an hypertext wherein an anchor is a
  node.
• A log_entry is a descriptive metadata
  specification about an event of a scenario.
• Let doi doi1, doi2,, doin be a set of
  digital objects and Ct c1, c2,,cn be a set
  of labels for categories. A classifier classCt
  doi ? 2Ct is a function that maps a digital
  object to a set of categories.
• A cluster cluk do1k, do2k, , donk is a
  subset of a set of digital objects.

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Service User input Other Service Input Output
Acquiring doi Ci Cj
Browsing anchor Hyptxtk doi
Cataloging doi, msi_k (hi, mssi_m) (hi, mssi_(mk))
Classifying doi classCt (doi, ck_i)
Clustering doi X cluk_i
Expanding (query) doi IC_i, qi qj
Indexing Ci none IC_i
Linking doi Hyptxtk Hyptxtik
Logging none ei(pi) log_entryi
Rating doi ,acj none (doi,acj,rk)
Searching q, Ci IC_i dok
Visualizing doi tfrk spik
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Applications A Taxonomy of DL Services

• Infrastructure Services dealing with basic
  concepts such as collections and catalogs
• Repository-Building create collections (digital
  objects) and/or catalogs (metadata
  specifications).
• Preservational generate instances by copying
  collections (digital objects) or transforming
  (converting/translating) objects into different
  formats for preservation purposes
• Add_Value either aggregate value/information to
  collections (digital objects) or connect objects
  together.
• Information Satisfaction dealing with higher
  level societal requirements
• KEY in next slide
• Fundamental minimal set of services or essential
  to existence of a DL
• Composite DL service takes input from some
  other service otherwise the service is called
  elementary.

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Applications A Taxonomy of DL Services
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Application A Taxonomy of DL Services
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DL Services I/O Behavior

• Regarding the prior figure, which shows
• Instantiations of the Services Definition model
• Inputs and outputs of examples of infrastructure
  and information satisfaction DL services
• Key
• CDL Collection
• ICDL index for collection CDL
• doi digital object
• Soc Society

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Applications A Taxonomy of DL Services
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Application Defining Quality in Digital Libraries

• Formal theory can help to define whats a good
  digital library by
• Formally defining metrics of quality for each
  formal concept (and relationships)
• Helping defining and applying numerical measures
  to these metrics
• Consider this in the Information Life Cycle

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Defining Quality in Digital Libraries
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Defining Quality in Digital Libraries

• Metadata specifications and metadata format -
  completeness
• Completeness of metadata specifications refers to
  the degree to which values are present in the
  description, according to a metadata standard. As
  far as an individual property is concerned, only
  two situations are possible either a value is
  assigned to the property in question, or not.
•  Metric
• Completeness(msx) 1 - (no. of missing
  attributes in msx/ total attributes of the schema
  to which msx conforms)

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Defining Quality in Digital Libraries

• Metadata specifications and metadata format -
  completeness
• OCLC NDLTD Union Catalog

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Defining Quality in Digital Libraries

• Services - Extensibility and Reusability
• A service Y reuses a service X if the behavior of
  Y incorporates the behavior of X.
• A service Y extends a service X if it subsumes
  the behavior of X and potentially includes
  additional subflows of events.
• Metrics
• Macro-Reusability(Serv) (? reused(sei), sei ?
  Serv)/ Serv, where reused is a 1, if ? smj,
  sej reuses si 0, otherwise.
• Micro-Reusability(Serv) (? LOC(smx)
  reused(sei), smx ? SM, sei ? Serv, sex runs sei
  )/ ?LOC(sm), ?sm ? SM, where LOC corresponds to
  the number of lines of code of a service manager

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Defining Quality in Digital Libraries

• Services - Extensibility and Reusability

Macro-Reusability 3/16 0.187 Micro-Reusability
3630 / 11910 0.304
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Application Re-engineering a DL Specification
Language

• 5SL Specification Language
• Reengineering
• Using the relationships to redefine/reorganize
  the semantics and organization of the XML
  elements within the several sections of the DL
  specification

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Re-engineering a DL Specification Language
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Re-engineering a DL Specification Language
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5SLGen Automatic DL Generation
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Conclusions and Future Work

• Presented a DL formal ontology which specifies
  the semantics of the relationships among the DL
  concepts therefore completing a theory for DLs
• Applied the resulting ontology to
• Define a taxonomy of DL services
• Create a Quality Model for DLs
• Re-engineer a DL specification language

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Conclusions and Future Work

• Future Work Include
• Including Pre- and Post-Conditions in the Service
  Behavior Analysis
• New Applications of the Model/theory
• New Design and Generation Tools
• Quality tools
• Modeling Complex Heterogeneous/Integrated Systems
• Archaeology (ETANA)
• Develop theorems and proofs
• Writing books