OKKAM Enabling the Web of Entities A SCALABLE AND SUSTAINABLE SOLUTION FOR SYSTEMATIC AND GLOBAL IDE

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OKKAM Enabling the Web of EntitiesA SCALABLE
AND SUSTAINABLE SOLUTION FOR SYSTEMATIC AND
GLOBAL IDENTIFIER REUSE IN DECENTRALIZED
INFORMATION ENVIRONMENTS

• KnowDive Seminar
• April 11, 2007
• Trento, Italy

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Background KR goes Global

• Knowledge representation is a field which
  currently seems to have the reputation of being
  initially interesting, but which did not seem to
  shake the world to the extent that some of its
  proponents hoped.
• It made sense but was of limited use on a small
  scale, but never made it to the large scale. This
  is exactly the state which the hypertext field
  was in before the Web.
• Each field had made certain centralist
  assumptions -- if not in the philosophy, then in
  the implementations, which prevented them from
  spreading globally.
• But each field was based on fundamentally sound
  ideas about the representation of knowledge.
• The Semantic Web is what we will get if we
  perform the same globalization process to
  Knowledge Representation that the Web initially
  did to Hypertext. We remove the centralized
  concepts of absolute truth, total knowledge, and
  total provability, and see what we can do with
  limited knowledge.
• Tim Berners-Lee, What the Semantic Web can
  represent, 1998

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In practice
Web of Meanings
Niederee
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Bouquet
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UniTN
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L3S
VIKEF
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Web_page
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www.unitn.it
www.trento.it
www.ryanair.com
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www.l3s.org
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www.paolobouquet.net
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www.google.com
ockham.org
Web of Links
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What went wrong (personal view)

• The Web of Meanings (the Semantic Web) is not
  happening, at least not as the WWW happened along
  the 90s
• Enabling factors for the Web of Links (the WWW)
• Any available resource has a global URL, which
  allows Web clients to address it
• The same identifier can be resolved to retrieve
  the resource through the HTTP protocol (running
  on top of TCP/IP)
• Creating href links is easy on top of this
  infrastructure
• What about the Web of Meanings?
• Non addressable resources do not have an
  infrastructure for supporting the use of global
  identifiers (more about this)
• Non addressable resources cannot be retrieved
• Creating global links between non addressable
  resources is difficult
• Outcome we lack the preconditions for the Web of
  Meanings to happen!

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Further (strategic) errors

• On top of these infrastructural issues, a big
  strategic error was made (personal opinion!)
• The AI people came in, and tried to recycle
  their logical know-how on the Semantic Web
• The plan was to build the Semantic Web starting
  from representations (theories, currently known
  as ontologies) and not from resources (entities)
• This led to a scalability issue reasoning is
  hard for local theories, forget about going
  global! Heard about semantic heterogeneity,
  ontology mapping, alignment, distributed
  reasoning, ?

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My vision

• Back to the building blocks entities!
• First, create the infrastructure for enabling in
  practice a global space of identifiers (e.g.
  URIs)
• Second, show how we can create value simply from
  linking globally identified entities
• Third, specify vocabularies and ontologies for
  (subsets of) globally identified entities
• Fourth, link ontologies to each others on top of
  the already integrated domain of globally
  identified entities
• Hopefully, this will lead to the Web of Entities,
  namely a global digital space in which any
  knowledge expressed in any local web of entities
  can be seamlessly integrated and reasoned about

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OKKAM overall goal

• The goal of the OKKAM project is to implement the
  first part of this plan.
• Establishing a scalable and sustainable
  infrastructure for the storage and reuse of
  global identifiers for non addressable entities
  in decentralized information environments
• Enabling different forms of OKKAMization of old
  and new content
• Creating a primitive index which links global
  identifiers to OKKAMized content
• Building applications which can showcase the
  potential value of this approach

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But why OKKAM?

• Ockham's Razor (14 century)
• entities should not be multiplied beyond
  necessity
• OKKAMs Razor (21 century)
• entity identifiers should not be multiplied
  beyond necessity

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1. Infrastructure

• Cornerstone large-scale EntityRepository (ER)
• Architecture distributed, supports federation of
  local ERs, replicated (no single point of
  failure)
• ER vs. Entity Base (or Knowledge Base)
  supporting reuse vs. collecting and providing
  knowledge about entities
• Basic schema set of attribute/value pairs
  (called labels) with no predefined semantics
• Features
• Size unbelievable (billions of
  identifiersprofiles stored
• Network traffic massive (up to millions of
  requests per minute)
• Quality hard to ensure
• Update grows monotonically (no deletion). Aging
  mechanism?

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2. OKKAMization

• Enabling the runtime or ex post OKKAMization of
  data in various formats (from unstructured to
  structured)
• Examples
• Office tools (named entity recognition and
  annotation)
• Databases (annotating records with OKKAM ids)
• Ontologies (replacing local URIs with global
  URIs)
• HTML pages
• Objective creating the critical mass of
  OKKAMized content

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3. Indexing

• The model of knowledge devolution
• The ER stores only IDs simple labels
• Knowledge about entities must be developed
  outside
• Idea use OKKAM to store and index pointers to
  external resources which mention an OKKAM id
• Different types of pointers
• Informal pointing to a document which contains
  an OKKAM id as a simple annotation for a piece of
  text
• Formal pointing to formal resources (e.g.
  ontologies) in which an OKKAM id is used as a URI
  of an instance
• Using this index also for entity resolution /
  matching

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Okkam Architecture
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Okkam Applications

• Three examplary applications on top of OKKAM
  infrastrucure
• Entity-centric search engine
• Entitity-centric organizational knowledge
  management
• Multimedia authoring based
• Purpose
• Show benefits of entity-centric approach
• Trigger the development of further applications
• contribute to building a community around the
  OKKAM approach

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Entity-centric search engine

• Starting point Different types of OKKAMized
  content collections, e.g. knowledge bases,
  document collections, metadata repositories,
  image collectons, etc.
• Goal
• enabling completely new methods for browsing and
  searching large collections of data and documents
  (including the Web itself)
• enable new forms of intelligent entity-centric
  search that exploit the OKKAMization of content
• RTD Challenges
• Retrieval indexing that takes into account the
  OKKAM IDs
• Combination of entity-centric and semantic search
• Combined ranking
• Adequate combination and visualization of the
  results from different kinds of resources (e.g.
  knowledg base document collection)
• ...

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Entity-centric organizational knowledge management

• Idea
• Exploit OKKAM benefits in organizational context,
• Managing and structuring corporate knowledge
  using entity identifiers as pivots for
  aggregating information not only from structured
  sources, but also from poorly or non-structured
  sources, like electronic documents, email
  messages, slide presentations, video and audio
  files, etc.
• Using and interlinking a local organizational
  entity repository

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Multimedia Content Authoring

• Idea
• Creation of an authoring environment, which makes
  use of the OKKAMization of content
• Variants
• authoring environment, which helps the scientific
  author by providing targeted additional
  information during writing process
• Support for the creation of value added artefact
  on the basis on OKKAMized content (text, video)
• creation template for task-specific /selective)
  enrichment with information about the entity
  found in the content object (semantic infusion)
• tool for publishers, broadcasters

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Example Semantic Infusion
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RTD Challenges

• Building a scalable entity repository in which a
  massive and growing number of entity IDs and
  profiles can be collected, stored and indexed
• Guaranteeing security and privacy for the data
  stored in the repository
• Making the repository efficiently searchable and
  usable by Web users as well as through APIs
• Supporting effective and reliable methods for
  entity matching and for ranking results
• Enabling several channels through which the
  repository can be populated, either manually or
  automatically (import filters, crawling,
  harvesting, )
• Supporting the integration of OKKAM with a
  variety of content creation applications (e.g.
  text editors, office applications, HTML and XML
  editors, ontology editors, DBMS, etc.)
• Ensuring the quality of data in the repository
• Enabling a virtuous circle of trust and
  collaboration with users

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Conclusions

• There are many critical issues
• Size and Performance
• Quality of entity search and matching
• Critical mass of data and applications
• Trust and community building
• Sustainability and exploitation
• but its fun and I want to give it a try!!