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Lifecycle Support for Networked Ontologies. The NeOn Team Luxembourg, 25 May 2005. Economic and socio-technical background. Closed Applications  Open Applications Key is the ability to handle large quantities of heterogeneous data in dynamic networked environments

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lifecycle support for networked ontologies

Lifecycle Support for Networked Ontologies

The NeOn Team

Luxembourg, 25 May 2005

economic and socio technical background
Economic and socio-technical background
  • Closed Applications  Open Applications
    • Key is the ability to handle large quantities of heterogeneous data in dynamic networked environments
    • Data integration and maintenance the key barrier to large-scale development of applications on the (open) web
  • Ontologies – enablers of large scale data integration
    • Predicted markets: from $2billion now  $63billion in 2010
  • Opportunity
    • build systems exhibiting a level of complexity qualitatively superior to the current generation of semantic systems, by integrating large, reusable semantic resources.
  • Challenge
    • current methodologies and technologies are simply not sophisticated enough to support the whole application development lifecycle for the envisaged applications

Question 1

concrete contributions
Concrete contributions
  • System-level contributions = methodology, architecture, toolkit
    • for managing the complete lifecycle of networked ontologies, meta-data and contexts associated with them
    • open, robust, scalable,service-centredreference architecture
    • the NeOn toolkit for working with networked ontologies
  • Contributions to foundational research = methods & tools
    • for managing with dynamic, evolving, possibly inconsistent and contextually grounded networked ontologies
    • supporting large-scale collaborative development, taking into account consensus, communal trust and group context
  • Also…
    • Sector-level contributions:
      • Three truly innovative testbeds in two sectors
    • Community-level contributions:
      • Creation of an active and live community of users and developers

Questions 1, 2, 9

worst case no neon project
Worst case: no NeOn project
  • Missed opportunity to achieve a major competitive advantage over US in scalable, open semantic solutions
    • We are already ahead of US in this area
    • …but no major effort on ontology infrastructure
      • which is the key area…
    • …also no NeOn implies no major ‘leap forward’
    • …and stagnation means losing competitiveness
  • We are already experiencing a ‘software crisis’
    • Systems are isolated, small-scale and closed
    • …and this will get worse
    • Key technology push towards “EU to become most competitive knowledge-based economy of the world by 2010” will not take place

Question 1

reducing budget reducing thrust
Reducing budget = reducing thrust
  • Very strong track record in implementing concrete solutions
  • NeOn budget carefully worked out  we believe it provides good value for money
    • A €15M project, returning 1,640 person-months, for a €10.6M EU investment (request for funding from EC is 69.1% p.65)
    • Frequent failures of software projects due to budget underestimation
  • 5% funding reduction:
    • Across the board hit increases the risk of not achieving quality
  • 10% funding reduction
    • Re-focusing effort and shelving some competitive advantages

Question 1

ambitions visions impact areas
Ambitions, visions, impact areas
  • Technology-level
    • NeOn as a bootstrapping means to foster sustainable innovation
      • Raise awareness of IT industry of semantic and NeOn technologies

…and address the inflated expectations on ‘intelligent’ technologies

  • Market-level
    • Improve and scale business in semantic technologies
      • Transplant lessons learnt from NeOn cases to other sectors
      • Capture a share of market in ontology engineering tools and in development of large-scale ontology-driven semantic applications
      • Achieve critical mass of impact ‘catalysers’, esp. among key players
  • Impact and Measures of Success  see detailed Measures
    • NeOn Reference Architecture and methodology de facto standard
    • Research uptake and dissemination
    • Contribution to knowledge systems markets

Questions 2, 3, 5

neon beyond the neon project
NeOn beyond the NeOn project
  • “” … a foundation and developers community
    • overseeing reference architecture, its future developments and co-ordination of the activities of NeOn community (fully supported by all partners)
  • “” … a spin-off company or partnership
    • jointly exploiting the core of NeOn technology & infrastructure
  • “*.com” … individual/private enterprises
    • mainly existing commercial partners marketing their own products
    • using specific parts or modules from NeOn infrastructure or architecture
  • …in short, learn from Apache (esp.), but also Mozilla, Jabber,…
    • Implications on Licensing Policy:
      • NeOn toolkit and reference architecture available as Open Source
      • linkages to commercial back-ends and processes (Software AG’s EII)
      • support for third-party extensions through compliance to standards
      • additional (paid-for) functionalities for ontology management

Questions 5, 6, 7

competitive environment prot g
‘Competitive’ environment (Protégé)
  • NeOn – replacement for Protégé
    • Appropriate a share of Protégé 3.5k developers and 11k users
  • More psychological decision than technical, but…
    • Protégé is the preferred tool only for ontology & KB population
    • Users prefer other tools to design ontologies, collaborate and infer rules
  • First-hand experience from various mailing lists:
    • Protégé’s support for large (e.g. NCI) or detailed ontologies (e.g. DOLCE) and reasoning is insufficient (See extracts from mailing lists in the notes)
      • Steep learning curve and many practical features missing
      • Basically, an editing environment that is continuously extended
  • NeOn – a one-stop shop for ontology design, mapping & contextual adaptation
    • Plug-in reference architecture to enable wider uptake
    • What is at the core of NeOn  see "beyond feature comparison"

Questions 8, 9

competitive environment cyc ibm
‘Competitive’ environment (*Cyc, IBM)
  • Cyc’s SKSI aims at similar market segment
    • Enable Cyc KB-s to integrate external knowledge sources
      • Focus on mapping of schemas (incl. translation, dependency,…)
    • Draw on multiple sources to answer queries (‘middleware’)
      • Contextual inconsistencies in integrated KB-s, evolving mappings…
    • OpenCyc vs. ResearchCyc vs. [Full]Cyc = different niches:
      • Usability / user friendliness of *Cyc…
  • Halo competition provides some insights:
    • OntoStudio more efficient than Cyc without sophisticated model
      • Cyc focuses on large number of instances  is this the issue for industrial-strength support for ontology design and use?
  • IBM’s SnoBase, Ontology Managing Tool, etc.
    • Different playing field, very simple functionality, basic user needs
    • Shows the need for usable, user-friendly systems
      • Usability IS the key strategic need for NeOn!

Question 10

existing collaborative environment
Existing ‘collaborative’ environment
  • Reuse not reinvent – learn from SEKT, KnowledgeWeb (but also Dot.KoM, AKT, DIP, etc….)
    • NeOn starts where these projects plan to stop
    • …adding the networked and contextual dimensions
    • …tackling integration and infrastructure seriously
    • Specific results we will build on are included in the notes
      • For example, ontology construction/extraction

Re: Ontology learning, acquisition, population

    • NeOn is not primarily about learning or extracting ontologies
    • Pragmatic stance: put existing methods in practice

…however, learning relates to context building, e.g.

      • in terms of predicting structural evolutionary changes (WP1)
      • in terms of generalizing from user level to communities (WP2)

Questions 4, 11, 13

how neon works technical clarifications
How NeOn works… (technical clarifications)

Re: Modularity and plug-ins

  • NeOn focusing on “design” end of app lifecycle
  • Complements foci of “use” oriented projects (X-Media, MIAKT)
    • NeOn’s offering orthogonal to others  they may both use NeOn as reference platform and contribute with special purpose plug-in modules

Re: Representation formalisms

  • OWL and F-logic + open to lightweight DL languages that have log-space worst case complexity  query instances & model relations!
  • Service-oriented architecture  translation between languages

Re: Context and its representation schemas

  • Logic-based approaches [Guha & McCarthy, C-OWL] vs. probabilistic approaches
  • Hybridization might be a way to achieve ‘good enough’ yet scalable solutions
    • Deliver flexibility and handle inconsistencies (in networked ontologies and in perspectives of different communities)

Questions 12, 13, 14

stress testing use cases
Stress-testing & use cases
  • System- rather than component-level complexity
    • Issues not with ontology size but with richness of mappings, contextual interpretations and continuous evolution
      • Millions of concepts vs. millions of instances (learn from KWeb)
    • Variety of tests needed:
      • Acquire and validate application requirements (mock-ups, user focus groups)
      • Validate and test software design (early and rapid prototyping)
      • Validate and test ontology (incl. expressivity, usability, complexity)
      • Validate and test software deployment (incl. usability)
  • Size matters – we aim to do things smarter rather than bigger
    • Human factors are more essential to apps with ‘000 editors (incl. view filtering, adaptation, simple visualization, navigation, wrapping,…)
    • For further details of tests see fisheries example in the notes

Questions 15, 16

neon critical mass of brainpower
NeOn – critical mass of brainpower
  • Right mix of expertise, market focus and track record
    • Build synergies to sustain leadership in ontology engineering
      • Partners selected to fill in identified gaps in the state-of-the-art
  • USFD – one of reliable bridges to precursor projects
    • Unique expertise, practical experience, proven track record (Dr. Cunningham)
      • Representation, storage and evolution of meta-data (WP1)
      • Large-scale meta-data collection management & evolution
      • The Networked Annotation and Mining Environment (WP2 )
    • SEKT, KnowledgeWeb, AKT
      • Supporting meta-data creation & resource annotation in the case studies  reuse of well-known USFD’s core competence
  • Implication of consortium composition on budgets
    • Travel/equipment budgets conservative & reflect NeOn ambitions
    • Travel comprises 6.52%, equipment 2.07% of total €15mil budget
      • See details on travel/equipment budget

Questions 17, 20

neon at the frontline
NeOn at the frontline
  • Core individuals at the frontline
    • Prof. Motta (OU) … co-ordinator
      • 20-yrs experience in large collaborative projects (AKT, KWeb, Vital,…)
    • Prof. Motta (OU) & Prof. Studer (UKARL) … joint scientific directors
      • Combined 50-yrs experience in leading edge research
    • Ms. Whild (OU) … project manager
      • 15-yrs experience in managing large, high-profile projects
      • First at Ernst & Young and then at The Open University
  • Streamlined project management  Executive PMB
    • Core individuals + equitable representation from core partners
    • Total effort: 81 PM  incl. Ms.Whild (48 months) + admin. assistant (P/T)
    • EPMB includes liaisons to Technical, Scientific & Exploitation Boards
      • Efficient delegation and acting on decisions and issues
    • See further details on sharing responsibilities in the notes

Questions 18, 19

different risks distributed risk mgt
Different risks  distributed risk mgt.
  • Consortium Agreement – basis for risk and quality mgt.
    • Risk impact categorization … high, medium, low
    • Guidance for risk resolution … monitoring and contingencies
      • WP12 includes periodic deliverables to maintain transparency

Human resources (PMB)

Technological (TMB)

  • Tool interoperability
  • Technology change & re-design
  • Limited functionality of module
  • Partner leaving
  • Multi-disciplinary nature
  • Staffing, recruitment

Risk management (EPMB)

Market (PEDB)

Scientific (PSB)

  • Change in market needs
  • User acceptance
  • Method/technique robustness over-estimated

Question 19

risk of stretching thin
Risk of stretching thin?
  • Definitely not, limit of projects participated in was enforced in early stages of bid writing
    • Max. 2 substantial & justifiable involvements + 1 minor involvement
  • Parallel funding to institutions vs. research groups
    • Parallelism on the institutional level (university, corporation)
    • Well-defined key responsible persons on the unit/group level
      • Minimal or no overlaps among groups in one institution
      • Senior leader + min. 1 established researcher/manager with track record dedicated to the NeOn project
      • Individuals named in section B.5 will participate, no ‘dead souls’
      • Partners successfully concluded FP5 projects  free capacity
  • The cross-fertilization with other initiatives is a potentially unique and non-imitable competitive advantage

Question 21















The End

Here the presentation ends.

The subsequent slides were included in Notes…

impact and measures of success
Impact and Measures of Success
  • NeOn Reference Architecture and methodology de facto standard
    • Size of developers community (both downloads and active developers)
    • Sales of NeOn handbook
    • Major companies – ‘gatekeepers’ adopting NeOn technology
  • Research uptake and dissemination
    • Publications, dissemination events, etc.
      • Number, timeliness and quality of published outcomes
  • Contribution to knowledge systems markets
    • Increased efficiency of work in distributed environments
      • Small businesses using NeOn technology to create competitive networks faster and more efficiently
    • Ontologies in the mainstream software development
    • Organizations reusing best practices from NeOn case studies


Questions 2, 3, 5

neon vs prot g timing costs motivation
NeOn vs. Protégé timing, costs, motivation
  • User group  specific focus  different speeds of adoption
  • Where NeOn is likely to win:
    • Tight coupling with powerful reasoners with track record
    • NeOn starts with native support for service-oriented architecture
    • First-class support for collaboration & contextualization
    • Scalability is a big issue for Protégé
  • NeOn – a one-stop shop for ontology design, reuse, mapping, contextual & communal adaptation
    • What is at the core of NeOn  see "beyond feature comparison"
  • Plug-in paradigm of NeOn reference architecture
    • Enables third-party extensions and wider uptake
    • Flexibility  popularity (‘my first ontology design tool’)

Question 8, 9

beyond feature by feature comparison
Beyond feature by feature comparison…
  • NeOn is going to provide a qualitatively different, radically more advanced technology than Protégé
    • Networked ontologies
    • Contexts
    • Collaboration
    • Trust
    • Open to services
    • Reference Architecture
    • LifeCycle
    • Etc..


Questions 8, 9

neon is about

Lifecycle and Evolution

Multiple Users

Multiple Contexts

Collaborative Service-based Infrastructure

From ‘one-size-for-all’ to contextual awareness

Application adaptability

Managing inconsistencies

Open Reference Architecture

NeOn Ontology Design Toolkit

NeOn is about…

Scalability and Usability of Networked Ontologies

stress testing use cases1
Stress-testing & use cases
  • Cases cover technology- and user-centred aspects
  • Each case will appoint Case Study Test Board
    • Different views (technologists, users, methodologists, independents)
    • Defines/refines test plan, liaises with users & testers, feeds back
  • Key types of tests  checkpoints (see fisheries example)
    • Acquire and validate application requirements
      • Mock-ups, requirement acquisition in user focus groups
    • Validate and test software design
      • Test plan for entire software lifecycle, early and rapid prototyping
    • Validate and test ontology (incl. expressivity, usability, complexity)
      • Cross-testing on application requirements, cognitive walkthroughs
    • Validate and test software deployment (incl. usability)
      • Unitary tests, integration tests, systems tests, acceptance tests

Questions 15, 16

example tests in agriculture sector
Example tests in Agriculture sector
  • Validate and test ontology (incl. expressivity, usability, complexity)
    • Construction and updates of networked ontologies
      • Staff involved in fishery resource management widely distributed
      • Frequency and geographic clustering of manual edits
      • Number of contextually relevant updates triggered by NeOn system
    • Use and maintenance of networked ontologies
      • Study use of networked ontologies in searching FIGIS and FAO web
      • Relevance of search results for current/single vs. networked ontologies
  • Validate and test software deployment (incl. usability)
    • Integrating and mapping networked ontologies
      • Number of overlaps among current ontologies
      • Context emergence – similar topics, different coverage and granularity
      • Number of editors – before/after training, coaching sessions,…


how neon works technical clarifications1
How NeOn works… (technical clarifications)

…however, learning relates to context building, e.g.

  • in terms of predicting structural evolutionary changes (WP1)
  • in terms of generalizing from user level to communities (WP2)
    • Support geographically distributed communities
    • Annotate using networks of ontologies and networked ontologies
    • Client-server enables customization, adaptation to diff. GUI-s
  • in terms of acquiring information on contexts (WP3)
  • In terms of choosing appropriate/typical presentations (WP4)

Questions 11, 13

neon sharing responsibilities
NeOn – sharing responsibilities
  • Shallow, accessible management structure – 2 lines
    • Co-ordinator  Administrator  Partner Leaders  Members
    • Scientific directors  Executive PMB  Other Boards  Members
  • Equitability, transparency, fairness, efficiency
    • Formally incorporated into Consortium Agreement
    • Fair representation on EPMB (not on size nor on funding)
      • 3 academic, 1 SME & 1 large partner; incl. min 1 female member; no nationality/country prevails
    • EPMB includes liaisons to Technical, Scientific & Exploitation Boards
    • Two ‘All Hands’ meetings a year + frequent virtual meetings
      • Foster interaction, prevent rather than solve conflicts
      • Utilize modern ICT to create a sense of joint enterprise and presence (BuddySpace, FlashMeeting, Hexagon)
    • Org. chart available in Figure 10, page 58 of the proposal

Questions 18, 19


implications on travel equipment budget
Implications on travel/equipment budget
  • Both budgets are conservative & reflect NeOn ambitions
    • Travel comprises 6.52%, equipment 2.07% of total €15mil budget
  • NeOn – a joint enterprise of distributed stakeholders
    • Ambitions to become the de-facto standard  dissemination
    • Life beyond NeOn funding  live & educated community
    • We must be pro-active in approaching key users  ‘gatekeepers’
    • Leading on quality & differentiation
  • We are conscious of ‘value for money’
    • Low-cost electronic media  virtual presence (OU is the leader)
    • Open Source or specially negotiated free commercial technologies
    • Re-use not re-invent
      • e.g. Atos’ mgt. portal,
      • UPM’s semantic portal,
      • OU’s virtual meetings


Question 20