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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