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Semantic technologies opportunities and issues for e-Government initiatives A talk by Yannis Kalfoglou at Monday, 18 th June 2007

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Overview <ul><li>Emergence ( and maturity of ) semantic technologies </li></ul><ul><ul><li>From the academic silos to industrial settings </li></ul></ul><ul><ul><li>Web 2.0 and Semantic Web drivers </li></ul></ul><ul><li>International and national trends towards a knowledge society </li></ul><ul><ul><li>Cutting edge factor </li></ul></ul><ul><ul><li>Engagement of the electorate </li></ul></ul><ul><ul><li>Knowledge economies </li></ul></ul><ul><li>Opportunities </li></ul><ul><ul><li>Use of semantic technologies </li></ul></ul><ul><ul><li>Web 2.0 & social networks </li></ul></ul><ul><li>Issues </li></ul><ul><ul><li>Technology gaps and knowledge representation adequacy </li></ul></ul><ul><ul><li>Social software, trust and community input </li></ul></ul><ul><ul><li>Business models re-engineering and change </li></ul></ul><ul><li>Experiences </li></ul><ul><ul><li>CS AKTive Space, 3Store, e-Response demonstrator, AKTive PSI </li></ul></ul><ul><ul><li>Ontology mapping </li></ul></ul><ul><li>Conclusions </li></ul><ul><ul><li>Adoption strategies </li></ul></ul><ul><ul><li>Societal implications </li></ul></ul><ul><ul><li>Synergy with legacy systems </li></ul></ul>Background Semantic technologies Knowledge society Opportunities Issues Experiences Conclusions 2/18

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Background Article ( to appear ): “ Knowledge society arguments revisited in the Semantic technologies era”, Y.Kalfoglou, International journal of Knowledge and Learning, 3(3/4)., special issue: “ Knowledge society: a roadmap for Government consultation”, 2007 Dagstuhl seminar on Semantic Interoperability and Integration, 04391, Sept. 2004, organised by Y.Kalfoglou AKT legacy: 6 year, multi million pound, multi site interdisciplinary research collaboration CS AKTive Space,3store, e-Response demonstrator, AKTivePSI Background Semantic technologies Knowledge society Opportunities Issues Experiences Conclusions 3/18

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Semantic Technologies why do we need them? Background  Semantic technologies Knowledge society Opportunities Issues Experiences Conclusions <ul><li>business drivers </li></ul><ul><ul><li>unprecedented exposure of information in digitised form  too much information available: “ infosmog ” </li></ul></ul><ul><ul><li>turn information into usable knowledge </li></ul></ul><ul><ul><li>collaborative, inter-organisational business systems </li></ul></ul><ul><ul><li>globalisation of business processes – need for increased interoperability </li></ul></ul><ul><ul><li>empowerment of the individual </li></ul></ul><ul><ul><li>retention of knowledge </li></ul></ul><ul><ul><li>reduction of implementation time and cost </li></ul></ul><ul><li>societal drivers </li></ul><ul><ul><li>trends in employment: “up to 30% of EU’s working population will be directly employed in the production and diffusion of knowledge” </li></ul></ul><ul><ul><li>knowledge based economy </li></ul></ul><ul><ul><li>ICTs affordable and available to everyone – participation is cheaper and global </li></ul></ul><ul><ul><li>(1.1bn web users) </li></ul></ul><ul><li>technology triggers </li></ul><ul><ul><li>syntax based systems can’t cope with information explosion ( semantic heterogeneity ) </li></ul></ul><ul><ul><li>semantics can be codified and represented in computational form </li></ul></ul><ul><ul><li>maturity of highly distributed open-end environments, e.g., (Semantic) Web; and Web 2.0 approaches (social networking) </li></ul></ul>4/18

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<ul><li>Emergence of “meaningful computing”: emphasis on codified representations of semantics </li></ul><ul><ul><li>represent meaning in computational forms; </li></ul></ul><ul><ul><li>enable automation and intelligent tasks; </li></ul></ul><ul><ul><li>better information management (search, discovery, integration); </li></ul></ul><ul><ul><li>enable re-use; </li></ul></ul><ul><ul><li>improved interoperability (semantic-based vs. syntax-based) </li></ul></ul><ul><li>Wide range of technologies: </li></ul><ul><ul><li>ontologies (OWL, KIF, Ontolingua, etc.) </li></ul></ul><ul><ul><li>data formats (RDF & RDF(S), ebXML ) </li></ul></ul><ul><ul><li>query languages (SPARQL) </li></ul></ul><ul><ul><li>APIs (HP Jena) </li></ul></ul><ul><ul><li>open standards (OG(eo)C, SUO, CL) </li></ul></ul><ul><ul><li>SOA </li></ul></ul><ul><ul><li>… </li></ul></ul><ul><li>Variety of application areas: </li></ul><ul><ul><li>knowledge representation & reasoning (ontologies) </li></ul></ul><ul><ul><li>semantic annotation (semantic tagging) </li></ul></ul><ul><ul><li>semantic querying (SPARQL, OWL-driven) </li></ul></ul><ul><ul><li>semantic interoperability and integration (ontology/schema mapping) </li></ul></ul><ul><ul><li>semantically enriched storage (RDF) </li></ul></ul>Semantic Technologies what are they? where do we apply them? Background  Semantic technologies Knowledge society Opportunities Issues Experiences Conclusions 5/18

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<ul><li>Semantic Web </li></ul><ul><ul><li>(towards) an infrastructure made up of representation languages, communication protocols, access controls & authentication services for coordinated sharing of knowledge across particular domain-oriented applications </li></ul></ul><ul><ul><li>(vision) turning the web into a globally distributed knowledge base where software agents will assist in most, if not all, tasks of information management </li></ul></ul><ul><li>Web 2.0 </li></ul><ul><ul><li>enabling technologies for mass participation in social networking activities on the Web </li></ul></ul><ul><ul><li>range of supporting technologies (AJAX, wikis, tagging, bloging, etc.) </li></ul></ul><ul><ul><li>no centralised control, no agreed vocabularies, “wisdom of the clouds” (collective intelligence) </li></ul></ul><ul><li>Semantic technologies a core component for both </li></ul>Semantic Technologies The Semantic Web and Web 2.0 impact Background  Semantic technologies Knowledge society Opportunities Issues Experiences Conclusions 6/18

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Semantic Technologies maturity Background  Semantic technologies Knowledge society Opportunities Issues Experiences Conclusions The Gartner Hype Cycle (7/06) – time to “plateau of productivity” (Public) Semantic Web: trough of disillusionment  5-10y (Corporate) Semantic Web: peak of inflated expectations  5-10y Web 2.0: peak of inflated expectations  2-5y Web 2.0 More visible Large end user base (Public) Semantic Web Invisible to the end user Infrastructure (Corporate) Semantic Web Better information management Visibility to end user is not an issue 7/18

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Knowledge society principles – the citizen Background  Semantic technologies  Knowledge society Opportunities Issues Experiences Conclusions <ul><li>Quest for knowledge </li></ul><ul><li>Society eager to harness knowledge for life long benefits </li></ul><ul><li>Knowledge as a commodity </li></ul><ul><li>Knowledge available in digitised form </li></ul><ul><li>Empowerment of consumer/citizen </li></ul><ul><li>Consumer/citizen in charge (selection, acquisition & production of knowledge) </li></ul><ul><li>Networking </li></ul><ul><li>Push knowledge onto & selectively pull knowledge from the system </li></ul><ul><li>Digital divide </li></ul><ul><li>Access to ICTs vs use of ICTs </li></ul><ul><li>Digital-literate vs. digital-illiterate </li></ul><ul><li>Clear benefits from participation </li></ul>8/18

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Knowledge society an example case Background  Semantic technologies  Knowledge society Opportunities Issues Experiences Conclusions Social media No moderation or censorship; two-way communication Individuals’ contributions clearly acknowledged; anonymity discouraged Spin and attempt to control are discouraged Pull system – let people bring to them the content and relationships they want Highly distributed, not centralised Adopted from Dion Hinchcliffe’s web site Participation powered by the network effect Low cost People in charge (use and control) Benefit of global scale syndication Democratisation and change of ground rules Shift from institutional control to consumer control 9/18

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Knowledge society principles – e-Government Background  Semantic technologies  Knowledge society Opportunities Issues Experiences Conclusions <ul><li>Enable micro-governance </li></ul><ul><li>encourage people to participate in socio-organisational processes </li></ul><ul><li>engage with the electorate </li></ul><ul><li>educate and promote interests </li></ul><ul><li>Benefits </li></ul><ul><li>outreach to mass audiences </li></ul><ul><li>push knowledge onto the network (digitised form) </li></ul><ul><li>reduce operational and transaction costs </li></ul><ul><li>relate to the public </li></ul><ul><li>Interactivity </li></ul><ul><li>explore new ways of interaction </li></ul><ul><li>explore new roles </li></ul><ul><li>internationalisation </li></ul>10/18

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Opportunities better information access, querying, integration Background  Semantic technologies  Knowledge society  Opportunities Issues Experiences Conclusions E-Government initiatives my.ecitizen.gov.sg - Singapore (personalisation) direct.gov.uk – UK (services) eEurope2005 action plan – EU (interface with the electorate) e-Petitions & e-Voting Direct dialogue with the public – e.g., 1.8M emails to PM wrt. anti-toll petition Voting and electorate management services Blogs Campaigning and rallying (e.g., B.Obama’s campaign in the US) Gauge public interests Engage the public Policy and consultation Intra-governmental (unit2unit, dept2dept) Inter-governmental (government2government) Voting and electorate consultation services 11/18

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Opportunities semantic technologies at work Background  Semantic technologies  Knowledge society  Opportunities Issues Experiences Conclusions Communities of interest Formed up and interact via social networking Common interests and CoP modus operandi Extract semantics monitor and extract semantically rich information from these interactions non-intrusively and openly (tags) Emergent semantics a computational model of these communities technology for processing semantics in place Regulate input regulate and classify that knowledge before we reason about it Provide services use these inferences to better inform and deliver services to the public 12/18

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<ul><li>Technology gaps </li></ul><ul><ul><li>Semantic interoperability vs. ontology building </li></ul></ul><ul><ul><li>Large scale semantic annotation vs. tagging </li></ul></ul><ul><ul><li>Ontology deployment architectures vs. SOA </li></ul></ul><ul><li>Non-uniform representation of communities knowledge </li></ul><ul><ul><li>Emergent semantics idea relies on a stable and uniform representation of interests </li></ul></ul><ul><ul><li>but: non-standard vocabulary </li></ul></ul><ul><ul><li>Possible conflicts of representation </li></ul></ul><ul><ul><li>Reach local agreement first, before achieving global consensus </li></ul></ul><ul><ul><li>Reliance on machine learning (supervised vs. unsupervised methods) – training sets? </li></ul></ul><ul><li>Mechanised trust </li></ul><ul><ul><li>Model and representation – no consensus </li></ul></ul><ul><ul><li>Sourcing – gather, broadcast in centralised units? </li></ul></ul><ul><ul><li>Measuring – no consensus, “who rates the raters”? </li></ul></ul><ul><ul><li>Context – local trust in a global environment </li></ul></ul><ul><li>Cost </li></ul><ul><ul><li>Conversion cost: convert legacy data to RDF, expose data to RDF </li></ul></ul><ul><ul><li>Maintenance cost: ontologies need regular updates </li></ul></ul><ul><ul><li>Organisational re-structuring costs: altering information gathering processes </li></ul></ul><ul><ul><li>Transaction costs: change of management structures </li></ul></ul><ul><ul><li>Reducing costs: increase the size of user base to offset the high cost of development </li></ul></ul><ul><ul><ul><li>Commodity: license the use of ontologies </li></ul></ul></ul><ul><li>BNW vs. BFC arguments </li></ul>Issues technology Background  Semantic technologies  Knowledge society  Opportunities  Issues Experiences Conclusions 13/18

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<ul><li>social software: Embedded observation </li></ul><ul><ul><li>Live the culture you are helping to frame </li></ul></ul><ul><ul><li>Designers love what they do and infuse their passion into the system </li></ul></ul><ul><ul><li>Take into account culture that cannot be systematically tested or modelled </li></ul></ul><ul><ul><li>Awareness of social problems – prompt reaction, bonding with the users (community) </li></ul></ul><ul><li>Respect local, regional and cultural aspects </li></ul><ul><ul><li>Local and regional affairs more important to local communities than national/international </li></ul></ul><ul><ul><li>Culture and customs need to be respected </li></ul></ul><ul><li>Informal gatherings influencing formal decisions (an oxymoron?) </li></ul><ul><ul><li>Online social networking and its decision making power </li></ul></ul><ul><ul><li>Boundaries of informal vs. formal </li></ul></ul><ul><li>Social cohesion and digital multiculturalism </li></ul><ul><ul><li>Voice your concerns in the digital world vs. real world </li></ul></ul><ul><ul><li>Same values, same person, two different personas? </li></ul></ul><ul><li>Blend of state-control vs. “no control” processes </li></ul><ul><ul><li>traditional formal processes vs. web 2.0 style informal modus operandi </li></ul></ul>Issues socio-political Background  Semantic technologies  Knowledge society  Opportunities  Issues Experiences Conclusions 14/18

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<ul><li>CS AKTive Space </li></ul><ul><li> Award winning SW application </li></ul><ul><li> Exploring the domain of a discipline (CS) </li></ul><ul><li> Use of STs to locate, extract, model and use heterogeneous data in a meaningful manner </li></ul><ul><li> Integration and deployment of services </li></ul><ul><li> Time consuming engineering </li></ul><ul><li> Costly ontology building process </li></ul><ul><li> Difficult to re-purpose </li></ul><ul><li> Reliance on external data sources (reliability, responsiveness issues) </li></ul>Experiences Background  Semantic technologies  Knowledge society  Opportunities  Issues  Experiences Conclusions <ul><li>3Store </li></ul><ul><li>Scalable RDF based repository </li></ul><ul><li>MySQL API interface </li></ul><ul><li>proprietary underlying RDF schema model </li></ul><ul><li>commercialised through a spin-off (garlik.com) </li></ul><ul><li> scale </li></ul><ul><li> RDF reliance </li></ul><ul><li> Re-engineering and legacy RDBSs linkage </li></ul><ul><li> Interface </li></ul>15/18

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<ul><li>e-Response demonstrator </li></ul><ul><li>Large scale AKT integrated feasibility demonstrator </li></ul><ul><li>9 technologies from 5 partners </li></ul><ul><li>realistic emergency response scenario </li></ul><ul><li>integrated view over heterogeneous sources and inference across them </li></ul><ul><li> Difficult to replicate </li></ul><ul><li> no integration framework </li></ul><ul><li> Reliance on external data sources </li></ul>Experiences Background  Semantic technologies  Knowledge society  Opportunities  Issues  Experiences Conclusions <ul><li>AKTive PSI </li></ul><ul><li>Initial investigation (9 month proj.) on the use of STs in the public sector </li></ul><ul><li>Positive reception – pilot study to follow </li></ul><ul><li>integrated disparate heterogeneous data </li></ul><ul><li> No user input </li></ul><ul><li> unclear quality criteria </li></ul><ul><li> undefined services </li></ul>16/18

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<ul><li>Ontology mapping </li></ul><ul><li>e-Government alignment scenario </li></ul><ul><li>align UK FCO and HO units to their US counterparts (DoS, DoJ) </li></ul><ul><li> Manual and accurate knowledge acquisition </li></ul><ul><li> Semi-automatic mapping </li></ul><ul><li> Verification and validation of results </li></ul><ul><li> Not clear processes and responsibilities </li></ul><ul><li> Same government, same department, different representation </li></ul><ul><li> No domain expert input </li></ul><ul><li>UK universities alignment </li></ul><ul><li>align CS dept. of 5 top UK universities </li></ul><ul><li> Semi-automatic knowledge acquisition </li></ul><ul><li> Semi-automatic mapping </li></ul><ul><li> Verify and validate results </li></ul><ul><li> Computational cost </li></ul>Experiences Background  Semantic technologies  Knowledge society  Opportunities  Issues  Experiences Conclusions 17/18

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<ul><li>Changing ICTs adoption strategy </li></ul><ul><li>“ Focus on the value that technology adds to people’s lives […] ICTs should be an outgrowth of people’s desires and needs, not an imposition” – EU2004 </li></ul><ul><ul><li>Blend of different stakeholders: technologists, regulators, organisations </li></ul></ul><ul><ul><li>Outgrowth of people needs: Web 2.0 approach (pull vs. push) </li></ul></ul><ul><ul><li>Holistic approaches that respect existing systems and infrastructures </li></ul></ul><ul><ul><ul><li>use legacy systems, not replace </li></ul></ul></ul><ul><li>Semantic technologies adoption </li></ul><ul><ul><li>“ start small with the big picture in mind” </li></ul></ul><ul><ul><li>(from lightweight semantic hypertext markup – microformats - to fully fledged ontologies) </li></ul></ul><ul><ul><li>Prepare for a major shift in business models </li></ul></ul><ul><ul><li>Long term investment, not a quick “cash return” </li></ul></ul><ul><ul><li>Keep it simple (semantics) </li></ul></ul><ul><ul><ul><li>Irreconcilable arguments among engineers at design time </li></ul></ul></ul><ul><ul><ul><li>Inappropriate interpretations and usage at deployment time </li></ul></ul></ul><ul><ul><ul><li>Hard to maintain – not stable over time – obsolete knowledge </li></ul></ul></ul><ul><li>Societal implications </li></ul><ul><ul><li>Privacy </li></ul></ul><ul><ul><li>Trust </li></ul></ul><ul><ul><li>“ Wisdom of the clouds” (collective intelligence) modus operandi </li></ul></ul>Conclusions Background  Semantic technologies  Knowledge society  Opportunities  Issues  Experiences  Conclusions 18/18

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Semantic technologies opportunities and issues for e-Government initiatives A talk delivered by Yannis Kalfoglou at Monday, 18 th June 2007 Thank you

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<ul><li>1. &quot;Technology Trigger&quot; The first phase of a Hype Cycle is the &quot;technology trigger&quot; or breakthrough, product launch or other event that generates significant press and interest. 2. &quot;Peak of Inflated Expectations&quot; In the next phase, a frenzy of publicity typically generates over-enthusiasm and unrealistic expectations. There may be some successful applications of a technology, but there are typically more failures. 3. &quot;Trough of Disillusionment&quot; Technologies enter the &quot;trough of disillusionment&quot; because they fail to meet expectations and quickly become unfashionable. Consequently, the press usually abandons the topic and the technology. 4. &quot;Slope of Enlightenment&quot; Although the press may have stopped covering the technology, some businesses continue through the &quot;slope of enlightenment&quot; and experiment to understand the benefits and practical application of the technology. 5. &quot;Plateau of Productivity&quot; A technology reaches the &quot;plateau of productivity&quot; as the benefits of it become widely demonstrated and accepted. The technology becomes increasingly stable and evolves in second and third generations. The final height of the plateau varies according to whether the technology is broadly applicable or benefits only a niche market. </li></ul>Gartner Hype Cycle