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Toward CERIF-ScienTI Cooperation and Interoperability
 

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The ScienTI and CERIF Models: a Compatibility Analysis Towards Interoperability Among European and Latin-American ST&I Information Networks

The ScienTI and CERIF Models: a Compatibility Analysis Towards Interoperability Among European and Latin-American ST&I Information Networks

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    Toward CERIF-ScienTI Cooperation and Interoperability Toward CERIF-ScienTI Cooperation and Interoperability Presentation Transcript

    • Roberto C. S. Pacheco EGC/UFSC INE/UFSC Instituto Stela - Brasil Toward CERIF-ScienTI Cooperation and Interoperability The ScienTI and CERIF Models: a Compatibility Analysis Towards Interoperability Among European and Latin-American ST&I Information Networks euroCRIS 2006 Bergen, Norway - May 12th 2006 SAS Hotel Bryggen. Lecture Hall Vinicius Medina Kern; José Salm Jr. Instituto Stela - Brasil Abel Laerte Packer; Renato Murasaki BIREME/PAHO - Brasil Luis Amaral; Leonel Duarte dos Santos Universidade do Minho - Portugal Alberto Cabezas Burlemore CONICYT - Chile
      • Introduction
        • Mapping information on a NIS
      • ScienTI Approach
      • ScienTI and CERIF
        • Different world views
        • Complementariness
        • Cooperation in Perspective
      TOPICS
    • Introduction – A National Innovation System University University Government Government Industry Industry NIS – National Innovation System Model Freeman, 1987. Lundvall, 1992 OECD, 1999. Triple Helix Model Etzkowitz & Leydesdorff, 2002.
      • CRIS have impact on all players and sources that are relevant to ST&I stakeholders
        • Government
        • S&T Community
        • Universities and Research Institutes
        • Industry
        • Economy
        • Legislation
        • Intellectual Property
        • Commerce
        • Etc…
    • NIS main features regarding information management
      • Highly decentralized processes with
        • Players with different timetables and requirements
        • Several world views of how S&T information should be mapped
      Please, would you be kind enough to ask all authors their official national IDs? Sorry but our system does not know for sure whether the funded authors are the same as article authors? Librarian Funding agent Then I know for sure that I cannot pay them !!! No way!
    • NIS main features regarding information management
      • The inevitable consequences:
        • Proliferation of data models, information projects and data sources
          • Multiple Funding Agency systems;
          • Multiple Other Public Systems (in each correspondent Ministry)
          • Multiple R&D organizational systems;
          • Multiple Librarian Systems;
          • Multiple Educational Systems;
          • Multiple Firm Systems;
          • Multiple Sector Portals;
        • Although there is a conceptual NIS there are several ST&I information flows.
      • How one can foster S&T information sharing by combining workflow and information modeling?
          • By establishing standards that support all processes in the innovation chain
          • By adopting IT architectures that establish methodological and technological frameworks for future developments
      Research Challenges Some of the Answers
      • How such approach can result from the cooperation involving all ST&I players?
          • Involving the users
          • Involving different CRIS designers
          • Practical Virtual Communities
            • CRIS designers - propose and maintain the standards (national and internationally compatible)
            • User communities - tell us what should be done in the next CRIS versions.
      Research Challenges Some of the Answers
      • How government, universities, R&D organizations, firms or other information owners should develop their CRIS?
          • Respecting the standards (specially governmental authorities)
          • Following best practices (IT architecture, openness, interoperability and information sharing)
          • Having a plan for involving, communicating and motivating the users
      Research Challenges Some of the Answers
    • ScienTI Approach Reference International standards Methodology eGov Architecture International Network ScienTI systems ScienTI standards Web services models ScienTI Network International Network on Information Sources and Knowledge for the Management of Science, Technology and Innovation ONCYTs OICYTs GDIs
    • 2000 VHL Science and Health Meeting
      • Meeting
      • PAHO/BIREME, CNPq and ONCyTs from Latin America and the Caribbean coutries
      • Agreement: links between SciELO-CvLattes
      • Perspectives: to create a health information sources network in Latin America and the Caribbean
      2001 CVLACS System
      • V CRICS: Presentation of beta version to ONCyTs
      • Piloto: Chile, Colombia, Cuba, Mexico and Venezuela
      • Portugal : integrated to the project DeGois Pilot
      1998/1999 Genesis
      • VHL SH: PAHO/BIREME.
      • Information and knowledge sources in health
      • Lattes Platform: CNPq/MCT:
      • Integrated management of Science, Technology and Innovation
      ScienTI Timeline
    • 2002 ScienTI Network
      • CvLAC System in Colombia
      • GrupLAC System in Colombia
      • Bilateral agreements 7 countries with CNPq.
      • Formalization: I Florianópolis Meeting, December 2002
      • Organization: Proposal in Agreement and Inter-institutional Committee.
      2003
      • Institutionalization II ScienTI Meeting.
      • Puebla (VI CRICS)
      • Executive Secretariat – BIREME
      • Indicators.
      • RICYT and PAHO’s studies of the network use in the production of indicators
      Consolidation 2004
      • Launching in other Countries:
        • Peru
        • Venezuela
      • Technology and Methodology. Adoption of web services to descentralized model
      • III ScienTI Meeting – Buenos Aires
      Extension ScienTI Timeline
    • 2005 Formalization
      • Workshop about ScienTI Web Services:
      • 6 countries participated
      • Debate for the signature in the Agreement of Cooperation 12 countries participated.
      • Technology and Methodology. Practice communities available in the ScienTI Regional Portal (documents, chats y foros)
      • Network structure GDI network defined
      • IV ScienTI Meeting – Salvador, Brasil
      ScienTI Timeline 2006
      • Brasil: Innovation Portal, Increasing of Institutional solutions and other public thematic approaches (health survailance, education, environment, etc)
      • Colombia: Peer review system, Firms module, job opportunities
      • Chile: SICTI Portal, Event agenda, New Business model for ScienTI as sustainable space for web services
      • Peru: National Portal searching for CVs
      • Portugal : ScienTI research advancements and planning for help national R&D funding
      • PAHO : International Expertise locator based on ScienTI model and connectable to institutional or national databases
      • Japan – CNPq presents Lattes Platform in Japan beggining cooperation in nanotechnology, biotechnology and biomass http://www.jornaldaciencia.org.br/Detalhe.jsp?id=37535
      Nationally spreading
    • Methodology Pacheco, 2003
      • METHODOLOGY: Perceiving design, development, use and revision as a continuous process is the key to make national platforms constantly growing.
      PROJECT PHASE Requirements (considering all users) Planning (CRIS life cycle) Related Projects Studies Forming Communities for Standards Development and Deployment Management and Maintenance Creating and Managing Knowledge Services (e-services) Interacting with Users Virtual Communities Information Sources OPERATION PHASE
    • eGov Architecture Investiments Indicators Analysis Systems Searches CvDeGois CvLattes CvLAC DM Cv DM Gr DM Inst DM Proj CVs Groups Institutions Projects SCienTI Directories ScienTI Portals Sistema Grupo GrupLAC
    • Investimentos em CT&I ScienTI System - Players CVs Researchers Students Profesionals CvDeGois CvLattes CvLAC Research Group Leaders Sistema Grupo Sistema GrupLAC Managers in ST&I Investments CT&I Universities Link Analysis Former Students ST&I Organizations Cv Viewer Groups
    • ScienTI Network Information Flow
      • What they are not
        • Technological platforms So in order to be in ScienTI the same technology is needed to every one
        • Single “Big Machine” Approaches As mentioned yesterday by Stefan Gradman
        • Silver bullets
      Some Remarks on the Methodology and Architecture
      • What they are
        • Methodological and Architectural References They offer to ScienTI members reference models to concept and build CRIS
        • Replicable Approaches They can be applied at organizational, funding agency or international networking levels
        • Long Run Support for NIS models They allow the construction of different CRIS views by keeping the perspective of model and best practices references
      Some Remarks on the Methodology and Architecture
    • Did we attend most of stakeholders information needs?
    • ScienTI Brazil – Indicators 1,8 million access a year 19.140 research groups in more than 200 institutions +713.000 100 thousand CVs per year
    • COUNTRY.……………….2002…….2005 Argentina.................................0……35.580 Brasil............................248.000…..590.000 Colombia........................13.500……40.000 Chile.................................2.000……..7.290 Equador...................................0……….430 Mexico.....................................0……11.900 Peru.........................................0……..2.200 Portugal...........................…….0…..…4.100 Venezuela……………………...0……..1.420 TOTAL…………………263.500……692.920 ScienTI CV Numbers (September 2005)
    • Example Using Dynamic Data Marts to yield Indicators for S&T Management Specialized Searches Server OLTP CV Database Primary Information Source Cv System Curriculum Data Mart Secondary Information Source POLICY MAKERS DM CV Curricula
    • Supporting the National Policy on Industry Development Strategic Areas (Brazilian PITCE)
      • Semiconductors
      • 1.238 people working in the area
      • 157 (12,6%) have IP
      • Only 2 researchers have 18% of all IP
      • Pharmacy
      • 2.269 people working in the area
      • 438 (16,7%) have IP
      • 15% have 50% from the total IP in the area
    • Social Network Analysis Primary Information Sources Cv System Group and Curriculum Data Marts Group Systems Dynamic Data marts Social Network Analysis EVALUATORS DM Group Groups Curricula DM CV
    • ScienTI Networking Analysis: Some Results (Brazil)
      • Social Network Analysis (e.g., searching for hubs on a national list of experts)
      • A search on a certain area shown that there are only 3 hubs on a list of the 40 researchers with the majority of P&T registers on their CV
      • The three hubs belong to the same graduate program
      Balancieri, R. 2004.
    • Automatic Semantic Analysis KNOWLEDGE RESEARCHERS Server OLTP CV Database Primary Information Source Cv System Curriculum Data Mart Secondary Information Source Analysis Systems DM CV Curricula
    • Hidden Relations for “Knowledge”
    • Lattes Platform Institutionalization UNIVERSITIES AND R&D INSTITUTIONS
      • Organizational research policies
      • Research evaluation
      • Researcher carrier plan
    • Finding Experts... Firm’s Environment How to make the national competences available to firms for contact and collaboration? www.portalinovacao.info
    • Search for Competences
    • Search for Competences
    • Search for Competences ANALYSIS OF THE EXPERT’S PROFILE
    • Search for Competences
    • Search for Competences SAVING EXPERTS IN “FAVORITES” FOR FUTURE COLABORATION
    • Saving in “Favorites” and Making Contact... Prezado Pesquisador, Estivemos consultando o Portal Inovação e verificamos sua experiência em temas de nosso interesse para uma possível cooperação visando capacitação. Assim, gostaríamos de verificar a possibilidade de realizarmos uma reunião
    • Back to CERIF-ScienTI possibilities…
    • Standards and Interoperability Standard Community of practice 2000-2004
      • Cooperation
        • Each ST&I unit of analysis should be defined as a result of collaboration between the different players
        • The standards have to be constantly updated to attend new trends and needs
        • Interoperability has to be part of the agenda
      http://lmpl.cnpq.br/lmpl/
    • CV Standard CV standard includes subunits ( e.g . bibliographic production) and a XML schema to control format and obligatory fields Identification, Professional address, Academic degree, Knowledge fields; research projects; Professional experiences, idioms; awards Articles; Conference papers; Books and chapters; newspaper articles; other kind of publications Software; products; processes; technical reports; intellectual property; other kind of technical work; Artistic work; PhD/master/undergraduate thesis; other kind of work Short courses; PhD/master/undergrate Committees; peer reviews; participation in event; etc.
    • Research Group Standard Research group standard includes subunits (researcher, students) – by identification fields and also XML schema to control format and obligatory fields Institution; Address; Research leaders; Work repercussion. Identification; research lines; students Identification; advisor; research line Identification; academic degree, work in the group Research areas; keywords; people involved Group partners; kind of partnership; kind of sponsorship
    • Organization Standards Examples
      • Institution standard has a three layer conceptual design:
      • General Model describes modules such as identification, historic, kind of structure, etc.
      • Expanded Model describes codification, classification, and other fields with reference domains (e.g., job classifications); and
      • Client system Model – describes specific fields needed in particular applications
      GENERAL MODEL – BASIC DATA: Mission; historic; foundation date EXPANDED MODEL: Organization structure GENERAL MODEL: Legal authority EXPANDED MODEL: Organization code (kind; entity definer; code; and code description
      • CERIF
        • OrgUnit, Person and Project
      • ScienTI
        • Institution, Curricula and Project
      ScienTI and CERIF Information Basic Entities
    • Entities – Shared View CERIF and ScienTI
      • AcademicTitle
      • Contact
      • Country
      • CV
      • ExpertiseAndSkill
      • ExpertiseAndSkillDescription
      • ExpertiseAndSkillName
      • HonorificTitle
      • Language
      • OrgUnit
      • OrgUnit_Contact
      • OrgUnit_ExpertiseAndSkill
      • OrgUnit_OrgUnit
      • OrgUnitName
      • Person_AcademicTitle
      • Person_Contact
      • Person_CV
      • Person_ExpertiseAndSkill
      • Person_Language
      Fields present in both CERIF AND ScienTI models
      • Project_Person
      • Project_ResultPatent
      • Project_ResultProduct
      • Project_ResultPublication
      • ProjectAbstract
      • ProjectKeywords
      • ProjectTitle
      • ProjectStatus
      Entities – Shared View CERIF and ScienTI
      • Person_Nationality
      • Person_OrgUnit
      • Person_Person
      • Person_ResultProduct
      • Person_ResultPublication
      • PersonResearchInterest
      • Project_Classification
      • Project_FundingProgramme
      • Project_OrgUnit
      Fields present in both CERIF AND ScienTI models
      • Different World Views
        • Information modeling drivers
          • ScienTI models (and architecture) were driven by the need of gathering national information for funding management
          • CERIF model was driven as a reference model (recommendation) without specific CRIS project
      CERIF And ScienTI Models Differences
        • Information redundancy approaches
          • CERIF is a conceptual model based on normalized non redundant data
          • In ScienTI the assumption of gathering information as close as possible to the owner and as a distributed system
            • Then the model is composed by units with subunits (such as publication within CVs) and individual fulfilling (such as authors keywords that lead individual vectors different from the article vector)
            • Redundancy is treated by capturing and treating 3 information formats:
              • Relational + XML at the researcher desktop;
              • Relational and multidimensional at the server
      • Areas of cooperation
        • ScienTI National Translations
          • CERIF flexible classification schemas
          • CERIF idiom translation approach
        • CERIF concerns about incentives
          • ScienTI systems were designed to gather information but also to offer services to the users (personal cv-website; legacy import systems; knowledge-based profiles, etc.).
          • These incentives have been proven even when facing government policy changes
            • starting in 2003 the new Brazilian CNPq authorities disagree on the initial Lattes assumption that new knowledge can be discovered from funding information)
      CERIF And ScienTI Models Opportunities
      • Regarding Interoperability
        • Both CERIF and ScienTI models have been proved as open models that can foster connectivity, information sharing, and compatibility in CRIS.
      • Mutual Strengths
        • CERIF has a mature and normalized model that eliminates redundancy and may play the role of design pattern for future ScienTI developments (particularly at the server level);
        • ScienTI has reached a wide public and uses strategies that proved to successful to make the database grow and remain constantly updated
      Some Conclusions
      • Future
        • A collaboration between CERIF and ScienTI could bring significant contributions to both projects an to all players in the correspondent NIS;
        • Portugal is a participant of both initiatives and may contribute to accelerate such collaboration;
        • Most importantly European and Latin American NIS would benefit from information sharing and cooperation
      Some Conclusions
    • Possible Future CERIF and Scienti info projects
    • Roberto C. S. Pacheco EGC/UFSC INE/UFSC Instituto Stela - Brasil Toward CERIF-ScienTI Cooperation and Interoperability The ScienTI and CERIF Models: a Compatibility Analysis Towards Interoperability Among European and Latin-American ST&I Information Networks euroCRIS 2006 Bergen, Norway - May 12th 2006 SAS Hotel Bryggen. Lecture Hall Vinicius Medina Kern; José Salm Jr. Instituto Stela - Brasil Abel Laerte Packer; Renato Murasaki BIREME/PAHO - Brasil Luis Amaral; Leonel Duarte dos Santos Universidade do Minho - Portugal Alberto Cabezas Burlemore CONICYT - Chile [email_address] [email_address] Thank you!! MUITO OBRIGADO!