Knowledge Engineering, Electronic Government and the applications to Scientometrics


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Presentation at 2nd International Meeting on Science, Technology and Innovation Indicators, organized by KAWAX, in Santiago - Chile (17 and january, Chile).

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  • Knowledge Engineering, Electronic Government and the applications to Scientometrics

    1. 1. Roberto C. S. Pacheco Vice Coordinator Graduate Program on Knowledge Engineering and Management Universidade Federal de Santa Catarina - Brazil Instituto Stela – Brazil – Research Leader Knowledge Engineering, Electronic Government and the applications to Scientometrics II SEMINARIO INTERNACIONAL SOBRE INDICADORES DE CIENCIA, TECNOLOGIA E INNOVACIÓN Santiago - Chile, 17 enero 2006 Sheraton Santiago Hotel.
    2. 2. <ul><li>The Bibliometrics Universe </li></ul><ul><ul><li>Multiple Information Sources: libraries, funding agencies, R&D organizations </li></ul></ul><ul><ul><li>Challenges ( to bibliometrics, to e-government and to Knowledge Engineering ) </li></ul></ul><ul><ul><li>The National Innovation System Players ( and their needs ) </li></ul></ul><ul><li>E-government in ST&I </li></ul><ul><ul><li>IT professional background </li></ul></ul><ul><ul><li>Information Modeling </li></ul></ul><ul><ul><li>Methodology and Technological Architecture </li></ul></ul><ul><ul><li>Connecting Information to Strategic Needs </li></ul></ul><ul><li>Knowledge Engineering </li></ul><ul><ul><li>Web semantics and ontology </li></ul></ul><ul><ul><li>Business Intelligence </li></ul></ul><ul><ul><li>Social Network analysis </li></ul></ul><ul><li>Cases </li></ul><ul><ul><li>Lattes Platform (Brazil) </li></ul></ul><ul><ul><li>ScienTI Network (Latin American Countries and Portugal) </li></ul></ul><ul><ul><li>Innovation Portal (Brazil) </li></ul></ul><ul><li>Conclusions </li></ul>AGENDA
    3. 3. How the source of ST&I information have been formed?? 70-80’s 80-90’s Paper Forms Electronic Forms Relational DB Full Texts and Bibliometric DB <ul><li>Multiple source of compatible information </li></ul><ul><li>Researchers inform the same data at the levels of: </li></ul><ul><ul><li>Funding raising </li></ul></ul><ul><ul><li>Publication </li></ul></ul><ul><ul><li>Institutional relationship </li></ul></ul>FUNDING PUBLISHING
    4. 4. How the source of ST&I information have been formed?? <ul><li>Main problems </li></ul><ul><li>Multiple sources of information </li></ul><ul><li>Lack of standards </li></ul><ul><li>Multiple efforts in S&T communities </li></ul><ul><li>Waste of public funds </li></ul>ST&I Indicators Homogeneous sources Other Sources (ex: Web) Textual Sources Relational Data Bases Questionnaires, Surveys Heterogeneous sources
    5. 5. Other Sources Knowledge Engineering can help with legacy and with new eGov Data Indicators, Studies, Analysis…for Decision Making in all ST&I levels Textual Sources Relational Data Bases Homogenous Sources Questionnaires, Surveys Heterogenous Sources <ul><li>How to deal with the existent sources ? </li></ul><ul><li>How are the trends in information gathering? </li></ul><ul><li>How Knowledge Engineering is useful in both cases? </li></ul>New Opportunities ICT y Knowledge Management Decision Making, process integration, knowledge managing… ICT y E-government eGov architectures, public access, user involvement (and requirements)… ICT New Technologies Data marts, knowledge extraction ( e.g. , data mining) textual retrieval, textual generation… New (and not so new) Methodologies (empowered by ICT) Social Network Analysis, Link Analysis, Trend Analysis…
    6. 6. <ul><li>In Bibliometrics </li></ul><ul><ul><li>Create methodologies, methods and tools </li></ul></ul><ul><ul><li>Support all ST&I players (from students to policy makers) </li></ul></ul><ul><ul><li>Deal with large amount of data from different sources </li></ul></ul><ul><li>In E-government </li></ul><ul><ul><li>Make information gathering a rational process </li></ul></ul><ul><ul><li>Establish (and respect) ST&I information standards </li></ul></ul><ul><ul><li>Cope with all ST&I players needs (convince sponsors that they are part of an information network but they are not their center) </li></ul></ul><ul><ul><li>Make ST&I information sources interoperable </li></ul></ul><ul><li>In Knowledge Engineering </li></ul><ul><ul><li>Modeling ST&I information as a knowledge base </li></ul></ul><ul><ul><li>Discover hidden (and useful) patterns </li></ul></ul><ul><ul><li>Improve ST&I by adding value to the decision processes </li></ul></ul>Some of the Challenges
    7. 7. First Step: To Understand 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. <ul><li>ICT has impact on all players and sources that matter to ST&I Indicators </li></ul><ul><ul><li>Government </li></ul></ul><ul><ul><li>S&T Community </li></ul></ul><ul><ul><li>Universities and Research Institutes </li></ul></ul><ul><ul><li>Industry </li></ul></ul><ul><ul><li>Economy </li></ul></ul><ul><ul><li>Legislation </li></ul></ul><ul><ul><li>Intellectual Property </li></ul></ul><ul><ul><li>Commerce </li></ul></ul><ul><ul><li>Etc… </li></ul></ul>
    8. 8. How did ICTs develop inside organizations? e-Gov IT Professional Background
    9. 9. 90’s ICT brings strategic support ICT as an instrument to knowledge era 94-hoje 60’s - 70’s 80’s Data Marts DSS GIS EIS Internet, Intranet, Extranet Knowledge Extraction Interoperability Communities of Practice Electronic Government ICT Evolution Regarding the Organizations Information Systems <ul><li>ICT history and its impact on the vision its professionals have </li></ul><ul><ul><li>ICT evolved in a bottom up manner. It begun as supporting operational issues at the organizations. </li></ul></ul><ul><ul><li>Only in the last decades ICT professionals have faced the problem of providing strategic information. </li></ul></ul><ul><ul><li>ST&I information platforms can suffer the same problems when conceived by pure ICT people: the information architecture can be designed to support only operational issues. Scientometrics is affected latter by the lack of consistent data. </li></ul></ul>ICT in the operational basis ICT allows tactic support OLTP Databases Data Warehouse Web New Trends for ICT (knowledge society)
    10. 10. Web Interoperability International Standards for S&T Information National Architectures for S&T Information <ul><li>Current Characteristics </li></ul><ul><li>ICT going to the top of all organizations </li></ul><ul><li>ICT in all public agencies </li></ul><ul><li>Highly connected (and demanding) society </li></ul><ul><li>More and More Interoperability </li></ul><ul><li>More and More Standards </li></ul><ul><li>A need for a broader view of the role of ICT in public administration </li></ul>A New Scene for TIC In Public Organizations
    11. 11. Fundamental Questions to ICT Who are the players involved with ST&I ? How each one of these players interact (use and create information) ? Which ST&I processes should be considered ?
    12. 12. ICT is being Applied in all S&T Processes INVESTIMENTS KNOWLEDGE CREATION MANAGEMENT TRANSACTIONAL PROCESSES Is to meet all processes and all ST&I players information needs In the outputs of a national ST&I system In the inputs of a national ST&I system In the processes of a national ST&I system ICT Challenge
    13. 13. Processes and Players: ST&I Knowledge Support, Production, Planning and Benefit Researchers Students Alumni Grad. coord. Managers Professionals Entrepreneurs Technicians Faculty Staff Players Knowledge <ul><li>IMPORTANT: The information flow is not linear. Together ST&I players form a complex network of interaction. As a consequence, ST&I information is created, transferred and managed on several levels, views from different repositories. </li></ul>Managers Multipliers Generation supporters Beneficiaries Producers
    14. 14. Textual Databases Operational Databases Rules Managers Professionals Students New Actors Researchers Web Sites, Portals ST&I Information Architecture Goal PLAYERS PROCESSES INFORMATION SOURCES VIRTUAL COMMUNITIES <ul><li>IMPORTANT: The most important issue in designing a ST&I information platform is how every player will be attended. Although the sponsor (funding agencies) necessities should be treated first, the platform must aim to transform ST&I players from providers to beneficiaries . </li></ul>
    15. 15. Methodology Pacheco, 2003 <ul><li>METHODOLOGY: Perceiving design, development, use and revision as a continuous process is the key to make national platforms constantly growing. </li></ul>PROJECT PHASE Requirements Planning 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
    16. 16. Unit Analysis Definition and Appropriate Information Gathering Instrument <ul><li>ST&I Contents in ST&I Curriculum </li></ul><ul><ul><li>Identification </li></ul></ul><ul><ul><li>Addresses </li></ul></ul><ul><ul><li>Level of Education </li></ul></ul><ul><ul><li>Professional experience </li></ul></ul><ul><ul><li>Knowledge fields </li></ul></ul><ul><ul><li>Idioms </li></ul></ul><ul><ul><li>Prizes and Titles </li></ul></ul><ul><ul><li>Projects </li></ul></ul><ul><ul><li>Bibliographic production </li></ul></ul><ul><ul><ul><li>Articles, Books, Events, other </li></ul></ul></ul><ul><ul><li>Technical production </li></ul></ul><ul><ul><ul><li>patents and not registered </li></ul></ul></ul><ul><ul><li>Supervisions </li></ul></ul><ul><ul><li>Complementary information </li></ul></ul><ul><li>Information Resources </li></ul><ul><ul><li>Homepage automatic </li></ul></ul><ul><ul><li>CV Indicators </li></ul></ul><ul><ul><li>Export to several formats </li></ul></ul><ul><ul><li>Easy error verification </li></ul></ul><ul><li>Information Units should be designed considering international standards but also the needs of all players. In the case of CV, for instance, besides evaluation and funding a curricula must provide data to build competence and experience databases. </li></ul><ul><li>Information Systems. The instruments to update information must be friendly used and most important they must make the user’s activity easier (e.g., make their professional profile public). </li></ul>
    17. 17. Standards and Interoperability Standard Community of practice 2000-2004 <ul><li>Cooperation </li></ul><ul><ul><li>Each ST&I unit of analysis should be defined as a result of collaboration between the different players </li></ul></ul><ul><ul><li>The standards have to be constantly updated to attend new trends and needs </li></ul></ul><ul><ul><li>Interoperability has to be part of the agenda </li></ul></ul>
    18. 18. Standards for ST&I <ul><li>C ommon </li></ul><ul><li>E uropean </li></ul><ul><li>R esearch </li></ul><ul><li>I nformation </li></ul><ul><li>F ormat </li></ul>Dublin Core SWRC – Semantic Web Research Community persons, organizations, publications, projects and topics <ul><li>Ultimate goal: ST&I web semantics </li></ul><ul><li>Standards and interoperability can lead to a point where making knowledge interchange is feasible </li></ul><ul><li>Scientometrics can benefit from the facility of making different information sources interchangeable and complementary. </li></ul>
    19. 19. DW Investments Demography Former Students Searches Technological Components Information Architecture. The Methodology leads to a technological architecture composed by layers. In the basis are the primary information sources and the standards. It is followed by the information systems that update these sources, by the secondary information sources (data warehouse and indexes), by search systems and sites. On the top are the knowledge systems that allow the information exploration. System: Groups GrupLAC CvDeGois CvLattes CvLAC DM Cv DM Gr DM Inst DM Proj CVs Groups Institutions Projects Primary information sources Portals
    20. 20. Is the Information useful at strategic levels?
    21. 21. Dynamic Data Marts : Indicators for S&T Management Specialized Searches Primary Information Source Cv System Curriculum Data Mart Secondary Information Source Information Gathering System Information Search Information Search and its strategic use. By indexing and searching the primary sources an analyst can discover hidden patterns on the data. DM CV Curricula
    22. 22. Finding National Competences from Curricula <ul><ul><li>Name </li></ul></ul><ul><ul><li>Profile </li></ul></ul><ul><ul><ul><li>Description (Free text informed by users in the CV short version) ; </li></ul></ul></ul><ul><ul><ul><li>Keywords (keyword profile informed in the CV short version) ; </li></ul></ul></ul><ul><ul><li>Professional Experiences: </li></ul></ul><ul><ul><ul><li>Location (Institution/Unit/Sub-unit) </li></ul></ul></ul><ul><ul><ul><li>Kind of Activity (Taxonomy) </li></ul></ul></ul><ul><ul><ul><li>Activity description (free text) </li></ul></ul></ul><ul><ul><ul><li>Activity keywords </li></ul></ul></ul><ul><ul><li>Projects </li></ul></ul><ul><ul><ul><li>Project Title </li></ul></ul></ul><ul><ul><ul><li>Description </li></ul></ul></ul><ul><ul><ul><li>Keywords </li></ul></ul></ul><ul><ul><li>Technical and Scientific Production </li></ul></ul><ul><ul><ul><li>Title </li></ul></ul></ul><ul><ul><ul><li>Keywords </li></ul></ul></ul><ul><ul><ul><li>Additional Information </li></ul></ul></ul><ul><ul><ul><li>Coauthor’s name </li></ul></ul></ul><ul><ul><li>Academic Degree </li></ul></ul><ul><ul><ul><li>Institution </li></ul></ul></ul><ul><ul><ul><li>Course Name </li></ul></ul></ul><ul><ul><ul><li>Title of the Thesis </li></ul></ul></ul><ul><ul><ul><li>Supervisor’s name </li></ul></ul></ul><ul><ul><ul><li>Keywords </li></ul></ul></ul>Search Content ( Which Knowledge, Who has it and Where are the experts ) : Where to Search. The primary information is transformed and loaded into secondary sources. All sub-units can now be divided into subfields of searching. As a consequence an analyst cab find competences by crossing several criteria (e.g., find experts with project experience in “nanotechnology” who have also taught this subject in graduate courses ).
    23. 23. <ul><ul><li>Identification </li></ul></ul><ul><ul><ul><li>by Gender </li></ul></ul></ul><ul><ul><ul><li>by Age </li></ul></ul></ul><ul><ul><li>Address </li></ul></ul><ul><ul><ul><li>by Institution </li></ul></ul></ul><ul><ul><ul><li>by State and Country Region </li></ul></ul></ul><ul><ul><li>Academic Degree </li></ul></ul><ul><ul><ul><li>by Institution </li></ul></ul></ul><ul><ul><ul><li>by State or Region </li></ul></ul></ul><ul><ul><ul><li>by Course field </li></ul></ul></ul><ul><ul><ul><li>by Degree </li></ul></ul></ul><ul><ul><ul><li>by Period </li></ul></ul></ul><ul><ul><li>Technical and Scientific Production: </li></ul></ul><ul><ul><ul><li>by Type, subtype and classification </li></ul></ul></ul><ul><ul><ul><li>by Period </li></ul></ul></ul><ul><ul><ul><li>by Supervisions (degree and courses) </li></ul></ul></ul>Searching and Retrieving (How to Query the Search) <ul><ul><li>Professional Experience </li></ul></ul><ul><ul><ul><li>by Institution/Unit/Subunit </li></ul></ul></ul><ul><ul><ul><li>by Kind of Employment Relationship </li></ul></ul></ul><ul><ul><ul><li>by Job position </li></ul></ul></ul><ul><ul><ul><li>by Period </li></ul></ul></ul><ul><ul><ul><li>by Kind of Activity (Taxonomy) </li></ul></ul></ul><ul><ul><li>Scientific Context: </li></ul></ul><ul><ul><ul><li>By Knowledge Field </li></ul></ul></ul><ul><ul><ul><ul><li>Of the Production </li></ul></ul></ul></ul><ul><ul><ul><ul><li>Of the Academic Degree </li></ul></ul></ul></ul><ul><ul><ul><ul><li>Of the Knowledge Field </li></ul></ul></ul></ul><ul><ul><ul><li>By Application sector </li></ul></ul></ul><ul><ul><ul><ul><li>Of the Production </li></ul></ul></ul></ul><ul><ul><ul><ul><li>Of the Academic Degree </li></ul></ul></ul></ul>Query Criteria : (Knowledge classification, Location, Time and Contextualization ) : Where to Search. The same search can also be focused in particular criteria (e.g., consider only experts working in the South ).
    24. 24. Example: Supporting the National Policy on Industry Development <ul><li>Semiconductors </li></ul><ul><li>1.238 people working in the area </li></ul><ul><li>157 (12,6%) have IP </li></ul><ul><li>Only 2 researchers have 18% of all IP </li></ul><ul><li>Pharmacy </li></ul><ul><li>2.269 people working in the area </li></ul><ul><li>438 (16,7%) have IP </li></ul><ul><li>15% have 50% from the total IP in the area </li></ul>Strategic use of information. Textual searches can support strategic decisions. In the following there is a national search in Brazil taken in march 2004, when the government had just launched the National Industrial Policy making semiconductors and pharmacy two of the priorities. The search shows the intellectual propriety concentration.
    25. 25. Investments in ST&I Public Funding Analysis Indicators Portal Primary Information Source Project Form Funding Data Mart Secondary Information Source Information Gathering System Information Search Information Analysis and its strategic use. By transforming the primary information into cubes the architecture brings the analyst a large amount of possibilities of cross indicators. An relevant example is related to how to show public investments in ST&I… DM Projects Projects
    26. 26. Public Funding Analysis Public Funding Portal. A data mart on the investments dimensions allows the public to know the different lines of investments offered by to the S&T community (scholarships in the country or abroad, quality programs, support to editing, funds to research projects, funding to scientific events, and special areas (ex: “Fundos Setoriais”))
    27. 27. Public Funding Analysis Information Analysis. Each area of investment can be analyzed by several criteria (e.g., total of investments classified by period, knowledge area supported, part of the country, etc).
    28. 28. Public Funding Analysis Information Analysis. The total amount of investments in energy in 2003, classified by the kind scholarship.
    29. 29. Public Funding Analysis Information Analysis. It is possible to verify who was funded and how the investments helped to increase the curricula of the beneficiary.
    30. 30. Social Network Analysis Primary Information Sources Cv System Group and Curriculum Data Marts Group Systems Dynamic Data marts Social Network Analysis Secondary Information Sources Knowledge Systems Network Analysis. Another possibility is to use the secondary information source to analyze the connectivity among the innovation players. DM Group Groups Curricula DM CV
    31. 31. Alumni analysis (example: geographic dispersion) Network Analysis. Where (country region) are working former students of a certain graduate course? Who are these students? What they are doing currently? These are some of the examples that networking analysis provides (once the e-Gov architecture is available).
    32. 32. Alumni analysis (example: employer / place of work) Networking Analysis. In which institutions are working now the former students of a certain university? This is also provided by the networking analysis.
    33. 33. Researcher: collaboration networks Network Analysis. Even a single curriculum provides information about the network of collaboration. Each co-author can be linked to the common productions.
    34. 34. Social Network Studies <ul><li>shattered world </li></ul><ul><li>Several Networking Analysis </li></ul><ul><li>Once the National ST&I Information Platform is achieved, it is possible to study social networks taking into account several criteria. For instance, only based on the curricula database one can form the following the networks: </li></ul><ul><ul><li>by coauthorship (in all types of production) although it does not provide co-citation analysis </li></ul></ul><ul><ul><li>by copublishing (same journal or same event) </li></ul></ul><ul><ul><li>by fellowship (considering affiliation to depts./Institution or courses at the same period) </li></ul></ul><ul><ul><li>by adviser process (in each level of education) </li></ul></ul><ul><ul><li>by project team </li></ul></ul><ul><ul><li>by personal profile (e.g., age, gender, etc.) </li></ul></ul><ul><ul><li>by knowledge activity (from several different profiles, including knowledge experience) </li></ul></ul><ul><ul><li>by acknowledgement (e.g., coparticipation in events, examinations, etc) </li></ul></ul><ul><ul><li>by neighborhood (city of address) </li></ul></ul>parochial world small world Balancieri, R. 2004.
    35. 35. Example: Hub detection and display <ul><li>Example – ScienTI network, using the 32 most productive Brazilian researchers from one area </li></ul>Degree 7 Degree 1 Degree 8 <ul><li>Social Network Analysis (e.g., searching for hubs on a national list of experts) </li></ul><ul><li>real case: a search on a certain area shown that there are only 3 hubs on a list of the 40 most researchers with the majority of P&T registers on their CV </li></ul><ul><li>The three hubs belong to the same graduate program </li></ul>Balancieri, R. 2004.
    36. 36. Hidden Relationships for the term “Plataforma Lattes” Plataforma Lattes Automatic Semantic Analysis Networking Analysis. Another possibility is to reveal hidden connection among knowledge terms freely informed by the National S&T platform. Words used by the S&T community to describe their professional activity form a hidden web of concepts that can be revealed by means of network analysis. The example shows how the expression “Platforma Lattes’” is conceived by the Brazilia S&T community regarding other terms. Search
    37. 37. Hidden Relations for “Knowledge” Mapping knowledge. A search by a single term shows how the knowledge has been developed in related areas. This example detaches the term “knowledge” in the Brazilian national innovation systems (considering the 600.000 curricula). It can be seen four nucleus of studies: pedagogy of knowledge, philosophy of knowledge, knowledge management and artificial intelligence.
    38. 38. Finding hidden information units. Stela Institute has developed the tool called “ISKMM” that allows to dig into the information sources (from several formats) and automatically discover unit analysis. ISKMM – Automatic Entity Discovery GONÇALVES, et. al. Mining Knowledge from Textual Databases: an Approach Using Ontology-Based Context Vectors. In: The IASTED International Conference on Artificial Intelligence and Applications. Innsbruck.: AIA, 2005. v. I, p. 66-71.
    39. 39. Information networking. ISKMM also allows to visualize the concept connections between information units (e.g., the link among people and among people and knowledge). ISKMM – Automatic Unit Link Analysis
    40. 40. Ontology that make possible elucidate relationships Rule Configuration by the user with dynamic reflection over the decision matrix ISBI - Business Intelligence (that anyone can apply) SELL, D.; et. al . Interactive Composition of WSMO-based Semantic Web Services in IRS-III. In: FIRST AKT WORKSHOP ON SEMANTIC WEB SERVICES - AKTSWS04, 2004, Milton Keynes, UK. Proceedings of AKT Workshop on Semantic Web services. Milton Keynes, UK: KMI, 2004. v. 122, p. 1-8.
    41. 41. <ul><li> </li></ul>CASE: e-Government to Map ST&I Information Lattes Platform Since 1999 CNPq - National Council of Scientific and Technological Development Lattes: a National ST&I Information Platform. From 1998 up to 2004 Brazil has developed a National ST&I Platform based on the methodology and technological components described before. Launched in September 1999, Lattes Platform has reached all S&T agencies, universities, institutes, and the majority of the individuals and groups working in the area. The platform became the most rich source of information of individual and collective competences in S&T in Brazil. It has helped more than 40 institutions to build their organizational competences database and it is a valuable asset to planning and decision making. In 2004 Lattes Platform was chosen the most important e-Gov project in Brazil in the category of government-citizen initiative.
    42. 42. Electronic government service composed by more than 140 elements among standards, information systems, databases, portals and knowledge systems in Science, Technology and Innovation. <ul><li>670 thousands curricula </li></ul><ul><li>5 thousands of updating per day (individually done by experts, students, professionals, etc.) </li></ul><ul><li>More than 300 new CVs per day </li></ul><ul><li>19,5 thousands research groups </li></ul><ul><li>335 R&D institutions </li></ul><ul><li>14 thousands accesses per day (from 90 countries) </li></ul><ul><li>More than 1 thousand Education Institutions </li></ul><ul><ul><li>62% of all undergraduate professors with personal cvs. </li></ul></ul><ul><li>More than 500 public organizations </li></ul><ul><li>More than 1 thousand firms </li></ul><ul><ul><li>registering partnerships among R&D groups and firms </li></ul></ul>Lattes Platform
    43. 43. Case 2: International Networking in ST&I ScienTI Network - International Network on Information Sources and Knowledge for the Management of Science, Technology and Innovation International View. In 2001 an agreement between CNPq and PAHO allowed the translation of Lattes systems into Spanish and its try version in 5 Latin American Countries. In the end of 2001 Portugal joined the cooperation. In December 2002 a meeting in Florianópolis, Brazil created the ScienTI Network with eleven countries. Since then we’ve been working on building up national platforms and make them connected by means of web services.
    44. 44. ScienTI Network in Numbers International Web services International Cooperation. At this moment ScienTI has been mostly the set of national actions in each country consisting of establishing the ST&I information platforms. The next step is to make this information connected by means of web services and provide services on a multi-national level. Source: ScienTI IV Meeting Salvador BA, September, 2005
    45. 45. ScienTI makes it possible to create new scientometric indicators and most importantly new approaches to study national innovation systems National ST&I Information Platforms Brings a New Scenario to Scientometrics ScienTI Indicators. One of the new possibilities brought by ScienTI Network is to provide scientometric methods with new data, standardized an coming from several countries. In the following we present some of these possibilities, consisting on a pilot study conducted by PAHO and RICYT.
    46. 46. Example: Researchers in Health By Gender and Age RICYT and PAHO Studies. Based on the national curricula databases from Brazil and Colombia, RICYT ( ) and PAHO ( ) have developed a new set of indicators. The following is a comparison between the gender distribution in both countries regarding researchers in health. There is a hidden phenomena of the unbalanced interest in Brazil by women.
    47. 47. Example: Researcher’s Knowledge Domain Flow RICYT and PAHO Studies. Another example is the study of how many experts have been studied (F – stands for “Formación” or Academic Degree), acted (A – stands for “Actuación” or Professional Activity) and produced (P – stands for “Producción” or Intellectual production such as papers, reports, software, etc). There is a similar behavior indicating that the great majority remains connected to their education area (either acting or publishing in health)
    48. 48. Roberto C. S. Pacheco INSTITUTO STELA - Research Leader A National Portal for Innovation Fostering Cooperation. In 2004 the Brazilian Ministry of Science and Technology established a goal of building a web space for making the national competence in S&T available to industry and firms interested in innovation projects. In 2005 we developed and launched the Innovation Portal. It includes Lattes Platform as a competence source for firms, the firms’ demands in innovation and a whole set of systems from a cooperation space up to knowledge systems about the partnership. CASE 3: e-Government for Cooperation
    49. 49. <ul><li>2. How to make such competences available to firms for contact and collaboration? </li></ul>? Main Issues in Building such a Portal 1. How to capture the national knowledge in ST&I in a systematic and continuous way? 3. How to know the firms demands on ST&I so the collaboration can start from both sides? 4. How far the current technologies and methodologies can lead a cooperation project such “Portal Inovação”?
    50. 50. <ul><li>The Innovation Portal is an electronic governmental service with systems specially designed to users related to the national innovation chain. </li></ul><ul><li>As a Portal, this environment supports processes of location, contact and correspondence between firms and technical-scientific community. </li></ul>What is the Innovation Portal? Systems and resources accessed via Web E-Governmental Architecture
    51. 51. infrastructure Currículos Building up the Information Sources... Offering Firms Experiences in cooperation Personal Training Technological Support Import Replacement Support to Exportation COMPETENCES OFFERTS Experts w/ Cv Currícula Offers OPPORTUNITIES FOR COOPERATION Demand Expert’s Environment Firm’s Environment Groups Space for Interaction
    52. 52. Using and Amplifying the Information Source COMPETENCE DIRECTORY Firm’s Environment OPPORTUNITIES Expert’s Environment PROPOSAL FOR COOPERATION RESPONSES FAVORITS COMPETENCES OPPORTUNITIES COOPERATION Proposes Responses Space for Interaction ICTI Environment Support Organizations Environment Search for Competencies Search for Opportunities
    53. 53. Firm’s Environment <ul><li>Use Indicators (Available sources, users) </li></ul><ul><li>Firm’s System (Identification and Demands) </li></ul><ul><li>Search for Competences (Favorites – Bookmarked experts) (Experts, Groups and Firms) </li></ul><ul><li>Search for Opportunities (Favorites – Bookmarked demands) (Firm’s Demands) </li></ul><ul><li>Interaction (Proposes and Answers) </li></ul><ul><li>Strategic Information (Competitive Intelligence) </li></ul>What does the Portal Offer to Firms? Firm’s Environment. The Portal has private environments for each innovation player. Firms can access their own data (profile, demands and technological offers), can search and save (bookmark) competences from experts, research groups and other firms, and can also use the cooperation environment to send (or receive) messages to experts or other firms.
    54. 54. Finding Experts... Firm’s Environment 2. How to make the national competences available to firms for contact and collaboration?
    55. 55. Searching for Competences – search alternatives Searching competences. Firms’ representative (as well as the general public) can find competences searching for terms in the national curricula database. The search results present the experts (classified by the match between profile and search interest) and the 10 terms more frequent on those curricula. R&D groups and firms are also available. A new search is available both as a result from choosing directly one or more resultant terms or starting a new search by one of the 3 most important terms in each expert’s cv.
    56. 56. Searching for Competences – Knowledge Distribution Searching competences. The user can also specialize its search according to education level, region or knowledge field of the experts. With this feature a firm can concentrate, for instance, only in competences within a certain country region. Indirectly the search also provides an interesting indicator to decision maker: country spatial distribution of knowledge.
    57. 57. Searching for Competences – Profile Analysis Profile Analysis. Each curricula, R&D group and firm technological portfolio is indexed by the methodology of context vectors. This allows the user to analyze the knowledge profile of each curricula (group or firm portfolio), based on the frequency of the terms either in title or as keyword for papers, reports, software, and more than 40 other kinds of productions present on the expert’s cv. ANALYSIS OF THE EXPERT’S PROFILE
    58. 58. Searching for Competences – Résumés Analysis Automatic Résumés. The user can also verify a text consisting of a résumé of the entire curriculum. The résumé is automatically created by a specialized knowledge system and allows the interested to check the most important aspects to firms cooperation (according to previous requirement mentioned by firms’ representatives at the project pilot phase). A chosen expert can be saved (bookmarked) as a favorite to cooperation…
    59. 59. Searching for Competences: Bookmarking experts SAVING EXPERTS IN “FAVORITES” FOR FUTURE COLABORATION
    60. 60. Searching for Competences: Bookmarking experts
    61. 61. Bookmarking: Saving in “Favorites” and Making Contact... Cooperation Proposals. Firms and experts can exchange messages whenever a possible cooperation can be established either because the firm things the expert fulfill a required profile or because the expert is interested in the firm’s demands for technical cooperation. Privacy policy. Besides the usual policy of restricting access to personal e-mails, the Portal allows that firms and experts can opt between identifying yourselves or sending the message as anonymous until they want. 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
    62. 62. <ul><li>Knowledge Systems </li></ul><ul><li>from the curricula and from R&D group data these systems extract information useful to the firm analyze its interaction with S&T community. </li></ul>Strategic Information to Firms
    63. 63. 3. How to know the firms demands on ST&I so the collaboration can start from both sides? Firm’s System (Demands) Firm’s Environment
    64. 64. Firm’s Environment Firm’s System (Demands) Experiences in Cooperation Personal Training Technological Support Importações substituíveis Support for Exportation
    65. 65. Search for Opportunities
    66. 66. A New Set of Scientometric Indicators?? Online ST&I Distributions. Since the platform is updated on daily basis, it is easy to make the secondary sources (data marts) present distributions of experts, firms or research group by country region or state. The same approach can be further specialized up to highly detailed analyses (considering, for instance, experts profile or historic distributions).
    67. 67. A New Set of Scientometric Indicators?? New parameters of decision. Cooperation web environments bring new parameters to the classical methods of ST&I management. Factors such as the portal accesses can measure the nature of the interested of ST&I communities. Features such as bookmarking brings a hidden interest factor not available before (e.g., who are the experts more likely to be contacted by firms?). Another aspect that has been considered is what would be the effect of having these bookmarks available at the funding decision making process (e.g., how is the bookmarking level of each expert). Access to the National Portals Bookmarked experts Favorites in searches for competences
    68. 68. A New Set of Scientometric Indicators?? Competitive intelligence. National ST&I platforms carry strategic information to firms. An example is the profile of researchers working in R&D groups that maintain projects with the company. Another example is the knowledge of what (and where) former workers are working. Such information is available at the private level of Innovation Portal (i.e., restricted to the user’s firm and accessible only for users properly logged in).
    69. 69. <ul><li>In 2006 Innovation Portal has Steering Committee formed by all public agencies related to the issue of innovation </li></ul><ul><li>The project is already part of a major national effort to articulate information on the Brazilian Innovation System </li></ul><ul><li>Several information projects are being taken into account in the interoperability process </li></ul>Interoperability Industry and Commerce Ministry Environmental Ministry <ul><li>Other Sources being tested: </li></ul><ul><ul><li>SciELO, INMETRO, University Information Sources, etc. </li></ul></ul><ul><li>Innovation Law </li></ul>RedeComp <ul><li>PITCE National Industrial Policy </li></ul>
    70. 70. Conclusions <ul><li>Applications to Knowledge Engineering and e-Gov </li></ul><ul><ul><li>There are new opportunities to knowledge engineering as well as to electronic government in ST&I information management </li></ul></ul><ul><li>Effective information workflow must be the priority. </li></ul><ul><ul><li>e-Gov projects should consider the rationality of information gathering by promoting interoperability among sources and by adopting data standards </li></ul></ul><ul><li>Successful e-Gov Platforms do not belong to their sponsors </li></ul><ul><ul><li>the “price” of success is to say: “we build an information platform that does not belong to us…” (in deed, to be successful it should have designed to belong to all ST&I community of players). </li></ul></ul><ul><li>New information management approaches must deal with the existent sources </li></ul><ul><ul><li>Knowledge engineering can help to deal with legacy data as well as support new information modeling </li></ul></ul>
    71. 71. Conclusions <ul><li>Knowledge Engineering and Scientometrics </li></ul><ul><ul><li>Several Knowledge engineering areas can help Scientometric Analysis (e.g., text generation, modeling - particularly ontology, knowledge discovery and representation, business intelligence) </li></ul></ul><ul><li>There is a brand new set of ST&I indicators available </li></ul><ul><ul><li>e-Gov projects (with knowledge engineering oriented architectures) and the Web bring to Scientometrics a whole new set of indicators. Web presence, networking and flexible information combination (based on OLAP analysis) bring a new set of opportunities to Scientometrics. </li></ul></ul><ul><li>Interoperability is the word of order </li></ul><ul><ul><li>Making compatible information projects communicate to each other is the essential goal to public services. </li></ul></ul>
    72. 72. <ul><ul><li>“ (…) when the data become more available and the means to assemble and manipulate them become more sophisticated, there is a tendency among evaluators to concentrate on the data (…) rather than on the constructs.” </li></ul></ul><ul><ul><li>Eliezer Geisler, 2000. </li></ul></ul>A Final Alert to Technology Oriented Solutions...
    73. 73. Careful with the Passion for Technology
    74. 74. Roberto C. S. Pacheco Vice Coordinator Graduate Program on Knowledge Engineering and Management Universidade Federal de Santa Catarina - Brazil Instituto Stela - Brazil Research Leader Knowledge Engineering, Electronic Government and the applications to Scientometrics II SEMINARIO INTERNACIONAL SOBRE INDICADORES DE CIENCIA, TECNOLOGIA E INNOVACIÓN Santiago - Chile, 17 enero 2006 Sheraton Santiago Hotel. MUITO OBRIGADO! [email_address] or [email_address]