Information TO Expertise (I2E) method : Scientific and Technical Information push in order to raise expertise from an operational point of view and in a non-deterministic approach

The I2E method is developed at the AEA Cadarache Center. The purpose of this method has been motivated by the observation of the inefficiency of traditional Scientometrics Indicators in order to give advice for experts to manage their career and to help our research institution to expand their areas of expertise. The inefficiency of Scientometrics Indicators is due to, at least, three major reasons: • expertise is a set of skills acquired through single experience depending on the single career of the experts, • Many aspects of expert experience are neither visible on the Web nor can automatically be extracted without assistance from the expert himself, • Even if it is assumed that cutting-edge research today is not done by individuals, experts are becoming the core of research groups and highly contribute to the path of the Scientific Community. Unlike the theoretical approaches used in science evaluation, our method is empirical and based on 1- Identification of efficient factors by retro-analysis (vs. story telling) 2- Information push according to previous factors (indirect action through the use of information) 3- Observation of effects on the scientific community (information for decision-making purpose) 4- Ongoing adjustment (non-deterministic monitoring) The method is based on a bibliography synthesis including scientific works dealing with science evaluation, measurement bias and practices to raise expertise. Retro-analysis is realized with experts who are obviously authorities (according to objective signs of recognition like graduation or prices). Study is currently going on with a sample of 10 experts working on strategic activities at NEA Cadarache center. The main issue of the study is to help experts building and maintaining their own proactive digital identity defined through a dynamic biography highlighting their experience according to the most favorable emerging criteria of the moment (serendipity principle). This work includes 1- Collection and evaluation of the external information dealing with the expert career 2- Diagnosis of the scientific production value-chain 3- Internal information push towards the scientific community by using HAL-CEA and Google-Scholar 4- External information analysis and production of indicators (visibility, relevance and attractiveness) for internal decision-making (Science Government, Operational Management, Human Resources Management) First results were obtained with 2 major experts working for 17 and 20 years on nuclear instrumentation in AEA Cadarache center: 1- Experts have shown strong commitment to the approach 2- Experts profile in Google scholar have been successfully built applying the tree-cloud method on thematic sub-corpus 3- Visibility analysis allowed us to identify institutional index failures and highlight the following individual determinants of visibility : • Scope of scientific activities : research, innovation, teaching, thesis direction, students mentoring, seminar organization, reviewing, … • Scientific scope and areas of work : multi disciplinarity, cross-application • Publication context and communication supports : seminars, conferences, work-group, journal etc… 4- Corpus analysis using the co-author pass of academic search tool has been very useful to identify research group through indirect expert networks The next step in the process will be to validate and enrich the initial outcomes by applying to the leading panel of experts.