The variety and diversity of published content are currently expanding in all fields of scholarly communication. Yet, scientific knowledge graphs (SKG) provide only poor images of the varied directions of alternative scientific choices, and in particular scientific controversies, which are not currently identified and interpreted. We propose to use the rich variety of knowledge present in search histories to represent cliques modeling the main interpretable practices of information retrieval issued from the same “cognitive community”, identified by their use of keywords and by the search experience of the users sharing the same research question. Modeling typical cliques belonging to the same cognitive community is achieved through a new conceptual framework, based on user profiles, namely a bipartite geometric scientific knowledge graph, SKG GRAPHYP. Further studies of interpretation will test differences of documentary profiles and their meaning in various possible contexts which studies on “disagreements in scientific literature” have outlined. This final adjusted version of GRAPHYP optimizes the modeling of “Manifold Subnetworks of Cliques in Cognitive Communities” (MSCCC), captured from previous user experience in the same search domain. Cliques are built from graph grids of three parameters outlining the manifold of search experiences: mass of users; intensity of uses of items; and attention, identified as a ratio of “feature augmentation” by literature on information retrieval, its mean value allows calculation of an observed “steady” value of the user/item ratio or, conversely, a documentary behavior “deviating” from this mean value. An illustration of our approach is supplied in a positive first test, which stimulates further work on modeling subnetworks of users in search experience, that could help identify the varied alternative documentary sources of information retrieval, and in particular the scientific controversies and scholarly disputes.

International audiencePurposeThis paper aims to present empirical evidence on the opinion and behaviour of French scientists (senior management level) regarding open access (OA) to scientific and technical information.Design/methodology/approachThe results are part of a nationwide survey on scientific information and documentation with 432 directors of French public research laboratories conducted by the French National Research Center (CNRS) in 2014.FindingsThe CNRS senior research managers (laboratory directors) globally share the positive opinion towards OA revealed by other studies with researchers from the UK, Germany, the USA and other countries. However, they are more supportive of open repositories (green road) than of OA journal publishing (gold). The response patterns reveal a gap between generally positive opinions about OA and less supportive behaviours, principally publishing articles with article processing charges (APCs). A small group of senior research managers does not seem to be interested in green or gold OA and reluctant to self-archiving and OA publishing. Similar to other studies, the French survey confirms disciplinary differences, i.e. a stronger support for self-archiving of records and documents in HAL by scientists from Mathematics, Physics and Informatics than from Biology, Earth Sciences and Chemistry; and more experience and positive feelings with OA publishing and payment of APCs in Biology than in Mathematics or in Social Sciences and Humanities. Disciplinary differences and specific French factors are discussed, in particular in the context of the new European policy in favour of Open Science.Originality/valueFor the first time, a nationwide survey was conducted with the senior research management level from all scientific disciplines. The response rate was high (>30 per cent), and the results provide good insight into the real awareness, support and uptake of OA by senior research managers who provide both models (examples for good practice) and opinion leadership

The decline of the European eel (Anguilla anguilla) stock has led the European Commission to enforce a regulation (Council Regulation N°1 100/2007), in which each member state was required to establish an eel management plan. Various measures in the French plan aim at restoring river connectivity by mitigating the impact of obstacles on the colonization of continental water by eels. Consequently, many obstacles are going to be equipped with elver ladder in the near future. In this context, a method to assess the passability of an obstacle seems essential. In this study, we developed a tag-recapture method, appropriate to glass eels and elvers, and an associated multi-state mark-recapture model (i) to assess the passability of a ladder and (ii) to quantify the effect of various environmental factors on this passability. An application to a specific obstacle is applied as an illustrative example that demonstrates the relevance of the assessment method, and how the results can be used to propose technical solution to improve the efficiency of the ladder. Nine tag-recapture campaigns were carried on this obstacle, and about 4400 young eels were tagged. The model demonstrates that the efficiency of the ladder was rather low, especially during low river flow periods, mainly because of accessibility problems. The model also demonstrates the major influence of the river flow on the probability for an eel to pass the ladder; consequently, managing river flow during the migration period can be a relevant measure to improve river connectivity and facilitate colonization of the watershed.

Big data have become a global strategic issue, as increasingly large amounts of unstructured data challenge the IT infrastructure of global organizations and threaten their capacity for strategic forecasting. As experienced in former massive information issues, big data technologies, such as Hadoop, should efficiently tackle the incoming large amounts of data and provide organizations with relevant processed information that was formerly neither visible nor manageable. After having briefly recalled the strategic advantages of big data solutions in the introductory remarks, in the first part of this paper, we focus on the advantages of big data solutions in the currently difficult time of the COVID-19 pandemic. We characterize it as an endemic heterogeneous data context; we then outline the advantages of technologies such as Hadoop and its IT suitability in this context. In the second part, we identify two specific advantages of Hadoop solutions, globality combined with flexibility, and we notice that they are at work with a “Hadoop Fusion Approach” that we describe as an optimal response to the context. In the third part, we justify selected qualifications of globality and flexibility by the fact that Hadoop solutions enable comparable returns in opposite contexts of models of partial submodels and of models of final exact systems. In part four, we remark that in both these opposite contexts, Hadoop’s solutions allow a large range of needs to be fulfilled, which fits with requirements previously identified as the current heterogeneous data structure of COVID-19 information. In the final part, we propose a framework of strategic data processing conditions. To the best of our knowledge, they appear to be the most suitable to overcome COVID-19 massive information challenges.

HAL is a multidisciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.