Internal dynamics of patent reference networks using the Bray–Curtis dissimilarity measure

Abstract Background Patents are indicators of technological developments. The science & technology categories, to which they are assigned to, form a directed, weighted network where the links are the references between patents belonging to the respective categories. This network can be conceived as a kind of intellectual ecology, lending itself to mathematical analyses analogous to those carried out in numerical ecology. The non-metric Bray–Curtis dissimilarity, commonly used in quantitative ecology, can be used to describe the internal dynamics of this network. Results While the degree-distribution of the network remained stable during the studied years, that of the sub-networks of with at least k links showed that k = 5 is a critical number of citations: this many are needed that the bias towards already highly cited works come into effect (preferential attachment). Using the d ij Bay-Curtis dissimilarity between nodes i and j, a surprising pattern emerged: the log-probability of a change in d ij during a quarter of year depended linearly, with a negative coefficient, on the magnitude of the change itself. Conclusions The developed methodology could be useful to detect emerging technological developments, to aid decisions, for example, on resource allocation. The pattern found on the internal dynamics of the system depends on the categorisation of the patents, therefore it can serve as an indicator when comparing different categorisation methods. Graphical Abstrac

Emerging risk identification by applying data analytical tools

Abstract The working programme ‘Emerging risk identification by applying data analytical tools’ was delivered by the Digital Food Chain Education, Research, Development, and Innovation Institute (Digital Food Institute, DFI) on the field of emerging risks at the University of Veterinary Medicine Budapest, Hungary. The Institute is the University's research and education unit that provides data analysis and research along the whole food chain and takes networking in this area to a new level. The Fellow joined the hub of experts and researchers in the field of food chain safety data analysis, responsible for protecting public health concerning food in Hungary. The programme consisted of several different activities to provide an overview of the different tools that can be employed in the emerging risk identification process and prepare various stakeholders for new food chain safety issues. The programme was split into four modules to run over the one‐year fellowship covering different areas of data analysis and emerging risk identification. The aim was to be fully integrated with the organisation's work experience, increase knowledge of scientific aspects relevant in the field of data analysis and visualisation tools in the emerging risk identification area, and implement the results into various EU stakeholders' environments assessments

Project DEMETER: Concept Note for an Emerging Risks Knowledge Exchange Platform (ERKEP) Framework

Researchers, governments, agencies, food producers and the civil society are increasingly concerned about ‘emerging food risks’. It is recognised that the successful identification of emerging risks is at the heart of protecting public health and the environment, and that this requires worldwide cooperation between all parties involved in the food supply chain. The objectives and research proposed in the DEMETER project are designed to support current (and future) EFSA procedures for emerging issue and risks identification, providing a community resource that will allow EFSA and EU Member State authorities to share data, data mining knowledge and methods in a rapid and effective manner. A prototype technical Platform called the Emerging Risks Knowledge Exchange Platform (ERKEP) will be developed by DEMETER.The ‘Concept Note’ is a vison document on a framework of Emerging Risk Knowledge Exchange in which ERKEP is embedded in – but goes beyond the ERKE platform. Outlined in this document are: definitions of relevant concepts in the context of emerging issues and risks identification; who are the contributors, users and stakeholders of ERKEP; what are the identified end‐user needs, how could the ERKEP Framework contribute to meeting these needs; what types of knowledge, data, and methods do they share; and how can a technical solution be implemented to support these activities

Determination and Metrics for Emerging Risks Identification DEMETER: Final Report

Identification of emerging risks in the food chain is essential if EFSA is to anticipate future needs in risk assessment, in relation to both data and methodology. The objectives and research proposed in the DEMETER project were specifically designed to support current (and future) EFSA procedures for emerging issue and risks identification by providing community resourcesto allow EFSA and EU Member State authorities to share data, knowledge and methods on emerging risks identification in a rapid and effective manner through a digital platform. To this end, an “Emerging Risk Knowledge Exchange Platform (ERKEP)” was developed as a prototype technical solution. Its design is based on a consultation on end‐users needs and the analysis of existing knowledge sharing solutions. ERKEP consists of three main components: 1) A content management system (CMS) providing the end‐user's “entry point” and Graphical User Interface (GUI) to ERKEP; 2) A web‐based data analytics platform (DAP) for sharing and executing data analytics workflows (DAWs), based on the KNIME Server infrastructure; 3) External web‐based services hosted by 3rd party service providers. Different DAWs were developed and added to the platform, these are: 1) Emerging risk identification system for the milk supply chain based on automated data retrieval; 2) NewsRadar; 3)Trending topics in news based on text mining and network analysis, and;4) Patent network analysis. Methodologies were identified to integrate social science information and data, into the emerging risk identification framework. Systematic reviews of the literature wereconducted in the areas of expert elicitation, citizen science, and behavioural science and a framework to incorporate data from Citizen Science into the EKREP platform was proposed. Finally, sustainability and maintenance of the project's outputs were conceptualized to enable use thereof beyond project DEMETER.<br/