Proceedings of the 4th Workshop of the MPM4CPS COST Action

Proceedings of the 4th Workshop of the MPM4CPS COST Action with the presentations delivered during the workshop and papers with extended versions of some of them

Pristup integraciji tehničkih prostora zasnovan na preslikavanjima iinženjerstvu vođenom modelima

In order to automate development of integration adapters in industrial settings, a model-driven approach to adapter specification is devised. In this approach, a domain-specific modeling language is created to allow specification of mappings between integrated technical spaces. Also proposed is the mapping automation engine that comprises reuse and alignment algorithms. Based on mapping specifications, executable adapters are automatically generated and executed. Results of approach evaluations indicate that it is possible to use a model-driven approach to successfully integrate technical spaces and increase the automation by reusing domainspecific mappings from previously created adapters.За потребе повећања степена аутоматизације развоја адаптера за интеграцију у индустријском окружењу, осмишљен је моделом вођен приступ развоју адаптера. У оквиру овог приступа развијен је наменски језик за спецификацију пресликавања између техничких простора који су предмет интеграције. Приступ обухвата и алгоритме за поравнање и поновно искориштење претходно креираних пресликавања са циљем аутоматизације процеса спецификације. На основу креираних пресликавања, могуће je аутоматски генерисати извршиви код адаптера. У испитивањима приступа, показано је да је могуће успешно применити моделом вођен приступ у интеграцији техничких простора као и да је могуће успешно повећати степен аутоматизације поновним искоришћењем претходно креираних пресликавања.Za potrebe povećanja stepena automatizacije razvoja adaptera za integraciju u industrijskom okruženju, osmišljen je modelom vođen pristup razvoju adaptera. U okviru ovog pristupa razvijen je namenski jezik za specifikaciju preslikavanja između tehničkih prostora koji su predmet integracije. Pristup obuhvata i algoritme za poravnanje i ponovno iskorištenje prethodno kreiranih preslikavanja sa ciljem automatizacije procesa specifikacije. Na osnovu kreiranih preslikavanja, moguće je automatski generisati izvršivi kod adaptera. U ispitivanjima pristupa, pokazano je da je moguće uspešno primeniti modelom vođen pristup u integraciji tehničkih prostora kao i da je moguće uspešno povećati stepen automatizacije ponovnim iskorišćenjem prethodno kreiranih preslikavanja

Relatedness, National Boarders, Perceptions of Firms and the Value of Their innovations

The main goal of this dissertation is to better understand how external corporate stakeholder perceptions of relatedness affect important outcomes for companies. In pursuit of this goal, I apply the lens of category studies. Categories not only help audiences to distinguish between members of different categories, they also convey patterns of relatedness. In turn, this may have implications for understanding how audiences search, what they attend to, and how the members are ultimately valued. In the first chapter, I apply incites from social psychology to show how the nationality of audience members affects the way that they cognitively group objects into similar categories. I find that the geographic location of stock market analysts affect the degree to which they will revise their earnings estimates for a given company in the wake of an earnings miss by another firm in the same industry. Foreign analysts revise their earnings estimates downward more so than do local analysts, suggesting that foreign analysts ascribe the earnings miss more broadly and tend to lump companies located in the same country into larger groups than do local analysts. In the second chapter, I demonstrate that the structure of inter-category relationships can have consequential effects for the members of a focal category. Leveraging an experimental-like design, I study the outcomes of nanotechnology patents and the pattern of forward citations across multiple patent jurisdictions. I find that members of technology categories with many close category \u27neighbors\u27 are more broadly cited than members of categories with few category \u27neighbors.’ My findings highlight how category embeddedness and category system structure affect the outcomes of category members as well as the role that classification plays in the valuation of innovation. In the third chapter, I propose a novel and dynamic measure of corporate similarity that is constructed from the two-mode analyst and company coverage network. The approach creates a fine-grained continuous measure of company similarity that can be used as an alternative or supplement to existing static industry classification systems. I demonstrate the value of this new measure in the context of predicting financial market responses to merger and acquisition deals

Academia/Industry DynAmics (AIDA): A knowledge Graph within the scholarly domain and its applications

Scholarly knowledge graphs are a form of knowledge representation that aims to capture and organize the information and knowledge contained in scholarly publications, such as research papers, books, patents, and datasets. Scholarly knowledge graphs can provide a comprehensive and structured view of the scholarly domain, covering various aspects such as authors, affiliations, research topics, methods, results, citations, and impact. Scholarly knowledge graphs can enable various applications and services that can facilitate and enhance scholarly communication, such as information retrieval, data analysis, recommendation systems, semantic search, and knowledge discovery. However, constructing and maintaining scholarly knowledge graphs is a challenging task that requires dealing with large-scale, heterogeneous, and dynamic data sources. Moreover, extracting and integrating the relevant information and knowledge from unstructured or semi-structured text is not trivial, as it involves natural language processing, machine learning, ontology engineering, and semantic web technologies. Furthermore, ensuring the quality and validity of the scholarly knowledge graphs is essential for their usability and reliability

AIDA: a Knowledge Graph about Research Dynamics in Academia and Industry

Academia and industry share a complex, multifaceted, and symbiotic relationship. Analysing the knowledge flow between them, understanding which directions have the biggest potential, and discovering the best strategies to harmonise their efforts is a critical task for several stakeholders. Research publications and patents are an ideal medium to analyze this space, but current datasets of scholarly data cannot be used for such a purpose since they lack a high-quality characterization of the relevant research topics and industrial sectors. In this paper, we introduce the Academia/Industry DynAmics (AIDA) Knowledge Graph, which describes 21M publications and 8M patents according to the research topics drawn from the Computer Science Ontology. 5.1M publications and 5.6M patents are further characterized according to the type of the author’s affiliations and 66 industrial sectors from the proposed Industrial Sectors Ontology (INDUSO). AIDA was generated by an automatic pipeline that integrates data from Microsoft Academic Graph, Dimensions, DBpedia, the Computer Science Ontology, and the Global Research Identifier Database. It is publicly available under CC BY 4.0 and can be downloaded as a dump or queried via a triplestore. We evaluated the different parts of the generation pipeline on a manually crafted gold standard yielding competitive results

Information retrieval and text mining technologies for chemistry

Efficient access to chemical information contained in scientific literature, patents, technical reports, or the web is a pressing need shared by researchers and patent attorneys from different chemical disciplines. Retrieval of important chemical information in most cases starts with finding relevant documents for a particular chemical compound or family. Targeted retrieval of chemical documents is closely connected to the automatic recognition of chemical entities in the text, which commonly involves the extraction of the entire list of chemicals mentioned in a document, including any associated information. In this Review, we provide a comprehensive and in-depth description of fundamental concepts, technical implementations, and current technologies for meeting these information demands. A strong focus is placed on community challenges addressing systems performance, more particularly CHEMDNER and CHEMDNER patents tasks of BioCreative IV and V, respectively. Considering the growing interest in the construction of automatically annotated chemical knowledge bases that integrate chemical information and biological data, cheminformatics approaches for mapping the extracted chemical names into chemical structures and their subsequent annotation together with text mining applications for linking chemistry with biological information are also presented. Finally, future trends and current challenges are highlighted as a roadmap proposal for research in this emerging field.A.V. and M.K. acknowledge funding from the European Community’s Horizon 2020 Program (project reference: 654021 - OpenMinted). M.K. additionally acknowledges the Encomienda MINETAD-CNIO as part of the Plan for the Advancement of Language Technology. O.R. and J.O. thank the Foundation for Applied Medical Research (FIMA), University of Navarra (Pamplona, Spain). This work was partially funded by Consellería de Cultura, Educación e Ordenación Universitaria (Xunta de Galicia), and FEDER (European Union), and the Portuguese Foundation for Science and Technology (FCT) under the scope of the strategic funding of UID/BIO/04469/2013 unit and COMPETE 2020 (POCI-01-0145-FEDER-006684). We thank Iñigo Garciá -Yoldi for useful feedback and discussions during the preparation of the manuscript.info:eu-repo/semantics/publishedVersio

Report of the Stanford Linked Data Workshop

The Stanford University Libraries and Academic Information Resources (SULAIR) with the Council on Library and Information Resources (CLIR) conducted at week-long workshop on the prospects for a large scale, multi-national, multi-institutional prototype of a Linked Data environment for discovery of and navigation among the rapidly, chaotically expanding array of academic information resources. As preparation for the workshop, CLIR sponsored a survey by Jerry Persons, Chief Information Architect emeritus of SULAIR that was published originally for workshop participants as background to the workshop and is now publicly available. The original intention of the workshop was to devise a plan for such a prototype. However, such was the diversity of knowledge, experience, and views of the potential of Linked Data approaches that the workshop participants turned to two more fundamental goals: building common understanding and enthusiasm on the one hand and identifying opportunities and challenges to be confronted in the preparation of the intended prototype and its operation on the other. In pursuit of those objectives, the workshop participants produced:1. a value statement addressing the question of why a Linked Data approach is worth prototyping;2. a manifesto for Linked Libraries (and Museums and Archives and …);3. an outline of the phases in a life cycle of Linked Data approaches;4. a prioritized list of known issues in generating, harvesting & using Linked Data;5. a workflow with notes for converting library bibliographic records and other academic metadata to URIs;6. examples of potential “killer apps” using Linked Data: and7. a list of next steps and potential projects.This report includes a summary of the workshop agenda, a chart showing the use of Linked Data in cultural heritage venues, and short biographies and statements from each of the participants

Consortium Proposal NFDI-MatWerk

This is the official proposal the NFDI-consortium NFDI-MatWerk submitted to the DFG within the request for funding the project. Visit www.dfg.de/nfdi for more infos on the German National Research Data Infrastructure (Nationale Forschungsdateninfrastruktur - NFDI) initiative. Visit www.nfdi-matwerk.de for last infos about the project NFDI-MatWerk