Saggion, HoracioRonzano, FrancescoAccuosto, PabloFerrés, Daniel2017-07-132017-07-132017Saggion H, Ronzano F, Accuosto P, Ferrés D. MultiScien: a bi-lingual natural language processing system for mining and enrichment of scientific collections. In: Mayr P, Chandrasekaran MK, Jaidka K, editors. Proceedings of the 2nd Joint Workshop on Bibliometric-enhanced Information Retrieval and Natural Language Processing for Digital Libraries (BIRNDL 2017); 2017 Aug 11; Tokyo, Japan. [place unknown]: CEUR Workshop Proceedings; 2017. p. 26-40.http://hdl.handle.net/10230/32537Comunicació presentada a: 2nd Joint Workshop on Bibliometric-enhanced Information Retrieval and Natural Language Processing for Digital Libraries (BIRNDL 2017) celebrada a Tokyo l'11 d'agost de 2017.In the current online Open Science context, scientific datasets and tools for deep text analysis, visualization and exploitation play a major role.We present a system for deep analysis and annotation of scientific text collections. We also introduce the first version of the SEPLN Anthology, a bi-lingual (Spanish and English) fully annotated text resource in the field of natural language processing that we created with our system. Moreover, a faceted-search and visualization system to explore the created resource is introduced. All resources created for this paper will be available to the research community.application/pdfeng© 2017 for the individual papers by the papers' authors. Copying permitted for private and academic purposes. This volume is published and copyrighted by its editors.info:eu-repo/semantics/conferenceObjectLanguage ResourcesScientific Text CorporaInformation ExtractionData VisualizationSemantic AnalysisPDF Conversioninfo:eu-repo/semantics/openAccess