• DARIAH EU
• Fundação para a Ciência e a Tecnologia, I.P. close

The National Research Council of Italy (CNR) is involved in the E-Cabin project, which aims to create a futuristic and intelligent cabin in order both to improve the well- being and satisfaction of passengers and to minimize the on-board waste by using advanced consumption control.

In this article, we present OntoDomLab-Med, a domain label ontology focused on medical and health sciences. We have developed a taxonomy from thelabels included in the list of abbreviations of the Dicionário da Língua Portuguesa Contemporânea of the Lisbon Academy of Sciences. Our goal is to connect OntoDomLab-Med to a set of selected entries from the dictionary which have been encoded in TEI Lex-0, a stricter and more suitable format than TEI for dictionary encoding, in line with the FAIR principles. The ontology, built with Protégé and represented in OWL, allows the knowledge to be exported using an interoperable exchange format, thereby enabling the ontology to be applied to different lexical resources and to various domains, regardless of the natural language being used. OntoDomLab-Med will be useful not only to research information by domain but it will also allow the lexicographer to be more consistent in his/her work as both researcher and coder of information for lexicographic purposes. Available here: https://es.calameo.com/read/0038662368a28c0171ff4

Multilingualism is a cultural cornerstone of Europe and firmly anchored in the European treaties including full language equality. However, language barriers impacting business, cross-lingual and cross-cultural communication are still omnipresent. Language Technologies (LTs) are a powerful means to break down these barriers. While the last decade has seen various initiatives that created a multitude of approaches and technologies tailored to Europe's specific needs, there is still an immense level of fragmentation. At the same time, AI has become an increasingly important concept in the European Information and Communication Technology area. For a few years now, AI, including many opportunities, synergies but also misconceptions, has been overshadowing every other topic. We present an overview of the European LT landscape, describing funding programmes, activities, actions and challenges in the different countries with regard to LT, including the current state of play in industry and the LT market. We present a brief overview of the main LT-related activities on the EU level in the last ten years and develop strategic guidance with regard to four key dimensions. Comment: Proceedings of the 12th Language Resources and Evaluation Conference (LREC 2020). To appear

Apresentação do projeto Edição Digital dos Vocabulários da Academia das Ciências de Lisboa: o VOLP 1940.

With the increasingly rapid growth of data in life sciences we are witnessing a major transition in the way research is conducted, from hypothesis-driven studies to data-driven simulations of whole systems. Such approaches necessitate the use of large-scale computational resources and e-infrastructures, such as the European Grid Infrastructure (EGI). EGI, one of key the enablers of the digital European Research Area, is a federation of resource providers set up to deliver sustainable, integrated and secure computing services to European researchers and their international partners. Here we aim to provide the state of the art of Grid/Cloud computing in EU research as viewed from within the field of life sciences, focusing on key infrastructures and projects within the life sciences community. Rather than focusing purely on the technical aspects underlying the currently provided solutions, we outline the design aspects and key characteristics that can be identified across major research approaches. Overall, we aim to provide significant insights into the road ahead by establishing ever-strengthening connections between EGI as a whole and the life sciences community. AD was supported by Fundação para a Ciência e a Tecnologia, Portugal (SFRH/BPD/78075/2011 and EXPL/BBBBEP/1356/2013). FP has been supported by the National Grid Infrastructure NGI_GRNET, HellasGRID, as part of the EGI. IFB acknowledges funding from the “National Infrastructures in Biology and Health” call of the French “Investments for the Future” initiative. The WeNMR project has been funded by a European FP7 e-Infrastructure grant, contract no. 261572. AF was supported by a grant from Labex CEBA (Centre d’études de la Biodiversité Amazonienne) from ANR. MC is supported by UK’s BBSRC core funding. CSC was supported by Academy of Finland grant No. 273655 for ELIXIR Finland. The EGI-InSPIRE project (Integrated Sustainable Pan-European Infrastructure for Researchers in Europe) is co-funded by the European Commission (contract number: RI-261323). The BioMedBridges project is funded by the European Commission within Research Infrastructures of the FP7 Capacities Specific Programme, grant agreement number 284209. This is an open-access article.-- et al. Peer Reviewed

This paper describes some experiments made while encoding the first complete dictionary of the Academia das Ciências de Lisboa (DACL) in the context of TEI Lex-0, a community-based interchange format for lexical data aimed at facilitating the interoperability and reusability of lexical resources. Even though the original encoding of the DACL was based on TEI, we decided to switch to TEI Lex-0 because it allowed us to streamline our encoding. Our experiments show that even though TEI Lex-0 is stricter than TEI itself (allowing fewer elements and imposing certain constraints that are not present in plain TEI), it is fully capable of representing the complexities of the entry structure of the DACL. In the paper, we discuss the TEI Lex-0 encoding of the DACL, as well as the conversion methodology and the tools used for the automatic conversion from the original encoding. We are currently focusing on the macrostructural level, more precisely on the types of lexical units and on the written and spoken forms of the lemma, providing a set of modelling principles and representation forms of every type of entry in the DACL. This paper is part of ongoing work and a contribution to the efforts of the DARIAH-ERIC Lexical Resources working group.

Domain Adaptation (DA) techniques aim at enabling machine learning methods learn effective classifiers for a "target'' domain when the only available training data belongs to a different "source'' domain. In this paper we present the Distributional Correspondence Indexing (DCI) method for domain adaptation in sentiment classification. DCI derives term representations in a vector space common to both domains where each dimension reflects its distributional correspondence to a pivot, i.e., to a highly predictive term that behaves similarly across domains. Term correspondence is quantified by means of a distributional correspondence function (DCF). We propose a number of efficient DCFs that are motivated by the distributional hypothesis, i.e., the hypothesis according to which terms with similar meaning tend to have similar distributions in text. Experiments show that DCI obtains better performance than current state-of-the-art techniques for cross-lingual and cross-domain sentiment classification. DCI also brings about a significantly reduced computational cost, and requires a smaller amount of human intervention. As a final contribution, we discuss a more challenging formulation of the domain adaptation problem, in which both the cross-domain and cross-lingual dimensions are tackled simultaneously.

One of the main goals of the PARTHENOS project (Pooling Activities, Resources and Tools for Heritage E-research Networking, Optimization and Synergies - EC-H2020-RIA grant agreement 654119) is to bridge existing DHIs by forming a federation where researchers of different sectors of the Humanities can collaborate, share data, services and tools in an integrated environment. PARTHENOS will produce a complete technical framework for the federation, enabling transparent access to resources managed by different DHIs and enabling the creation and operation of Virtual Research Environments where researchers with different backgrounds can collaborate on specific research topics.