Information access systems provide users with key information from reliable sources such as scientific literature; however, non-experts tend to avoid these sources due to its complex language or their lack of background knowledge. Text simplification removes some of these barriers. SimpleText will be a step forward to make research really open, accessible and understandable for everyone and help to counter fake news based on scientific results (sustainable development goal QUALITY EDUCATION). This is especially important with an explosion of open science during the COVID-19 pandemic. Simplified texts are more accessible for non-native speakers, young readers, people with reading disabilities or lower levels of education (sustainable development goal REDUCED INEQUALITY). Automatic text simplification could be useful for various domains such as scientific communication, science journalism, politics and education. SimpleText tackles technical challenges and evaluation challenges by providing appropriate algorithms, data and benchmarks for text simplification and aims to answer the following research questions: RQ1 - What textual expression carrying information should be simplified (document and passage to be included in the simplified summary)? RQ2 - What kind of background information should be provided (what terms should be contextualised by giving a definition, use-case, example etc.)? RQ3 - How to improve the readability of a given short text (e.g. by reducing vocabulary and syntactic complexity) with acceptable rate of information distortion? RQ4 - To what extent are the approaches for English applicable for French? We will provide algorithms, collections and evaluation tools openly available to the scientific community (to the extent permitted by third-party copyrights) and will be valued at international evaluation campaigns, e.g. CLEF as well as at classes on pre-editing, web-site localisation, technical writing and digital humanities.

The APPREL2 project aims to provide an account of the learning and development of the foreign language (FL or L2) lexicon in a schooling context. This context is characterized by the fact that L1 reading acquisition in still ongoing in children and that exposure to the L2 is quantitatively low. The project draws upon theoretical models developed in cognitive psycholinguistics: first, the well-structured models of skilled visual word recognition in bilinguals (especially, the BIA and BIA+ models, Dijkstra et al, 1998; Dijkstra et al 2002); and second, the models developed to describe the process of learning to read in monolinguals (Ehri, 2014). The project aims to test a developmental version of bilingual visual word recognition, BIA-d (Grainger et al, 2010), and to extend it by integrating a phonological component. This approach will be complemented by a language-teaching perspective that aims to connect our experimental studies to classrooms situations and to situate (visual) word recognition within a broader spectrum of emerging L2 skill and knowledge. Models of L2 lexical development (DevLex, MacWhinney) will therefore also be considered. The scientific objectives are to demonstrate how L2 words are progressively integrated in the lexicon and to analyse how L1 –L2 lexical and sublexical information interacts. We will assess how L2 word processing, especially written words, evolves according to children’s age and reading level. We also will examine orthographic processing during L2 word learning. How FL lexicon development is related to reading skills will also be explored through the impact of a partial L2 school immersion on the learning of a L3. The challenge is to trace the benefits of the early learning of two languages and the mastery of two systems of grapheme to phoneme correspondences. The project is organized into four tasks. Task 1 consists of compiling a lexical database, from textbooks, reflecting English written language instruction in secondary school. Quantitative analyses will define word lexical and sublexical characteristics, which will be used to construct assessments of L2/L3 word acquisition. The written database will be completed by transcripts of lessons. The following three tasks are organized according to participant age –leading to the use of different paradigms: word learning in primary school vs. visual -and to a lesser extend spoken- word recognition in secondary school- and the L2/L3 learning context (traditional vs. after partial immersion in L2). Task 2 aims to assess L2 word recognition development in secondary school via several experiments and will focus on L1 and L2 lexical and sublexical interactions. Task 3 is designed to investigate the effects of partial L2 immersion during L3 word processing, in terms of the development of both linguistic and word recognition skills. The aim is to assess the effects of partial immersion in L2 during L3 word processing, in terms of both linguistic development and word recognition. Task 4 uses learning experiments conducted with developing reading at primary school to assess the contribution of orthographic information in L2 word memorization. Task 4 also includes experiments in immersion programs in order to locate the benefits of the immersion situation by manipulating the L2/L3 linguistic proximity of words in word learning experiments. The project brings researchers with expertise in reading acquisition, L2 word learning, lexical databases and language teaching. The main deliverables from the project are a lexical database for L2 English words in secondary school, dissemination papers, and concrete methodological recommendations for L2 teaching. Scientific papers will be submitted to high-impact journals and conferences, and papers will be published in professional journals to reach leading players (teachers, conseillers pédagogiques, the Inspection) in foreign language teaching in primary and secondary schools.

The Data PACT project aims at analysing and fostering data culture through the development of two main activities: the creation of a database about data practices and initiatives in involved European countries and the analyse of publics and practices in a “datafied society”. These two activities will settle the basis of the H2020 proposal : coproduction of new activities with citizens and cocreation of knowledge about and with data. First we think that data culture takes plural form in different social and cultural contexts and is reflected in many practices : mediatic, routine, associative, militant, etc. Second we are convinced that a critical approach is necessary and we strongly disagree with an universalizing and homogenizing conception of data publics and practices. We advance the hypothesis that there are data cultures as a new field of scientific culture and it could be enhancing by establishing links between scientific vulgarization and media literacy. Our goal is to move beyond traditional data literacy endeavours by taking into account activities emerging in societies. Moreover, we firmly believe that, in order to go further on this topic, researchers have to cross their expertise, create new interdisciplinary methods with and for citizens and document their observations and processes. The Data PACT project has configured an academic network from 8 countries in Europe (Belgium, England, France, Luxembourg, Netherlands, Portugal, Spain, Italy). Several disciplines are represented as the network will working in an interdisciplinarity way: information science, media and communication studies, computer science, design, data science, citizen science. This variety of perspectives is strengthened by different methodological approaches: data analysis, sociological inquiry, visualization techniques, living labs etc. Network members experiment and set up different actions to define, transmit and coproduce data culture: citizen workshop, educational program, data camp, analysis tools, etc. As we explore different fields, it allows us to deal with people practices and to analyze and compare their differences and similarities in regard to established new initiatives. Citizens interact, produce or engage in data-oriented activities in an everyday pace. However, we aim at identifying the different processus ways data cultures are emerging in society. We foresee mainly five fields at this phase: 1) data of everyday things and life (ordinary use of data) 2) retro-engineering (opening the black box and understanding logics of data); 3) data activism (participatory and debate with data); 4) participatory science (citizen as producer and analyst of data with the support of researchers); 5) media data and data art (the use of data from an aesthetic and artistic perspective). Our network targets "Integrating Society in Science and Innovation – An approach to co-creation" H2020. The main goal is to build documentation about practical activities to forther replication, improvement, sharing. The Data PACT project has the intention to, first, conduct a situational analysis of data culture initiatives and events in each involved country. The outcome of this phase takes the form of an opendatabase, which is conceived and configured collectively from its basic structure. In a second and larger phase, the project confronts people to their practices. It is about fostering a reflective thinking on data culture, to unveil contrasts between established practices and emerging ones. Data culture, considered as a new scientific culture, addresses problems of specifications, objectives and methods that propel everyday practices and try to formalize them in order to communicate with other initiatives. The purpose is not strictly to develop a data-driven education or evangelization of data-based methods. We rather describe and understand empirical methods that increase public engagement and encourage the dissemination of data culture.