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The aim of this poster is to provide an overview of the principal objectives of the newly started H2020 Computational Literary Studies (CLS) project- https://www.clsinfra.io. CLS is a infrastructure project works to develop and bring together resources of high-quality data, tools and knowledge to aid new approaches to studying literature in the digital age. Conducting computational literary studies has a number of challenges and opportunities from multilingual and bringing together distributing information. At present, the landscape of literary data is diverse and fragmented. Even though many resources are currently available in digital libraries, archives, repositories, websites or catalogues, a lack of standardisation hinders how they are constructed, accessed and the extent to which they are reusable (Ciotti 2014). CLS project aims to federate these resources, with the tools needed to interrogate them, and with a widened base of users, in the spirit of the FAIR and CARE principles (Wilkinson et al. 2016). The resulting improvements will benefit researchers by bridging gaps between greater- and lesser- resourced communities in computational literary studies and beyond, ultimately offering opportunities to create new research and insight into our shared and varied European cultural heritage. Rather than building entirely new resources for literary studies, the project is committed to exploiting and connecting the already-existing efforts and initiatives, in order to acknowledge and utilize the immense human labour that has already been undertaken. Therefore, the project builds on recently- compiled high-quality literary corpora, such as DraCor and ELTeC (Fischer et al. 2019, Burnard et al. 2021, Schöch et al. in press), integrates existing tools for text analysis, e.g. TXM, stylo, multilingual NLP pipelines (Heiden 2010, Eder et al. 2016), and takes advantage of deep integration with two other