Lowcomote, Training the Next Generation of Experts in Scalable Low-Code Engineering Platforms

The MSCA ITN 2018 project Lowcomote will train a generation of experts that will upgrade the current trend of Low-code development platforms (LCPDs) to a new paradigm, Lowcode Engineering Platforms (LCEPs).

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These platforms allow anyone to build software by interacting through dynamic graphical user interfaces without requiring to write code in complex programming languages. This project will open LCDPs by making LCEPs interoperable, allowing for cross-platform engineering. They will then allow to integrate heterogeneous engineering tools, supporting very large engineering models.
Using machine learning, they will allow anyone to become a citizen developer and to build its own software for Internet of Things or smartphones for instance. This will be achieved by injecting into LCDPs the theoretical and technical framework defined by recent research in Model Driven Engineering (MDE), augmented with Cloud Computing and Machine Learning techniques.

The 48-month Lowcomote project will train the first European generation of skilled professionals in LCEPs. For 36 months, the 15 future Early Stage Researchers (ESRs) will benefit from an original training and research program merging competencies and knowledge from 5 highly recognised academic institutions and 8 large and small industries of several domains in Europe. Collaborations between ESRs and their co-supervision by several partners is a promising process to facilitate agility of our future professionals between the academic and industrial world.

Groupe projet Lowcomote

Partners

IMT Atlantique, University of York, Universidad Autόnoma de Madrid, University of L’Aquila, JK University of Linz, British Telecom, Intecs, Uground, CLMS UK, IncqueryLabs, SparxSystems, Metadev, The Open GroupAmazon Web Services

Further information

For any further information please visit the project’s website:

https://www.lowcomote.eu/

EuropeThis project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement
No 813884