AI-Driven data science

WP 1 is concerned with all steps starting from the ingestion of the data to the generation of labelled data and high-level features. It will contribute partially automated techniques for data ingestion and wrangling, data quality assessment and enhancement, semantic interpretation, automatic feature generation and active learning. 

WP 2 focuses on using knowledge in the data science process, and as such it will contribute knowledge representation languages that extend the common ground between learning and reasoning, new algorithms for learning and reasoning as well flexible and interactive ways for humans to supervise and steer learning and reasoning processes.

WP 3 will contribute with AI techniques to (partially) automate the data exploration processes, and to better assist data analysts in obtaining interesting and actionable insights from data. It will focus on AI-assisted interactive techniques, on formalizing ‘insights’ in intelligible and actionable ways, on exploiting background knowledge to ensure the (subjective) interestingness of such discovered insights, on realistic high-dimensional and structured datasets, and on scalable methods.

WP 4 is concerned with the automation of machine learning and as such focuses on the model construction step starting from the data and knowledge produced in the earlier WPs. It will focus on three steps: problem analysis, the actual model construction step and performance tuning while keeping the human in the loop.

WP 5 focuses on technical AI-oriented solutions for obtaining trustworthy AI systems. It wants to build trust, ethical and privacy aspects directly into the core of AI methods. It focuses on three techniques: explainability, ethics (pen-testing) and preserving the privacy of data in a federated manner. 

WP 6 focuses on decision support, that is, on the adoption of AI technologies *after* algorithm development, benchmarking, and training of machine learning systems. Decision support systems have an integrative role vis à vis technologies, and a matchmaking and educative role vis à vis users and applications. Thus WP 6 contributes to the system, user, process and organizational level of decision support.

WP 7 focuses on the following Use Cases in the area of health: Single Cell Technologies, Multiple Sclerosis, Epilepsy, Medical Image Processing, Length of Stay in Hospitals.

WP 8 focuses on the following Use Cases for industry and society: Production Process Optimization, Low Voltage Energy Distribution Grid, Employment Services, Prognostic and health monitoring for ageing wind turbines.