The pilot entity of the CID is : Institute for Information Sciences and Technologies - INS2I
Sections of affiliation : 01, 06, 07, 11, 12, 13, 14, 15, 16, 17, 18, 19, 30, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41
The skills covered by this Interdisciplinary Commission (CID) should be part of an interdisciplinary approach
which links data science to other scientific fields like high-energy physics, climate science, seismology,
astronomy, cosmology, materials science, digital humanities, social network analysis and the humanities and
social sciences in general
- New management architectures for heterogeneous and massively distributed scientific data
- New intensive computing models used for distributed or virtualised data sources (Cloud)
- Standardisation, verification, analysis and automatic correction of data (quality factors and metrics)
- High-speed screening of large thematic databases
- Processing of imperfect, incomplete or probabilistic data
- Cross-referencing and assimilation of distributed, multi-source and multi-scale data
- Sampling, aggregation and "intelligent" data reduction
- Semantic indexing and extraction of domain ontologies from large data or text corpora
- Visual exploration of large volumes of data, new 3D and 4D visualisation methods
- New multi-scale numerical modelling and simulation methods using large data sets
- Statistical analysis of data, associated with high dimensional data spaces.
- New advances in data mining, text mining and machine learning which drive new methodological practices in
- Artificial intelligence to emulate and/or accelerate digital simulations and multi-source data
- New methods for the engineering, optimisation and dynamic evolution of scientific workflows.
- Long-term data preservation
The expected long-term benefits may either be better understanding of the underlying problems in a scientific
field, accelerating research by using efficient tools or the emergence of new methodological practices.
Composition of the interdisciplinary commission