The CMI research imaging infrastructure ENACT which connects virtual workspaces with large data centers and high performance computing facilities is embedded in the Center for Information Technology (CIT) of the University of Groningen. The CIT provides high quality IT services, primarily to the University of Groningen and secondarily to educational institutions in the north of the country. To achieve our objective, the CIT has many facilities at its disposal. The department of Research and Innovation Support (RIS) CIT provides scientists and other interested parties with state-of-the-art facilities in High-Performance Computing (HPC). These include the Peregrine Cluster (>170nodes, >4000cores, ~500TB storage, 56Gb/s Infiniband network, 10Gb/s Ethernet), the Grid Cluster (58 compute nodes, ~1000 cores, 10Gb/s Ethernet, Access to the Target storage of 10 Petabytes) and the Millipede Cluster (>250 nodes, 3280 cores, 350TB storage). The heart of the visualization facilities is the Reality Center, which consists of the 4-sided Reality Cube and the wide-screen Reality Theatre. Both the Cube and the Theatre are driven by the high-end visualization cluster. There is a portable 3D system available for on-site presentations. The facilities and expertise of the CIT are available and used both by DSSC and CMINEN in a variety of projects.
The center for Data Science and Systems Complexity (DSSC) consists of a cluster of more than 50 prominent senior researchers at the University of Groningen in a number of basic disciplines (mathematics, astronomy, computer science, artificial intelligence, systems & control) and scientific application domains (genomics, pharmacology, instrumentation). The ambition of DSSC is to combine data science and complexity science. Simulations or measurements of complex systems, like climate models or coupled cell systems, give rise to (big) data in a mixed deterministic and random style. The DSSC is lead by Prof. Roerdink (see attached CV).
The DSSC focuses on a new way of scientific research, resulting from the impact of information technology. Data are produced in huge amounts, either by instruments or sensors, by simulations, or captured from the internet. Then the data are processed in software pipelines, stored in databases, and permanently archived in data centers. Only then will scientists ‘look’ at their data via complex data analysis and visualisation pipelines to search for specific information, or do large-scale exploration of the data. In short, the database has become the laboratory / observatory.
Scientific data, the software to analyze the data, the results of the analysis (tables, graphs, images), and the corresponding publications become part of one persistent digital archive. The application of Data Science in scientific, economic, health, and social contexts has become known under the name ‘Big data’. Producing, handling, and analyzing big data also increasingly involves large scientific communities of experts in their respective fields. So, by nature, data science is collaborative science, which is also reflected in increasing attention for data sharing, innovative ways of data acquisition (for example, through crowd sourcing), integration of cyber-infrastructure into human workflows and practices, and new ways of publication (including data) that depart from the traditional journal and conference format.
The ENACT environment is already up and running for pilot studies and will be released more extensively early 2017. Future perspective is to have every CMI related research project running the ENACT environment providing easy data collection, storage and access with cloud-based access to advanced visualization software and other required software tools.
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