Digital resources are data, storage capacity, computing capacity, network capacity and necessary software to perform calculations and manage data. Our Data Science Analytics Group offers this to researchers and project partners in industry and public sector.
Accelerating integration of data science in research projects
The dScience Data Science Analytics Group has been established to accelerate the integration of data science technologies, such as data management, high-performance computing, machine learning, artificial intelligence, and interactive data visualisation into research projects.
By integrating these technologies, we are enhancing the competitiveness and productivity of researchers at the University of Oslo and among dScience partners. As we pursue this goal, our efforts are mainly focused on two key areas of support:
1) Courses and workshops on commonly encountered challenges by researchers
Below is a list of workshops that we have designed and held so far:
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Version control using Git and GitHub
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Building packages in R
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Introduction to modern tools and packages in R
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Project management for PhD students.
These workshops are regularly held depending on the demands from the researchers.
2) Direct involvement in research projects
The projects are received in the context of data science support calls or from dScience partners. The scope of this support is categorized in three main pillars: “Data preparation”, “Data analysis” and “Dissemination” with detailed sub-categories as follow:
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Data preparation
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Data storage and access (systematic storage and sharing of data)
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Big data (challenges with storage and backup and memory for processing)
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Data organization and management (need to develop a system)
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Data pipeline and automation (use the data efficiently and effectively in pipeline)
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Data wrangling and transformation (prepare and structure data for analysis)
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Data analysis
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High performance computing
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Programming support (need limited programming support on particular issues)
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Prototyping and implementation (turning your idea into a model)
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Statistical data analysis (you know what but don’t know how)
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Machine learning (from brainstorming on ideas to implementation and interpretation)
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Exploratory data analysis (need to explore and understand your data)
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Dissemination
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Data visualization and communication (effective visualization of results for publications)
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Platform development (turning code to packages and graphical user interface)
Contact us
dScience collaborates closely with USIT – The University Centre for Information Technology and their Department for Research Computing.
