Research

About the Data Science Lab

What is data science?

Data science is an interdisciplinary field whose goal is to extract knowledge from complex data using a fusion of computation, machine learning, and domain expertise. Data science is closely related to big data, but data science is more focused on the process of learning from, and making decisions based on, data rather than the size of the data set itself. Data science is also closely related to artificial intelligence (AI) in its utilization of high computational power and core methodological approaches like machine learning, deep learning, and natural language processing.

Three core pillars

The Data Science Lab will leverage and amplify breakthroughs in data science and AI to tackle major challenges facing society.

Research

The Data Science Lab is building a programme of research excellence in applied data science in three core areas:

  • Foundational aspects of data science (e.g., machine learning, natural language processing).
  • Intensive and novel applications of data science to a variety of data-rich domains.
  • Study of the implications of data science on government and society (e.g., ethics, law, andpublicpolicy).

 

 

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Training and capacity-building

Training and professional development provided through the Data Science Lab prepares graduates for careers in the public and private sectors into both technical positions that require methodological expertise and leadership positions that require high-level understanding of underlying AI and data science technology. The lab's team work closely with employers, alumni and academics, in developing and introducing a set of courses on machine learning, natural language processing, causal inference in machine learning, and the societal implications of AI.

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Outreach

The Data Science Lab helps external partners achieve their long-term policy aims in service of the common good. The lab's outreach is informed by the principles of fairness, accountability, and transparency.

The lab's team have already started working with a range of Berlin startups who carry out innovative R&D work to assess the ethical and policy implications of their products. 

Academic research benefits from access to real-world data, novel research challenges, and opportunities for high-impact use cases.

The Hertie School community benefits from the acquisition of new skills, improved employability for our students, exposure to real-world working environments and demands, and access to partners’ research entrepreneurship teams.

The key asset of the Hertie School is the availability of a broad range of skills and experiences to address partners’ needs, challenges and opportunities.

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Services

The Data Science Lab also helps researchers across the Hertie School to accelerate their data-intensive research by bringing together people with different backgrounds and expertise and encouraging collaboration. This is supported through a set of services provided by the lab:

  • A Data Lab Help Desk is available for students and researchers. It is staffed by the lab's IT specialist who provides advice on statistical software for teaching or research, helps with debugging code, making data visualizations, and, more generally, provides support for any issue that can be resolved quickly.
  • Data Think Tanks are provided for researchers who have data and are looking for ideas and collaborators to help them increase the sophistication of their analytical methods.The lab organises brainstorming sessions that are attended by people with relevant expertise. During these sessions, the domain experts describe their data and the research questions that are interesting, and then they brainstorm together with participants who have expertise in data science methods (primarily but not limited to the Data Science Lab team). The aim is for these sessions to spark new research collaborations.
  • Community-building events are organised to bring people together and build community. Such events include data science talks, annual symposia, and roundtable discussions on specific topics related to data science and AI.