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Internal network of experts Bundling big data competencies across the disciplines 

Data Worlds makes the competencies of big data experts ("scouts") more visible internally and externally, and the knowledge of these scouts is also available to external project partners.

Exploiting synergies

The full value of data becomes apparent only once experts have identified its significance and extracted the information it contains. With this in mind, Data Worlds serves as a venue for data experts to gather and where laypeople can identify the potential in their data, formulate data-driven research questions, and work with specialists to devise solutions.

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It is dedicated to communicating the competencies that scouts at Lucerne University of Applied Sciences and Arts have in these fields for the benefit of internal and external partners. In addition, the expertise of its scouts should be made available to external project partners that so far have had little experience with innovative forms of data use. The advantages include:

  • Stretching the horizon: Data Worlds shows laypersons the possibilities that arise when high quality data is combined with the right forms of expertise.
  • The scouts of Data Worlds invest a lot of time and effort into evaluating the trends, methods and technologies used in connection with data, and they subsequently pass on this knowledge to internal and external interest groups.
  • Basic research: Good research means asking good questions, which is precisely where Data Worlds scouts excel. They will study a problem in detail and then suggest a number of data-driven questions and solutions.
  • Curated data: In order to carry out analyses, it is necessary to first organise the data properly. Data Worlds therefore provides experts who are highly skilled in straightening out the often muddled contents of databases.

data innovation

Data offers enormous potential for product innovations and for optimising processes. At the same time, the ability to recognise this potential requires not only knowledge of the data and expertise in its application, it also calls for effective use of innovation methods.

data collection / integration / extracion

When gathering information, it is often necessary to combine heterogeneous data obtained from disparate data collections. With new data sources becoming available continuously – especially with the increasing use of mobile devices and sensor technologies, the ability to process unstructured text, image and audio data is also increasingly gaining in importance.

data analyses / interaction

Merely gathering large quantities of data is of little use. Only once data has been prepared properly and its information and knowledge extracted and made available comprehensibly and easily will users and decision-makers be able to act in an informed manner.

Data (Knowledge) Management

Data-driven business models require companies to adopt a holistic approach to generating value from data – from entering raw data, extracting the information, or applying the newly gained knowledge.

data and society

The increase in digitalisation and datafication of the world we live in raises an entirely new set of questions about data security, protection of the private sphere, and ownership of personal and personalised data, among other things.