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Principles and guidelines on handling research data at Bielefeld University

Researchers at Bielefeld University should treat research data* as valuable academic work in line with the following principles:

  • Across the entire data lifecycle – from data collection to publication – research data should be handled and documented diligently and according to appropriate subject-specific standards
  • Each Project Investigator (PI) should provide a data management plan in line with the given subject-specific guidelines for institutions and projects – particularly for each new data-intensive research proposal  
  • Research data management in institutions and projects should aim towards making data  widely available and retaining it for the long term in order to facilitate its reuse for research, practice, and the general public while simultaneously balancing the need to protect intellectual property rights, personal data, and obligations to third parties
  • To promote a sustained embedment and development of high-quality research data management, both teaching and further training should pay sufficient attention to subject-specific training in methods and the principles of good academic practice
--- *In a broader sense, the term research data refers to any primary data, secondary analyses, visualizations, models, analysis tools, collections of objects or products that are generated and used during the academic research lifecycle.