Huge amount of data is collected and entered into computer systems by humans and machines during various operations and services both in industrial companies and public organisations. Unfortunately, these data often contain errors or they can be interpreted in many different ways by various users during the information production process. This is a problem because the validity and consequences of decisions depend on the quality and meaning of the data they are based on.


The project aims to improve the validity of decisions by creating methods and building knowledge for managing and developing information production processes. To improve the validity of decisions information should be managed transparently across all organizational
processes and units to improve its trustworthiness and validity.


The project delivers both academic and industrial results. Academic results are new models and methods about improved means of managing the quality of data. Industrial and practical results are gained through the real-life case studies that provide empirical data for the creation and validation of the models.

Research questions

  1. How to recognize and model data quality across information production processes?
  2. What kind of effects do data quality errors have on decision making?
  3. How could valuable information be offered more transparently and simultaneously for various uses and users?
  4. How to prevent and fix identified data quality errors to guarantee the validity of decisions?
  5. What is the effect of usability of data entry systems on data quality?


The project started in 1.9.2012 and continues to 31.12.2014. It is funded by Tekes – the Finnish Funding Agency for Technology and Innovation.