Effective and efficient maintenance requires a proper information logistics, which can be delivered through eMaintenance solutions. Development of eMaintenance solutions faces extensive challenges. One of these challenges is how to ensure the quality of data used in different eMaintenance solutions. Data Quality (DQ) concerns all phases of the maintenance process.

The purpose of this paper is to answer the research question: How should DQ be considered and managed when developing eMaintenance solutions?

To deal with such challenges a case study was conducted at a mining company. Empirical data has been collected through interviews, observations, archival records and workshops.

The data analysis has been based on an empirical framework that supports the identification of required information services. Conditions that support the DQ and the information logistics, along with that, support the maintenance process have been presented. These aspects have also been related to the phases of a generic maintenance process.