Matching Corporate Software Engineers and Data Offerings - from Discovery to Recommendations

Abstract

Data plays an essential role in developing software, especially in large and complex projects. Data can be collected from different stages of the software life cycle and can form the basis for decision-making and thereby the success of projects. With increasingly automated and tool-supported development landscapes, the amount of data that is generated and accessible rises as well. Large corporate software projects, in addition to generating data also give rise to a high volume of offerings based on the data. These aim to increase the value generated by stakeholders like developers, requirement engineers, and testers. The offering land-scape brings new complexities and difficulties with it and needs to be managed, systematized, and brought to the correct person at the right time in order to create value. In this publication, models for abstracting and generalizing data offerings and data consumers are presented and their applicability is verified in a global corporate software environment. In addition, approaches for matching data offerings and consumers are presented. Our results show that offerings and consumers can be abstracted and matched using a recommender system.