Software Project Management for Combined Software and Data Engineering

Software engineering is an established discipline for the systematic creation of large and complex software systems. Relatively more recent are attempts to systematise the creation and management of large data sets, in data engineering. A key feature of these disciplines is managing engineering processes using several stages that form a development life cycle. This leads to a methodical process for development and separation of work into modular elements. A challenge when using this approach is integrating software engineering life cycles with the wider context of the software, for example, business processes, user requirements or indeed other codependent development life cycles. This chapter is on combining software engineering with data engineering to enable better project management, foster reuse and harness best practice from two seeming disparate domains. The presented methodology is created from experiences on the ALIGNED project, a large, interdisciplinary research project that applies state-of-the-art software and data engineering techniques for the development of real-world systems. Several use cases have been identified that are challenging due to a lack of coherence between the software and data engineering, from collection and management of anthropological research to cataloguing and exploration of jurisprudence data and machine interpretation of large encyclopaedic data sets. In the project, several state-of-the-art tools are under development from both domains such as Booster [1], the Model Catalogue [2], RDFUnit [3], Repair Framework and Notification (RFN), Ontology Repair and Enrichment (ORE), Dacura [4], the PoolParty Confluence/JIRA Data Extractor (CJDE) [5] and External