  Internet of Things Driven Data Analytics (IoT-DA) has the potential to excel
data-driven operationalisation of smart environments. However, limited research
exists on how IoT-DA applications are designed, implemented, operationalised,
and evolved in the context of software and system engineering life-cycle. This
article empirically derives a framework that could be used to systematically
investigate the role of software engineering (SE) processes and their
underlying practices to engineer IoT-DA applications. First, using existing
frameworks and taxonomies, we develop an evaluation framework to evaluate
software processes, methods, and other artefacts of SE for IoT-DA. Secondly, we
perform a systematic mapping study to qualitatively select 16 processes (from
academic research and industrial solutions) of SE for IoT-DA. Thirdly, we apply
our developed evaluation framework based on 17 distinct criterion (a.k.a.
process activities) for fine-grained investigation of each of the 16 SE
processes. Fourthly, we apply our proposed framework on a case study to
demonstrate development of an IoT-DA healthcare application. Finally, we
highlight key challenges, recommended practices, and the lessons learnt based
on framework's support for process-centric software engineering of IoT-DA. The
results of this research can facilitate researchers and practitioners to
engineer emerging and next-generation of IoT-DA software applications.
