  Process management and process orchestration/execution are currently hot
topics; prevalent trends such as automation and Industry 4.0 require solutions
which allow domain-experts to easily model and execute processes in various
domains, including manufacturing and health-care. These domains, in turn, rely
on a tight integration between hardware and software, i.e. via the Internet of
Things (IoT). While process execution is about actuation, i.e. actively
triggering actions and awaiting their completion, accompanying IoT sensors
monitor humans and the environment. These sensors produce large amounts of
procedural, discrete, and continuous data streams, that hold the key to
understanding the quality of process subjects (e.g. produced parts), outcome
(e.g. quantity and quality), and error causes. Processes constantly evolve in
conjunction with their IoT environment. This requires joint storage of data
generated by processes, with data generated by the IoT sensors is therefore
needed. In this paper, we present an extension of the process log standard
format XES, namely SensorStream. SensorStream enables to connect IoT data to
process events, as well as a set of semantic annotations to describe the
scenario and environment during data collection. This allows to preserve the
full context required for data-analysis, so that logs can be analyzed even when
scenarios or hardware artifacts are rapidly changing. Through additional
semantic annotations, we envision the XES extension log format to be a solid
based for the creation of a (semi-)automatic analysis pipeline, which can
support domain experts by automatically providing data visualization, or even
process insights.
