This paper introduces enterprise architecture (EA) traces, a new theoretical lens for collecting EA artifacts from web
sources to accelerate enterprise modeling. EA traces are defined as data publicly accessible on the web, providing
insights into an enterprise’s architecture, often without the originator’s awareness, offering a rich, yet complex
interpretive device for understanding the peculiarities and evolution of EA. This paper first conceptualizes EA
traces, then performs an integrative review encompassing 119 eligible records. The objective of this review was to
identify which enterprise-related insights have been previously derived from web data, and whether they can be
mapped to EA artifacts. The results reveal promising coverage across architecture layers and substantial potential
for extension. Despite this, the approach lacks methodological guidance and remains highly subjective. Therefore,
a three-step method is proposed drawing on ontology mapping. Utilizing selected studies from the review, the
feasibility of this method is demonstrated by deriving employees’ competencies from LinkedIn profiles. The
paper concludes with a research agenda to guide future work on EA traces.