  The iLCM project pursues the development of an integrated research
environment for the analysis of structured and unstructured data in a "Software
as a Service" architecture (SaaS). The research environment addresses
requirements for the quantitative evaluation of large amounts of qualitative
data with text mining methods as well as requirements for the reproducibility
of data-driven research designs in the social sciences. For this, the iLCM
research environment comprises two central components. First, the Leipzig
Corpus Miner (LCM), a decentralized SaaS application for the analysis of large
amounts of news texts developed in a previous Digital Humanities project.
Second, the text mining tools implemented in the LCM are extended by an "Open
Research Computing" (ORC) environment for executable script documents,
so-called "notebooks". This novel integration allows to combine generic,
high-performance methods to process large amounts of unstructured text data and
with individual program scripts to address specific research requirements in
computational social science and digital humanities.
