iLCM - A Virtual Research Infrastructure for Large-Scale Qualitative Data

Andreas Niekler; Arnim Bleier; Christian Kahmann; Lisa Posch; Gregor Wiedemann; Kenan Erdogan; Gerhard Heyer; Markus Strohmaier

arXiv · 1805.11404

iLCM - A Virtual Research Infrastructure for Large-Scale Qualitative Data

Andreas Niekler·Arnim Bleier·Christian Kahmann·Lisa Posch·Gregor Wiedemann·Kenan Erdogan·Gerhard Heyer·Markus Strohmaier

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Abstract

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.

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Andreas Niekler, Arnim Bleier, Christian Kahmann, Lisa Posch, Gregor Wiedemann, Kenan Erdogan, Gerhard Heyer, Markus Strohmaier. 2018-05-11. iLCM - A Virtual Research Infrastructure for Large-Scale Qualitative Data. https://arxiv.org/abs/1805.11404

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