Sense Making in the Digital World

Dear Colleagues,

Sense making is a process where large volumes of basic data, usually collected from different, heterogeneous sources, is set into perspective and yields new insights or a deeper understanding with respect to some topic. In particular, sense making is a way to look at data in light of a certain application domain or application-specific question. That includes the integration of data from different, possibly noisy sources, the selection of relevant data, and the exclusion of irrelevant data, making different pieces of information plausible with respect to prior hypotheses, and empirically testing whether conjectures derived from initial models over samples of data sources (usually of limited size and varying quality) also hold for real-world data. Basic techniques used for sense making, thus, include, but are not limited to, knowledge representation and meta-data enhancement, big data analytics, uncertainty and ambiguity management and resolution, as well as a variety of reasoning techniques from the field of the semantic web.

Consequently, modern intelligent and data-driven applications will always have to rely on components making sense of large sets of heterogeneous, diverse, and possibly noisy data from different sources. In order to actually build those applications and at the same time understand their behavior, on one hand, we need rigorous foundations for sense making on the data side, including means for semantic integration of data, assessment of data quality, etc. On the other hand, intelligent applications need engineering principles and methods considering the specific challenges of data-driven sense making components. In particular, test and verification techniques are required that ensure the quality of system results influenced by sense making.

This Special Issue is intended to bring together researchers in all fields of sense making, from foundations, via engineering and analysis, to applications.

Prof. Dr. Wolf-Tilo Balke
Prof. Dr. Ina Schaefer
Guest Editors

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• knowledge representation
• meta-data enhancement
• big data analytics
• semantic web
• software testing
• software verification