CFG Seminar: Computational Reproducibility vs Transparency

Professor Bertram Ludaescher will lead the session, "Computational Reproducibility vs Transparency: Are we barking up the wrong tree?"

The “reproducibility crisis” has resulted in much interest in methods and tools to improve computational reproducibility. FAIR data principles (data should be findable, accessible, interoperable, and reusable) are also being adapted and evolved to apply to other artifacts, notably computational analyses (scientific workflows, Jupyter notebooks, etc.) The current focus on computational reproducibility of scripts and other computational workflows sometimes overshadows a somewhat neglected and arguably more important issue: transparency of data analysis (including data wrangling and cleaning). To sort out things, I suggest we ask the question: What information is gained by conducting a reproducibility experiment?

The Conceptual Foundations Group (CFG) is an interest-based research group, centered around clarifying foundational concepts relating to information organization, data curation, and semantic technologies. Concepts related to the fundamental nature of information, descriptive metadata, digital objects and text markup are frequent topics. The group emphasizes the application of “formal methods” — that is, approaches that originated in logic, philosophy of language, analytic philosophy – to information science problem areas.

Questions? Contact Lan Li