Quantitative Surface Analysis (QSA 17)
"Data Reproducibility Challenges"
Sunday, October 21, 7:30 AM - 3:00 PM
Long Beach Convention Center
Cost: $150 General Admission and $50 for Students
Registration includes continental breakfast and lunch
Have you tried to reproduce published scientific experiments, but found it difficult to achieve the same results? Have you struggled with a lack of experimental detail in journal articles? Why do I get different results when I use materials from different suppliers? What are the steps I can take to thoroughly document and report my experiments? These are issues of data reproducibility that have been receiving notice around the world. Through invited speakers, panel discussions and audience participation, we will delve into this topic first by introducing the breadth and depth of the issue and how it applies to AVS technologies. AVS Journal Editors will lead a panel discussion on the topic, and then invited speakers will provide practical advice on how to perform and document reproducible experiments by: utilizing standards appropriately, understanding starting materials, preparing samples and analyzing samples in a reproducible way and then documenting these procedures in a way that can be duplicated by others. Real examples and case studies will be presented with generous time for discussion.
Invited Speakers include (but are not limited to):
Don Baer (PNNL)
Mark Engelhard (PNNL)
Jeff Fenton (Medtronic)
Ian Gilmore (NPL)
Wolfgang Unger (BAM)
Amy Walker (UTD)
The conference takes place on Sunday, October 21st at the AVS 65 conference venue. Registration costs $150 and $50 for students. Registration includes continental breakfast and lunch. The conference will end at 3pm so that you can attend the Biomaterials Plenary session. Registration is easy! Register for QSA17 when you register for AVS 65!
Who should attend?
Contributed posters are being accepted and encouraged.
Students, postdocs, professors, government and industry scientists alike who have experienced the problem and strive to produce quantitative experimental data and document it in a way that others can reproduce.
Contact Tony Ohlhausen (firstname.lastname@example.org
) to submit a poster.