BURIED DEEP: How data about subseafloor life becomes dark and why PETER DARCH REBEKAH CUMMINGS DEPARTMENT OF INFORMATION STUDIES UNIVERSITY OF CALIFORNIA, LOS ANGELES American geophysical union fall meeting 2013, san francisco http://explorationnow.org/atlantis/album/2013/07/21/recent-dive-operations

“Dark data” and the “long-tail” of science What is “dark data” (Heidorn 2008)? And “dark methods” Why is this important? Data Provenance Darch and Cummings, AGU Fall Meeting 2013

“Dark data” and the “long-tail” of science What is “dark data” (Heidorn 2008)? And “dark methods” Why is this important? Data Provenance Darch and Cummings, AGU Fall Meeting 2013

“Dark data” and the “long-tail” of science What is “dark data” (Heidorn 2008)? And “dark methods” Why is this important? Data Provenance Darch and Cummings, AGU Fall Meeting 2013

Darch and Cummings, AGU Fall Meeting 2013 Introducing C-DEBI National Science Foundation Science and Technology Center Interactions between subseafloor microbial life and geochemistry Individual and small group support for research https://sites.google.com/site/adoptamicrobe/home (Accessed 8 October 2013) Darch and Cummings, AGU Fall Meeting 2013 4

Darch and Cummings, AGU Fall Meeting 2013 Introducing C-DEBI National Science Foundation Science and Technology Center Interactions between subseafloor microbial life and geochemistry Individual and small group support for research https://sites.google.com/site/adoptamicrobe/home (Accessed 8 October 2013) Darch and Cummings, AGU Fall Meeting 2013 4

Darch and Cummings, AGU Fall Meeting 2013 Introducing C-DEBI National Science Foundation Science and Technology Center Interactions between subseafloor microbial life and geochemistry Individual and small group support for research https://sites.google.com/site/adoptamicrobe/home (Accessed 8 October 2013) Darch and Cummings, AGU Fall Meeting 2013 4

Darch and Cummings, AGU Fall Meeting 2013 CRUISES International Ocean Drilling Program (IODP) University-National Oceanographic Laboratory System (UNOLS) Samples Personal photo Samples BIOLOGICAL ANALYSES IN THE LABORATORY Quantification, Community structure, Community composition, Function Iodp.tamu.org PHYSICAL ANALYSES IN THE LABORATORY Crystallographic Mineralogical Chemical Geological Extraction of DNA/RNA Low biomass PCR, amplification Choice of sequencing facilities (commercial, university) Choice of sequencing methods Sequencing Cleaning sequences, classifying sequences, Phylogenies, community comparisons etc. Online databases Choice of bioinformatics tools (commercial, free, created by researcher) LAB-GENERATED PHYSICAL DATA ON-BOARD GEOCHEMICAL DATA BIOINFORMATICS DATA Darch and Cummings, AGU Fall Meeting 2013

Darch and Cummings, AGU Fall Meeting 2013 Biological data generated in laboratory (e.g. DNA sequences, proteomic data) Social scale IODP Disciplinary Institutional Journal C-DEBI Leaves laboratory Leaves field/ academia Data/laboratory notebook retention ends Mid-range UNOLS Publishes paper Lab Local Months One to a few years Indefinite Time horizon LOST DATA Darch and Cummings, AGU Fall Meeting 2013

Darch and Cummings, AGU Fall Meeting 2013 Physical data generated in laboratory (e.g. mineralogical, geochemical) Social scale IODP Disciplinary Institutional Journal C-DEBI Leaves laboratory Leaves field/ academia Data/laboratory notebook retention ends Mid-range UNOLS Publishes paper Lab Local Weeks/ months One to a few years Indefinite Time horizon LOST DATA Darch and Cummings, AGU Fall Meeting 2013

What happens to laboratory data? Scientists immediate needs Darch and Cummings, AGU Fall Meeting 2013

What happens to laboratory data? Scientists immediate needs Some in disciplinary databases Darch and Cummings, AGU Fall Meeting 2013

What happens to laboratory data? Scientists immediate needs Some in disciplinary databases Other data discovery Darch and Cummings, AGU Fall Meeting 2013

What makes data and methods “dark”?: Data use in other contexts Darch and Cummings, AGU Fall Meeting 2013

What makes data and methods “dark”?: Data use in other contexts Networking and serendipitous encounters Darch and Cummings, AGU Fall Meeting 2013

What makes data and methods “dark”?: Data use in other contexts Networking and serendipitous encounters Short-term research grants Darch and Cummings, AGU Fall Meeting 2013

What makes data and methods “dark”?: Data use in other contexts Networking and serendipitous encounters Short-term research grants Standardization of data practices Darch and Cummings, AGU Fall Meeting 2013

Darch and Cummings, AGU Fall Meeting 2013 Conclusions “Dark data” And “dark methods” Heterogeneity Important that methods do not become “dark” Makes methods more likely to become “dark” Darch and Cummings, AGU Fall Meeting 2013

Darch and Cummings, AGU Fall Meeting 2013 Conclusions “Dark data” And “dark methods” Heterogeneity Important that methods do not become “dark” Makes methods more likely to become “dark” Darch and Cummings, AGU Fall Meeting 2013

Darch and Cummings, AGU Fall Meeting 2013 Conclusions “Dark data” And “dark methods” Heterogeneity Important that methods do not become “dark” Makes methods more likely to become “dark” Darch and Cummings, AGU Fall Meeting 2013

And thank you for listening Acknowledgements Those scientists who have participated in our research Sloan Foundation (Award #20113194) National Science Foundation (Award #1216879) Other members of the Knowledge Infrastructures team at UCLA (PI Prof Christine Borgman, Co-PI Prof Sharon Traweek) And thank you for listening Darch and Cummings, AGU Fall Meeting 2013