Publications

[1]
D. S. Katz, F. E. Psomopoulos, and L. J. Castro, “Working Towards Understanding the Role of FAIR for Machine Learning,” DaMaLOS 2021, Oct. 2021.
[1]
K. McHenry, “EarthCube GeoCODES - Data Plus X Towards a Geoscience Scientific Gateway,” Gateways 2021, Oct. 2021.
[1]
D. LeBauer, M. Burnette, N. Fahlgren, R. Kooper, K. McHenry, and A. Stylianou, “What Does TERRA-REF’s High Resolution, Multi Sensor Plant Sensing Public Domain Data Offer the Computer VisionCommunity?,” Virtual, Oct-2021.
[1]
T. Nicholson et al., “Creating a Permafrost Discovery Gateway - Providing Researchers and the Public withaccess to arctic data,” Gateways 2021, Oct. 2021.
[1]
D. S. Katz, K. McHenry, and J. Lee, “Senior  level  RSE  career  paths,” Virtual, 27-Sep-2021 [Online]. Available: https://danielskatzblog.wordpress.com/2021/09/27/senior-rse-paths
[1]
D. S. Katz, K. McHenry, and J. Lee, “Senior  level  RSE  career  paths,” Virtual, Sep-2021 [Online]. Available: ttps://septembrse.society-rse.org
[1]
V. Sagan et al., “Data-Driven Artificial Intelligence for Calibration of Hyperspectral Big Data,” IEEE Transactions on Geoscience and Remote Sensing, Jul. 2021, doi: 10.1109/TGRS.2021.3091409. [Online]. Available: https://ieeexplore.ieee.org/document/9486501
[1]
E. A. Huerta et al., “Accelerated, scalable and reproducible AI-driven gravitational wave detection,” Nature Astronomy, Jul. 2021, doi: https://doi.org/10.1038/s41550-021-01405-0.
[1]
R. Smith et al., “Longitudinal assessment of diagnostic test performance over the course of acute SARS-CoV-2 infection,” The Journal of Infectious Diseases, no. jiab337, Jun. 2021, doi: https://doi.org/10.1093/infdis/jiab337.
[1]
N. Kenyon et al., “Extended Survival vs Accelerated Rejection of Nonhuman Primate Islet Allografts:  Effect of Mesenchymal Stem Cell Source and Timing,” American Journal of Transplantation, Jun. 2021.
[1]
C. Kirkpatrick et al., “National and International Trends in Research Storage at Scale.” San Diego Super Computer Center, University of California, San Diego, 12-Mar-2021 [Online]. Available: http://library.ucsd.edu/dc/object/bb8676950x/_1.pdf
[1]
S. L. Brantley et al., “The future low-temperature geo-chemical data-scape as envisioned by the U.S. geochemical community,” Computers & Geosciences,2021., 2021.
[1]
Y. Babuji et al., “Federated Function as a Service for eScience,” eScience, 2021, doi: https://doi.org/10.1109/eScience51609.2021.00046.
[1]
A. Villarreal, Y. Babuji, T. Uram, D. S. Katz, K. Chard, and K. Heitmann, “Extreme Scale Survey Simulation with Python Workflows,” eScience, 2021, doi: https://doi.org/10.1109/eScience51609.2021.00031.
[1]
A. Villarreal et al., “A High Performance Python-based Workflow for Sky Survey Simulations,” presented at the 17th IEEE International Conference on eScience 2021, 2021.
[1]
C. Kirkpatrick, K. Coakley, M. Cragin, J. Glasgow, and J. Goodhue, “Research Drivers and Capabilities.” San Diego Supercomputer Center, University of California, San Diego, 07-Dec-2020 [Online]. Available: http://library.ucsd.edu/dc/object/bb7106971q/_1.pdf
[1]
N. Makhoul, C. Navarro, J. S. Lee, and P. Gueguen, “A comparative study of buried pipeline fragilities using the seismic damage to the Byblos wastewater network.,” International Journal of Disaster Rick Reduction, vol. 51, Dec. 2020, doi: https://doi.org/10.1016/j.ijdrr.2020.101775. [Online]. Available: https://www.sciencedirect.com/science/article/abs/pii/S2212420920312772
[1]
N. Makhoul, C. Navarro, and J. Sung Lee, “Seismic estimation of casualties and direct economic loss to Byblos city: a contribution to the ‘100 resilient cities’ strategy.,” Sustainable and Resilient Infrastructure, Apr. 2020, doi: https://doi.org/10.1080/23789689.2020.1745531.
[1]
L. Wang et al., “Community resilience assessment of an EF-5 tornado using the IN-CORE modeling environment,” in Life-Cycle Civil Engineering: Innovation, Theory and Practice, 1st ed., vol. 1, CRC Press, 2020 [Online]. Available: https://www.taylorfrancis.com/chapters/edit/10.1201/9780429343292-49/community-resilience-assessment-ef-5-tornado-using-core-modeling-environment-wang-van-de-lindt-cutler-rosenheim-koliou-lee-calderon
[1]
B. Stalder, K. Reil, C. Claver, M. Liang, S. Pietrowicz, and H.-K. Win, “Rubin commissioning camera: integration, functional testing, and lab performance,” SPIE 11447, vol. 11447, 2020, doi: 10.1117/12.2561132.
[1]
B. Galewsky, R. Gardner, L. Gray, M. Neubauer, and J. Pivarski, “ServiceX A Distributed, Caching, Columnar Data Delivery Service,” EPJ Web Conf. 245 (2020), 2020 [Online]. Available: https://www.epj-conferences.org/articles/epjconf/abs/2020/21/epjconf_chep2020_04043/epjconf_chep2020_04043.html
[1]
C. Blatti III et al., “Knowledge-guided analysis of ‘omics’ data using the KnowEnG cloud platform,” PLOS Biology, 2020, 2020 [Online]. Available: https://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.3000583
[1]
J. Zwart et al., “Reproducible Forecasting Workflows,” Ecological Forecasting Intiative Blog, 2020, 2020 [Online]. Available: https://ecoforecast.org/introducing-efi-task-views
[1]
L. Angrave et al., “Improving student accessibility, equity, course performance, and lab skills:How introduction of ClassTranscribe is changing engineering education at the University of Illinois,” ASEE 2020, 2020 [Online]. Available: https://www.asee.org/public/conferences/172/papers/29904/view
[1]
L. Shinn et al., “" Fecal Bacteria as Biomarkers for Predicting Food Intake in Healthy Adults,” Journal of Nutrition, October 2020, 2020 [Online]. Available: https://academic.oup.com/jn/advance-article/doi/10.1093/jn/nxaa285/5918305
[1]
B. Smith et al., “Identification of early liver toxicity gene biomarkers using comparative supervised machine learning,” Nature, November 2020, 2020 [Online]. Available: https://www.nature.com/articles/s41598-020-76129-8
[1]
D. Katz, J. Lee, and K. McHenry, “Research Software Sustainability: Lessons Learned at NCSA,” Hawaii International Conference on System Sciences (HICSS), 2020 [Online]. Available: http://hdl.handle.net/10125/71494
[1]
S. Brantley et al., “A Vision for the Future Low-Temperature Geochemical Data-scape,” EarthArXiv 2020, 2020 [Online]. Available: https://eartharxiv.org/repository/view/1839/
[1]
L. Marini, C. Wehmeier, K. Hass, S. P. Satheesan, and M. Slavenas, “Supporting Broad Data Management and Sharing with the Clowder Framework,” Museum Big Data 2020, 2020.
[1]
E. Huerta et al., “Convergence of artificial intelligence and high performance computing on NSF‑supported cyberinfrastructure,” Journal of Big Data 2020, no. Article 88, 2020 [Online]. Available: https://journalofbigdata.springeropen.com/articles/10.1186/s40537-020-00361-2
[1]
K. Rubin et al., “Recommended Standards and Specifications for EarthCube Projects,” EarthCube Leadership Council 2020, 2020 [Online]. Available: https://library.ucsd.edu/dc/object/bb7786965d
[1]
K. McHenry, D. Fulker, D. Katz, M. Daniels, and C. Kirkpatrick, “From Papers to Notebooks: Submission, Review, Presentation & Publication of Notebooks at EarthCube’20,” JupyterCon 2020, 2020 [Online]. Available: https://cfp.jupytercon.com/2020/schedule/presentation/258/from-papers-to-notebooks-submission-review-presentation-publication-of-notebooks-at-earthcube20/
[1]
K. McHenry, D. Fulker, D. Katz, M. Daniels, and C. Kirkpatrick, “From Papers to Notebooks Submission, Review, Presentation & Publication of Notebooks at EarthCube’20,” Research Data Alliance 2020: BoF - Computational Notebooks, 2020.
[1]
McHenry, K., Fulker, D, Katz, D, and Kirkpatrick, C., “Jupyter Notebooks as a tool to increase Visibility of EarthCube Products,” American Geophysical Union Fall Meeting, 2020, 2020 [Online]. Available: https://agu.confex.com/agu/fm20/webprogram/Paper775046.html
[1]
Liljedahl, Anna et al., “Permafrost Discovery Gateway: A web platform to enable discovery and knowledge-generation of permafrost Big Imagery products,” American Geophysical Union Fall Meeting, 2020 [Online]. Available: https://agu.confex.com/agu/fm20/webprogram/Paper770791.html
[1]
Z. Ivezic, S. Kahn, and J. A. Tyson, “LSST: From Science Drivers to Reference Design and Anticipated Data Products,” The Astrophysical Journal, March 2019, no. 873, 2019, doi: 10.3847/1538-4357/ab042c. [Online]. Available: LSST: From Science Drivers to Reference Design and Anticipated Data Products
[1]
B. Galewsky et al., “ServiceX - A Distributed, Caching, Columnar Data Delivery Service,” 2019 [Online]. Available: https://indico.cern.ch/event/773049/contributions/3474438/
[1]
B. Zhang and T. Kosar, “SMURF: Efficient and Scalable Metadata Access for Distributed Applications from Edge to the Cloud,” IEEE International Conference on Edge Computing (EDGE), 2019 [Online]. Available: https://ieeexplore.ieee.org/document/8812196
[1]
S. P. Satheesan et al., “Extensible Framework for Analysis of Farm Practices and Programs,” PEARC, 2019.
[1]
S. Puthanveetil, A. Craig, and Y. Zhang, “A Historical Big Data Analysis to Understand the Social Construction of Juvenile Delinquency in the United States,” eScience, 2019.
[1]
C. Wang et al., “Social Media Intelligence and Learning Environment: an Open Source Framework for Social Media Data Collection, Analysis and Curation,” eScience, 2019.
[1]
C. Willis, M. Lambert, R. Kalyanam, K. Coakley, K. McHenry, and C. Kirkpatrick, “Labs Workbench: A Scalable Platform for Research Data Access, Education, and Training,” SCGI, 2019.
[1]
P. Kumar, L. Marini, M. Pitcel, L. Keefer, and K. McHenry, “Design of an Observatory Data System and Open Source Sharing with Active Curation and Machine Learning,” GSA, 2019.
[1]
K. Chard et al., “Implementing Computational Reproducibility in the Whole Tale Environment,” P-RECS’19, 2019.
[1]
D. Katz, K. McHenry, C. Reinking, and R. Haines, “Research Software Development & Management in Universities: Case Studies from Manchester’s RSDS Group, Illinois’ NCSA, and Notre Dame’s CRC,” ACM/IEEE International Conference on Software Engineering, International Workshop on Software Engineering for Science (SE4Science), 2019.
[1]
P. Nguyen et al., “Bracelet: Edge-Cloud Microservice Infrastructure for Aging Scientific Instruments,” International Conference on Computing, Networking and Communications (ICNC), 2019.
[1]
T. Jenness, F. Economou, W. O’Mullane, B. van Klaveren, and S. Pietrowicz, “LSST data management software development practices and tools,” Software and Cyberinfrastructure for Astronomy V, July 2018, 2018, doi: 10.1117/12.2312157. [Online]. Available: https://docushare.lsst.org/docushare/dsweb/Get/Document-28452
[1]
N. Attary et al., “Hindcasting community-level building damage for the 2011 Joplin EF5 tornado,” Natural Hazards, 2018, vol. 93, pp. 1295–1316, 2018 [Online]. Available: https://link.springer.com/article/10.1007/s11069-018-3353-5
[1]
R. Kooper et al., “Developing and Adapting Data Management Services Across Multiple Virtual Observatories,” AGU, 2018.
[1]
L. Marini et al., “Using Docker to Ease the Sharing and Running of Code in the PEcAn Project,” AGU, 2018.