Publications

[1]
C. Jay et al., “Theory-Software Translation: Research Challenges and Future Directions,” arXiv:1910.09902 [cs], Oct. 2019 [Online]. Available: http://arxiv.org/abs/1910.09902. [Accessed: 23-Oct-2019]
[1]
E. A. Huerta et al., “Enabling real-time multi-messenger astrophysics discoveries with deep learning,” Nat Rev Phys, vol. 1, no. 10, pp. 600–608, Oct. 2019 [Online]. Available: https://www.nature.com/articles/s42254-019-0097-4. [Accessed: 03-Oct-2019]
[1]
A. E. Ahmed et al., “Managing genomic variant calling workflows with Swift/T,” PLOS ONE, vol. 14, no. 7, p. e0211608, Jul. 2019 [Online]. Available: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0211608. [Accessed: 10-Jul-2019]
[1]
D. S. 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,” in 2019 IEEE/ACM 14th International Workshop on Software Engineering for Science (SE4Science), 2019, pp. 17–24.
[1]
D. S. Katz, S. Druskat, R. Haines, C. Jay, and A. Struck, “The State of Sustainable Research Software: Learning from the Workshop on Sustainable Software for Science: Practice and Experiences (WSSSPE5.1),” Journal of Open Research Software, vol. 7, no. 1, p. 11, Apr. 2019 [Online]. Available: http://openresearchsoftware.metajnl.com/articles/10.5334/jors.242/. [Accessed: 02-Apr-2019]
[1]
E. A. Huerta, R. Haas, S. Jha, M. Neubauer, and D. S. Katz, “Supporting High-Performance and High-Throughput Computing for Experimental Science,” Comput Softw Big Sci, vol. 3, no. 1, p. 5, Feb. 2019 [Online]. Available: https://doi.org/10.1007/s41781-019-0022-7. [Accessed: 08-Feb-2019]
[1]
D. Sholler, K. Ram, C. Boettiger, and D. S. Katz, “Enforcing public data archiving policies in academic publishing: A study of ecology journals,” Big Data & Society, vol. 6, no. 1, p. 2053951719836258, Jan. 2019 [Online]. Available: https://doi.org/10.1177/2053951719836258. [Accessed: 01-Apr-2019]
[1]
M. Barker et al., “The global impact of science gateways, virtual research environments and virtual laboratories,” Future Generation Computer Systems, 2019 [Online]. Available: https://linkinghub.elsevier.com/retrieve/pii/S0167739X18314018. [Accessed: 04-Jan-2019]
[1]
Y. Babuji et al., “Scalable Parallel Programming in Python with Parsl,” in Proceedings of the Practice and Experience in Advanced Research Computing on Rise of the Machines (Learning), New York, NY, USA, 2019, pp. 22:1–22:8 [Online]. Available: http://doi.acm.org/10.1145/3332186.3332231. [Accessed: 04-Sep-2019]
[1]
Y. Babuji et al., “Parsl: Pervasive Parallel Programming in Python,” in Proceedings of the 28th International Symposium on High-Performance Parallel and Distributed Computing, New York, NY, USA, 2019, pp. 25–36 [Online]. Available: http://doi.acm.org/10.1145/3307681.3325400. [Accessed: 13-Jul-2019]
[1]
D. S. Katz et al., “The principles of tomorrow’s university,” F1000Research, vol. 7, p. 1926, Dec. 2018 [Online]. Available: https://f1000research.com/articles/7-1926/v1. [Accessed: 04-Jan-2019]
[1]
M. D. Hildreth et al., “HEP Software Foundation Community White Paper Working Group - Data and Software Preservation to Enable Reuse,” arXiv:1810.01191 [physics], Oct. 2018 [Online]. Available: http://arxiv.org/abs/1810.01191. [Accessed: 09-Oct-2018]
[1]
S. Druskat and D. S. Katz, “Mapping the Research Software Sustainability Space,” in 2018 IEEE 14th International Conference on e-Science (e-Science), 2018, pp. 25–30.
[1]
J. Cohen, D. S. Katz, M. Barker, R. Haines, and N. C. Hong, “Building a Sustainable Structure for Research Software Engineering Activities,” in 2018 IEEE 14th International Conference on e-Science (e-Science), 2018, pp. 31–32.
[1]
M. L. Mondelli et al., “BioWorkbench: a high-performance framework for managing and analyzing bioinformatics experiments,” PeerJ, vol. 6, p. e5551, Aug. 2018 [Online]. Available: https://peerj.com/articles/5551. [Accessed: 29-Aug-2018]
[1]
D. S. Katz and N. P. C. Hong, “Software Citation in Theory and Practice,” in Mathematical Software – ICMS 2018, 2018, pp. 289–296 [Online]. Available: https://link.springer.com/chapter/10.1007/978-3-319-96418-8_34. [Accessed: 21-Jul-2018]
[1]
H. S. Foundation et al., “HEP Software Foundation Community White Paper Working Group - Training, Staffing and Careers,” arXiv:1807.02875 [hep-ex, physics:physics], Jul. 2018 [Online]. Available: http://arxiv.org/abs/1807.02875. [Accessed: 10-Jul-2018]
[1]
S. Druskat and D. S. Katz, “Mapping the research software sustainability space,” arXiv:1807.01772 [cs], Jul. 2018 [Online]. Available: http://arxiv.org/abs/1807.01772. [Accessed: 10-Jul-2018]
[1]
D. S. Katz et al., “Fourth Workshop on Sustainable Software for Science: Practice and Experiences (WSSSPE4),” Journal of Open Research Software, vol. 6, no. 1, Feb. 2018 [Online]. Available: http://openresearchsoftware.metajnl.com/articles/10.5334/jors.184/. [Accessed: 15-Feb-2018]
[1]
A. M. Smith et al., “Journal of Open Source Software (JOSS): design and first-year review,” PeerJ Comput. Sci., vol. 4, p. e147, Feb. 2018 [Online]. Available: https://peerj.com/articles/cs-147. [Accessed: 13-Feb-2018]
[1]
D. S. Katz, K. E. Niemeyer, and A. M. Smith, “Publish Your Software: Introducing the Journal of Open Source Software (JOSS),” Computing in Science & Engineering, vol. 20, no. 3, pp. 84–88, 2018 [Online]. Available: https://ieeexplore.ieee.org/document/8358035/. [Accessed: 21-May-2018]
[1]
J. C. Carver, S. Gesing, D. S. Katz, K. Ram, and N. Weber, “Conceptualization of a US Research Software Sustainability Institute (URSSI),” Computing in Science & Engineering, vol. 20, no. 3, pp. 4–9, 2018 [Online]. Available: https://ieeexplore.ieee.org/document/8358036/. [Accessed: 21-May-2018]
[1]
Y. Babuji et al., “Parsl: Scalable Parallel Scripting in Python,” in 10th International Workshop on Science Gateways (IWSG 2018), Edinburgh, Scotland, 2018 [Online]. Available: http://ceur-ws.org/Vol-2357/paper11.pdf
[1]
D. S. Katz et al., “Community Organizations: Changing the Culture in Which Research Software Is Developed and Sustained,” Computing in Science Engineering, pp. 1–1, 2018.
[1]
D. S. Katz, “Software Citations and the ACAT Community,” J. Phys.: Conf. Ser., vol. 1085, no. 2, p. 022010, 2018 [Online]. Available: http://stacks.iop.org/1742-6596/1085/i=2/a=022010. [Accessed: 30-Oct-2018]
[1]
B. Couturier et al., “HEP Software Foundation Community White Paper Working Group - Software Development, Deployment and Validation,” arXiv:1712.07959 [hep-ex, physics:physics], Dec. 2017 [Online]. Available: http://arxiv.org/abs/1712.07959
[1]
A. A. Alves Jr et al., “A Roadmap for HEP Software and Computing R&D for the 2020s,” arXiv:1712.06982 [hep-ex, physics:physics], Dec. 2017 [Online]. Available: http://arxiv.org/abs/1712.06982
[1]
J. P. Tennant et al., “A multi-disciplinary perspective on emergent and future innovations in peer review,” F1000Research, vol. 6, p. 1151, Nov. 2017 [Online]. Available: https://f1000research.com/articles/6-1151/v3
[1]
U. Nangia and D. S. Katz, “Track 1 Paper: Surveying the U.S. National Postdoctoral Association Regarding Software Use and Training in Research.” 30-Aug-2017 [Online]. Available: https://figshare.com/articles/Track_1_Paper_Surveying_the_U_S_National_Postdoctoral_Association_Regarding_Software_Use_and_Training_in_Research/5328442
[1]
A. M. Smith et al., “Journal of Open Source Software (JOSS): design and first-year review,” arXiv:1707.02264 [cs], Jul. 2017 [Online]. Available: http://arxiv.org/abs/1707.02264
[1]
R. C. Jiménez et al., “Four simple recommendations to encourage best practices in research software,” F1000Research, vol. 6, p. 876, Jun. 2017 [Online]. Available: https://f1000research.com/articles/6-876/v1
[1]
D. S. Katz et al., “Report on the Fourth Workshop on Sustainable Software for Science: Practice and Experiences (WSSSPE4),” arXiv:1705.02607 [cs], May 2017 [Online]. Available: http://arxiv.org/abs/1705.02607
[1]
S. Jha, D. S. Katz, A. Luckow, N. Chue Hong, O. Rana, and Y. Simmhan, “Introducing distributed dynamic data-intensive (D3) science: Understanding applications and infrastructure,” Concurrency Computat.: Pract. Exper., vol. 29, no. 8, p. n/a-n/a, Apr. 2017 [Online]. Available: http://onlinelibrary.wiley.com/doi/10.1002/cpe.4032/abstract
[1]
T. Clark, H. Cousijn, D. S. Katz, and M. Fenner, “Open Science strategies for NIH data management, sharing, and citation,” PeerJ Preprints, e2836v1, Mar. 2017 [Online]. Available: https://peerj.com/preprints/2836. [Accessed: 12-Jul-2017]
[1]
K. Chard, S. Caton, K. Kugler, O. Rana, and D. S. Katz, “A social content delivery network for e-Science,” Concurrency Computat.: Pract. Exper., vol. 29, no. 4, p. n/a-n/a, Feb. 2017 [Online]. Available: http://onlinelibrary.wiley.com/doi/10.1002/cpe.3854/abstract
[1]
J. M. Wozniak, J. Ozik, D. S. Katz, and M. Wilde, “Streaming supercomputing needs workflow-enabled programming-in-the-large,” arXiv:1702.07425 [cs], Feb. 2017 [Online]. Available: http://arxiv.org/abs/1702.07425
[1]
K. Maheshwari, D. Katz, S. D. Olabarriaga, J. Wozniak, and D. Thain, “Report on the first workshop on negative and null results in eScience,” Concurrency Computat.: Pract. Exper., vol. 29, no. 2, p. n/a-n/a, Jan. 2017 [Online]. Available: http://onlinelibrary.wiley.com/doi/10.1002/cpe.3908/abstract
[1]
U. Nangia and D. S. Katz, “Understanding Software in Research: Initial Results from Examining Nature and a Call for Collaboration,” 2017, pp. 486–487 [Online]. Available: http://ieeexplore.ieee.org/document/8109183/. [Accessed: 05-Dec-2017]
[1]
M. Turilli et al., “Evaluating Distributed Execution of Workloads,” 2017, pp. 276–285 [Online]. Available: http://ieeexplore.ieee.org/document/8109146/. [Accessed: 05-Dec-2017]
[1]
E. A. Huerta et al., “BOSS-LDG: A Novel Computational Framework That Brings Together Blue Waters, Open Science Grid, Shifter and the LIGO Data Grid to Accelerate Gravitational Wave Discovery,” 2017, pp. 335–344 [Online]. Available: http://ieeexplore.ieee.org/document/8109152/. [Accessed: 05-Dec-2017]
[1]
A. Allen et al., “Engineering Academic Software (Dagstuhl Perspectives Workshop 16252),” Dagstuhl Manifestos, vol. 6, no. 1, pp. 1–20, 2017 [Online]. Available: http://drops.dagstuhl.de/opus/volltexte/2017/7146
[1]
A. Marshall-Colon et al., “Crops In Silico: Generating Virtual Crops Using an Integrative and Multi-scale Modeling Platform,” Front. Plant Sci., vol. 8, 2017 [Online]. Available: http://journal.frontiersin.org/article/10.3389/fpls.2017.00786/full. [Accessed: 03-Jun-2017]
[1]
D. S. Katz, K. E. Niemeyer, and A. M. Smith, “Strategies for biomedical software management, sharing, and citation,” PeerJ Preprints, e2640v1, Dec. 2016 [Online]. Available: https://peerj.com/preprints/2640. [Accessed: 12-Jul-2017]
[1]
D. Katz et al., “Report on the Third Workshop on Sustainable Software for Science: Practice and Experiences (WSSSPE3),” Journal of Open Research Software, vol. 4, no. 1, Oct. 2016 [Online]. Available: http://openresearchsoftware.metajnl.com/article/10.5334/jors.118/. [Accessed: 04-Jun-2017]
[1]
K. E. Niemeyer, A. M. Smith, and D. S. Katz, “The Challenge and Promise of Software Citation for Credit, Identification, Discovery, and Reuse,” J. Data and Information Quality, vol. 7, no. 4, pp. 16:1–16:5, Oct. 2016 [Online]. Available: http://doi.acm.org/10.1145/2968452
[1]
A. M. Smith, D. S. Katz, and K. E. Niemeyer, “Software citation principles,” PeerJ Comput. Sci., vol. 2, p. e86, Sep. 2016 [Online]. Available: https://peerj.com/articles/cs-86. [Accessed: 04-Jun-2017]
[1]
M. Gamell et al., “Evaluating Online Global Recovery with Fenix Using Application-Aware In-Memory Checkpointing Techniques,” in 2016 45th International Conference on Parallel Processing Workshops (ICPPW), 2016, pp. 346–355 [Online]. Available: https://doi.org/10.1109/ICPPW.2016.56
[1]
Y. Perez-Riverol et al., “Ten Simple Rules for Taking Advantage of Git and GitHub,” PLOS Computational Biology, vol. 12, no. 7, p. e1004947, Jul. 2016 [Online]. Available: http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1004947. [Accessed: 04-Jun-2017]
[1]
Z. Zhang, D. S. Katz, A. Merzky, M. Turilli, S. Jha, and Y. Nand, “Application Skeleton: Generating Synthetic Applications for Infrastructure Research,” The Journal of Open Source Software, vol. 1, no. 1, May 2016 [Online]. Available: http://joss.theoj.org/papers/10.21105/joss.00017
[1]
“Sustaining Research Software: an SC18 Panel.” [Online]. Available: https://arxiv.org/abs/1902.08942. [Accessed: 27-Feb-2019]

ISDA

[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]
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]
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.
[1]
M. Ruiz et al., “A Prediction System for Vector-Borne Diseases : a Use Case for Weekly Estimation of West Nile Virus Risk,” AGU, 2018.
[1]
W. Thomas et al., “Petabytes in Practice: Working with Collections as Data at Scale,” Workshop on Cyberinfrastructure and Machine Learning for Digital Libraries and Archives, JCDL, 2018.
[1]
S. Satheesan et al., “Brown Dog: Making the Digital World a Better Place, a Few Files at a Time,” PEARC, 2018.
[1]
L. Marini et al., “Clowder: Open Source Data Management for Long Tail Data,” PEARC, 2018.
[1]
M. Burnette et al., “TERRA-REF Data Processing Infrastructure,” PEARC, 2018.
[1]
M. Simeone, C. Morris, K. McHenry, and R. Markley, “The Canoe and the Superpixel: Image Analysis of the Changing Shorelines on Historical Maps of the Great Lakes M. Simeone, C. Morris, K. McHenry, and R. Markley,” Journal18, 2018 [Online]. Available: http://www.journal18.org/issue5/the-canoe-and-the-superpixel-image-analysis-of-the-changing-shorelines-on-historical-maps-of-the-great-lakes/
[1]
D. Li, B. Deal, X. Zhou, M. Slavenas, and W. Sullivan, “Moving Beyond the Neighborhood: Daily Exposure to Nature and Adolescents’ Mood,” Landscape and Urban Planning, 2018 [Online]. Available: https://www.sciencedirect.com/science/article/pii/S0169204618300318
[1]
P. Suppakittpaisarn, B. Jiang, M. Slavenas, and W. Sullivan, “Does Density of Green Infrastructure Predict Preference?,” Urban Forestry & Urban Greening, 2018 [Online]. Available: https://www.researchgate.net/publication/323514146_DOES_DENSITY_OF_GREEN_INFRASTRUCTURE_PREDICT_PREFERENCE
[1]
R. Kooper, M. Burnette, J. Maloney, and D. LeBauer, “Data Flow for the TERRA-REF Project,” presented at the AGU, 2017.
[1]
S. Satheesan et al., “Brown Dog: A Data Transformation Ecosystem for Research - Advancing from Beta to 1.0,” presented at the AGU, 2017.
[1]
I. Gutierrez-Polo et al., “Monitoring Water Quality in the Great Lakes leveraging Geo-Temporal Cyberinfrastructure,” presented at the IEEE eScience, 2017.
[1]
A. Langmead, P. Rodriguez, S. Puthanveetil Satheesan, and A. Craig, “Extracting Meaningful Data from Decomposing Bodies,” presented at the PEARC, 2017.
[1]
A. Langmead, P. Rodriguez, S. Puthanveetil Satheesan, and A. Craig, “Extracting Meaningful Data from Decomposing Bodies,” in Workshop on Computer Vision in Digital Humanities, Digital Humanities, 2017.