| Analytics-driven data ingestion and derivation in the AWESOME polystore S Dasgupta, K Coakley, A Gupta 2016 IEEE International Conference on Big Data (Big Data), 2555-2564, 2016 | 34 | 2016 |
| Sources of irreproducibility in machine learning: A review OE Gundersen, K Coakley, C Kirkpatrick, Y Gil arXiv preprint arXiv:2204.07610, 2022 | 24 | 2022 |
| MetENP/MetENPWeb: An R package and web application for metabolomics enrichment and pathway analysis in metabolomics workbench KS Choudhary, E Fahy, K Coakley, M Sud, MR Maurya, S Subramaniam BioRxiv, 2020.11. 20.391912, 2020 | 4 | 2020 |
| Open Research in Artificial Intelligence and the Search for Common Ground in Reproducibility: A Commentary on “(Why) Are Open Research Practices the Future for the Study of … OE Gundersen, K Coakley Language Learning 73 (S2), 407-413, 2023 | 1 | 2023 |
| Engaging with Researchers and Raising Awareness of FAIR and Open Science through the FAIR+ Implementation Survey Tool (FAIRIST) CR Kirkpatrick, KL Coakley, J Christopher, I Dutra arXiv preprint arXiv:2301.10236, 2023 | | 2023 |
| Examining the Effect of Implementation Factors on Deep Learning Reproducibility K Coakley, CR Kirkpatrick, OE Gundersen 2022 IEEE 18th International Conference on e-Science (e-Science), 397-398, 2022 | | 2022 |
| Open Storage Network Concept Paper: National and International Trends in Research Storage at Scale CR Kirkpatrick, K Coakley, MH Cragin, J Glasgow, K McHenry, U Jandt, ... https://doi.org/10.6075/J00G3HQ1, 2021 | | 2021 |
| Open Storage Network Concept Paper: Research Drivers and Capabilities CR Kirkpatrick, K Coakley, MH Cragin, J Glasgow, J Goodhue https://doi.org/10.6075/J0HM56Z7, 2020 | | 2020 |
