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ESA 2020 Data Help Desk: Difference between revisions
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→Schedule of Career Central Activities
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| Erin McLean (Arctic Data Center) | | Erin McLean (Arctic Data Center), Amber Budden (DataONE), Margaret O'Brien (EDI), Deborah Paul (iDigBio), Erica Krimmel, Julia Masterman (CUASHI), Jack Williams (Neotoma), Marie Faust (NEON), Kelsey Yule (NEON Biorepository), Kyle Copas (GBIF) | ||
| [[Media:TBD|Data Help Desk: So much data, so little time!]] | | [[Media:TBD|Data Help Desk: So much data, so little time!]] | ||
| This session is an introduction to data repositories where you can deposit your datasets to meet funder or publisher requirements, and also retrieve public data to further your research. Representatives from seven repositories will give 3-min presentations highlighting their holdings, approach and services, followed by general Q&A and discussion initiated by the audience. | | This session is an introduction to data repositories where you can deposit your datasets to meet funder or publisher requirements, and also retrieve public data to further your research. Representatives from seven repositories will give 3-min presentations highlighting their holdings, approach and services, followed by general Q&A and discussion initiated by the audience. | ||
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| ''asynchronous'' | | ''asynchronous'' | ||
| Jeanette Clark (Arctic Data Center) | | Deborah Paul (iDigBio), Jeanette Clark (Arctic Data Center) | ||
| [[Media:TBD|Cleaning data and creating tidy data structures to facilitate reproducible research]] | | [[Media:TBD|Cleaning data and creating tidy data structures to facilitate reproducible research]] | ||
| Join us to learn how tidy data concepts can make your analysis easier and improve reproducibility. This session describes how to deal with inconsistencies, missing values, entry errors, multiple values in single columns, and many other data issues. Demonstrations will use R and Open Refine. | | Join us to learn how tidy data concepts can make your analysis easier and improve reproducibility. This session describes how to deal with inconsistencies, missing values, entry errors, multiple values in single columns, and many other data issues. Demonstrations will use R and Open Refine. | ||