ESA 2019 Data Help Desk: Difference between revisions

Line 82: Line 82:
| 11:30-1:15
| 11:30-1:15
| Deborah Paul (iDigBio)/Karl Benedict (ESIP/UNM Libraries)
| Deborah Paul (iDigBio)/Karl Benedict (ESIP/UNM Libraries)
| Data Cleaning for Analysis and Publication Using R and OpenRefine Software Packages
| [[Media:DataCleaning_Benedict-Paul.pdf|Data Cleaning for Analysis and Publication Using R and OpenRefine Software Packages]]
| Data start life with issues: inconsistent content, missing values, entry errors, multiple values in single columns, and many others. Before any analysis or visualization can be done these issues must be resolved. This workshop will demonstrate processes within OpenRefine and R for making your data analysis ready and improving reproducibility.
| Data start life with issues: inconsistent content, missing values, entry errors, multiple values in single columns, and many others. Before any analysis or visualization can be done these issues must be resolved. This workshop will demonstrate processes within OpenRefine and R for making your data analysis ready and improving reproducibility.
|-
|-
Line 112: Line 112:
| 3:30-4:30
| 3:30-4:30
| Dmitry Schigel (GBIF)/Bill Michener (DataONE)
| Dmitry Schigel (GBIF)/Bill Michener (DataONE)
| How to Publish a Data Paper
| [[Media:GBIF_DataPapers_16Aug2019.pdf|How to Publish a Data Paper]]
| Data papers published as unstructured narratives can be challenging for data discovery, integration, and reuse. Alternative data paper models are available. We will outline the current status of data papers and show the main principles of data paper writing using the GBIF page: https://www.gbif.org/data-papers.
| Data papers published as unstructured narratives can be challenging for data discovery, integration, and reuse. Alternative data paper models are available. We will outline the current status of data papers and show the main principles of data paper writing using the GBIF page: https://www.gbif.org/data-papers.
|}
|}
4,707

edits