This week I continued to work on the literature review, this time focusing on metric driven papers. While some primary research papers found statistical significance between data sharing and increased citation rates, a literature review of multiple primary papers noted that confounding effects were not taken into account — such as time article was published and journal it was published in. After finding a few more sources, I began a summary write-up of my results loosely structured around these four themes: Current State of the Field, Current Perceptions, Evidence of Data Sharing Benefits, Reasoning for the study.<\/p>\n
The second part involved looking into how DataONE collects upload and download data, and how we can then access that data. We’ve put in a request to access that information for 7 of the 30 member nodes and began to create a study design to account for the different timelines of each member nodes. The design will start with\u00a0a bivariate test looking at downloads before and after joining DataONE (with a buffer zone in the middle). We threw around ideas about a regression analysis as well, and once we have the data, we’ll be able to run some more ideas. Monday, I’ll be creating a spreadsheet for the timelines for each of the member nodes.\u00a0The analysis will begin in earnest next week once we retrieve the data.<\/p>\n","protected":false},"excerpt":{"rendered":"
This week I continued to work on the literature review, this time focusing on metric driven papers. While some primary research papers found statistical significance between data sharing and increased citation rates, a literature review of multiple primary papers noted that confounding effects were not taken into account — such Continue reading Week Two: Lit Review & Data Collection<\/span>