Job Analyses of Earth Science Data Scientists


The purpose of this presentation is to provide preliminary findings of the results from interviews with scientists using the (Developing a Curriculum) DACUM approach. A DACUM is the best first step for earth science data scientists to create a list of knowledge, skills, and abilities, operationalized job descriptions, and eventually learning outcomes for use in continuing education, secondary education, and higher education. First, job incumbents know their job better than anyone else, and therefore they are the best at describing what it is that they do. Job incumbents are currently working in the field and this is especially salient for the rapidly evolving roles in data analytics and data science with external changes like technology and information policy. The second principle of the DACUM is that the best way to define a job is by describing the specific tasks that are performed on the job. Earth science data scientists, like any other intellectual work, routinely have tasks that may be difficult to describe, but those professionals who are actually performing the jobs currently should be best able to clearly explain what those tasks are in terms of task statements. Finally, the third principle of the DACUM is that all tasks performed on a job require the use of knowledge, skills and abilities (KSA) that enable successful performance of those tasks. For this DACUM, I conducted interviews with 12 earth science data scientists at the ESIP Summer Meeting 2016. The participants were asked to describe their daily/weekly/less frequent tasks, job titles, years in job and working with earth science data, credentials and degrees, other educational/training received that apply to job performance. The recorded interviews were transcribed and this presentation presents preliminary finding of the analyses. Feedback will help inform more targeted questions for a larger survey that will validate the list identified through the interviews.

File ESIP_2017.pptx2.81 MB
Bishop, W.; Job Analyses of Earth Science Data Scientists; Winter Meeting 2017. ESIP Commons , October 2016