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Title: Investigating Scientific Data Change with User Research Methods

Abstract

Scientific datasets are continually expanding and changing due to fluctuations with instruments, quality assessment and quality control processes, and modifications to software pipelines. Datasets include minimal information about these changes or their effects requiring scientists manually assess modifications through a number of labor intensive and ad-hoc steps. The Deduce project is investigating data change to develop metrics, methods, and tools that will help scientists systematically identify and make decisions around data changes. Currently, there is a lack of understanding, and common practices, for identifying and evaluating changes in datasets since systematically measuring and managing data change is under explored in scientific work. We are conducting user research to address this need by exploring scientist's conceptualizations, behaviors, needs, and motivations when dealing with changing datasets. Our user research utilizes multiple methods to produce foundational, generative insights and evaluate research products produced by our team. In this paper, we detail our user research process and outline our findings about data change that emerge from our studies. Our work illustrates how scientific software teams can push beyond just usability testing user interfaces or tools to better probe the underlying ideas they are developing solutions to address.

Authors:
 [1];  [1];  [1]
  1. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Publication Date:
Research Org.:
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR)
OSTI Identifier:
1650129
Report Number(s):
LBNL-2001347
ark:/13030/qt87b7h27d
DOE Contract Number:  
AC02-05CH11231
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English
Subject:
96 KNOWLEDGE MANAGEMENT AND PRESERVATION; user research; qualitative methods; data change; scientific software development

Citation Formats

Paine, Drew, Ghoshal, Devarshi, and Ramakrishnan, Lavanya. Investigating Scientific Data Change with User Research Methods. United States: N. p., 2020. Web. doi:10.2172/1650129.
Paine, Drew, Ghoshal, Devarshi, & Ramakrishnan, Lavanya. Investigating Scientific Data Change with User Research Methods. United States. https://doi.org/10.2172/1650129
Paine, Drew, Ghoshal, Devarshi, and Ramakrishnan, Lavanya. 2020. "Investigating Scientific Data Change with User Research Methods". United States. https://doi.org/10.2172/1650129. https://www.osti.gov/servlets/purl/1650129.
@article{osti_1650129,
title = {Investigating Scientific Data Change with User Research Methods},
author = {Paine, Drew and Ghoshal, Devarshi and Ramakrishnan, Lavanya},
abstractNote = {Scientific datasets are continually expanding and changing due to fluctuations with instruments, quality assessment and quality control processes, and modifications to software pipelines. Datasets include minimal information about these changes or their effects requiring scientists manually assess modifications through a number of labor intensive and ad-hoc steps. The Deduce project is investigating data change to develop metrics, methods, and tools that will help scientists systematically identify and make decisions around data changes. Currently, there is a lack of understanding, and common practices, for identifying and evaluating changes in datasets since systematically measuring and managing data change is under explored in scientific work. We are conducting user research to address this need by exploring scientist's conceptualizations, behaviors, needs, and motivations when dealing with changing datasets. Our user research utilizes multiple methods to produce foundational, generative insights and evaluate research products produced by our team. In this paper, we detail our user research process and outline our findings about data change that emerge from our studies. Our work illustrates how scientific software teams can push beyond just usability testing user interfaces or tools to better probe the underlying ideas they are developing solutions to address.},
doi = {10.2172/1650129},
url = {https://www.osti.gov/biblio/1650129}, journal = {},
number = ,
volume = ,
place = {United States},
year = {2020},
month = {8}
}