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Context: social, organizational, etc.
System:desktop, mobile,tablet, etc. User
Tool
Task Data analysis? Writing? Graphing?
Example: Cancer Deep Phenotyping Extraction from Electronic Medical Records
G. Savova, and R. Jacobson co-PIs
DeepPhe Stakeholder:Translational Scientist with “Dry Bench” Bioinformatics skillsBackground• PhD trained scientist in wide range of fields relevant to cancer (e.g. genetics, pharmacology, molecular
biology, immunology)• Analytically trained and familiar with statistical methods, including genomics/bioinformatics.• Unfamiliar with NLP Concepts• Unfamiliar with NLP tools and resources• Limited familiarity with OO programming languages• Familiar with text manipulation languages ( e.g. Python, Perl, Ruby)
Premise/story• Cancer biologists are unraveling the genomic and molecular changes that drive tumors towards
specific behaviors such as progression and metastasis. Identifying these molecular drivers will require information about the specific cancer behaviors that they produce. This class of users will examine data for case finding and to classify cases based on outcome.
DeepPhe Stakeholder:Translational Scientist with “Dry Bench” Bioinformatics skillsExpectations • Population-level statistics, summarization, and comparisons.• Graphical displays, including bar charts, error bars, etc.• Inferential statistics• Export to statistical software (SAS,SPSS,RapidMiner, R)
Information needs• Demographic data• Treatment data• Disease progression, metastasis and other outcomes (e.g. RECIST criteria)• Available biomarkers and other clinical molecular information not in structured format (e.g.
Oncotype Scores)
Current tools and limitations• Mac desktop, Linux and Windows computing• Some familiarity with DBMS and data management principles• Knowledge and use of statistical software (e.g. SAS, SPSS, RapidMiner, R), but time required
to extract and format data is substantial.• Routine access to PHI clinical text for work, able to interpret clinical text reports, but in-
depth review is too error-prone and time-consuming.
Contextual Interviews
Synthesis Lectures in Human-Centered InformaticsMorgan & Claypool 2014
Principles of contextual inquiry modified from Beyer & Holtzblatt 1998, 2014
Contextual Inquiry Example
Participatory Design
Kemmis & McTaggart (1982) reprinted in Clemensen, et al. 2007
Clemensen, et al. 2007
•Users involved throughout•Scenario design between CD and PD
•Pros and Cons?
“Five Reasons for Scenario-Based Design” J.M. Carroll, 1995
Problem scenario: visit to a science fiction club meetingRosson & Carroll 2002
