Katherine Diaz (kdiaz)

Personal information
Full name: Katherine Diaz
User name: kdiaz
Organization memberships
Not a member of any organization.
Awards
First 500 volunteers
5+ tasks completed
Volunteer background
Volunteer availability
Start date: None
End date: None
Hours available per week: None
Volunteering interests
No stated preferences.
Skills
Skill
Beginner
Intermediate
Expert
Python
Data in Relational Databases
SQL
Data Visualization
Social Science (Economics, Sociology, etc.)
Experience working on real-world problems using data
Data Analysis
R
Matlab

Volunteer projects

Project name Organization name Social impact area Project summary Task name Task status
Amphan: analyzing experiences of extreme weather events using online data International Water Management Institute Education Cyclone Amphan made landfall in South Asia on May 20, 2020. It was the most damaging storm in the history of the Indian Ocean, rendering hundreds of thousands of people homeless, ravaging agricultural lands and causing billions of dollars in damage. How were people affected by the storm? What were the responses of individuals, governments, corporates and NGOs? How was it covered by local, national and international media, as opposed to individuals' accounts? Who has created the dominant narratives of Cyclone Amphan; and whose voices go unheard? We aim to use online data -- such as Twitter posts, news headlines and research publications -- to analyze people's experiences of Cyclone Amphan. Text Analysis done_all Completed
PINVAL (PIN Valuation) Cook County Assessor's Office Education Interactive web application that produces a customized valuation report for an individual real estate property. Task and project QA done_all Completed
Amphan: analyzing experiences of extreme weather events using online data International Water Management Institute Education Cyclone Amphan made landfall in South Asia on May 20, 2020. It was the most damaging storm in the history of the Indian Ocean, rendering hundreds of thousands of people homeless, ravaging agricultural lands and causing billions of dollars in damage. How were people affected by the storm? What were the responses of individuals, governments, corporates and NGOs? How was it covered by local, national and international media, as opposed to individuals' accounts? Who has created the dominant narratives of Cyclone Amphan; and whose voices go unheard? We aim to use online data -- such as Twitter posts, news headlines and research publications -- to analyze people's experiences of Cyclone Amphan. Project management done_all Completed
Comparison of Actual and Expected Delivery Dates Medic Mobile Education This project will use a de-identified dataset to examine differences in reported last menstrual period (LMP) as a determinant of a pregnant woman’s delivery data and women’s recorded delivery dates in the CHT application. Data Analysis done_all Completed
Amphan: analyzing experiences of extreme weather events using online data International Water Management Institute Education Cyclone Amphan made landfall in South Asia on May 20, 2020. It was the most damaging storm in the history of the Indian Ocean, rendering hundreds of thousands of people homeless, ravaging agricultural lands and causing billions of dollars in damage. How were people affected by the storm? What were the responses of individuals, governments, corporates and NGOs? How was it covered by local, national and international media, as opposed to individuals' accounts? Who has created the dominant narratives of Cyclone Amphan; and whose voices go unheard? We aim to use online data -- such as Twitter posts, news headlines and research publications -- to analyze people's experiences of Cyclone Amphan. Data Collection done_all Completed
Comparison of Actual and Expected Delivery Dates Medic Mobile Education This project will use a de-identified dataset to examine differences in reported last menstrual period (LMP) as a determinant of a pregnant woman’s delivery data and women’s recorded delivery dates in the CHT application. Project close-out done_all Completed