Are we to choose a topic from the tasks that @reenashah listed in her issue article and then present it on Tuesday? Just wanted to make sure I understood the assignment.

Thanks,

Presenter, maybe filling out this google doc. I hope this can give us have a better idea of what other groups are doing and hopefully we can figure out where our tasks fit into the "picture".

A group of our presenters will be meeting tonight at 8pm, send me an email/message if you would like to meet with us.

https://docs.google.com/spreadsheet/ccc?key=0AlHvJfpaZk5-dHNpQVhfUkpzMzZ4SFFHY1Mxd0J6eVE#gid=0

Does anyone have suggestions on how to get people from other horizontals to contribute their findings?

Maybe have each horizontal elect a captain to report to the presenters so we can fit the pieces together.

Also, how do I upload files to the presenters repo, it says it is not up yet.

Carl and Sam:

If you guys could come up with another task list similar to the one that came out mid semester (more general), that would allow presenters and visualizers not involved with the science portion of the project to polish our final product. As always, let us know if you guys need help with anything in general.

DataCurators-Subgroup

Members (We got approval for 5 members in office hours)

• Data Curators
  • Alisha Agrawal
  • Theresa Andrasfay
  • Jie Zhang
  • Eric Tsai
• Presentor
  • Lorraine Hsiao

Group SMART Goals and Tasks

• Clean up the SCEC data from 1938-2013: remove NA's, create datetime column
• Read Luen article to determine magnitude type needed for analysis
• Specific-Yes-We know which tasks we are working on. We are working on making the data into a form usable by the analyzers and visualizers. We are also providing information on the format of the output so that groups further along can progress with their work even without the exact data.
• Measurable-Yes-We will be able to determine our progress. Our end output shows clearly whether or not we have accomplished cleaning NA's and creating a datetime column.
• Attainable-Yes-We are choosing goals we can reach by Tuesday
• Relevant-Yes-Everything we are working on is necessary for the analyzers; we have communicated with their group to see what is most relevant and important for them. The tasks that we do should make it easier for them to analyze the data.
• Time-bound-Yes-We are making progress and are on track to finish

(2) Researching and Negotiating on Data Formats

• Curator: Construct interface for Curators and Visualizers to to utilize
• what is the most common one
• JSON versus CSV versus XML
• Data Frame versus 2-D Array versus List of Dictionaries
• Analyzers/Visualizers: research sufficient/functional data formats in terms of
  ease-of-use and ability to produce visuals
• Presenters: decide on how to present the data
• iPython notebook, HTML, etc.
• what are the pro’s and con’s of each method
• which format could be used to make the graph dynamic?

TASKS:

(1) Curate Data from SCEC website {Taken by: Group Smile}
- check integrity of data (watch for duplicates, NA’s, etc.)
- store as a CSV
- return as a data frame
- provide usage sample to analyzers and visualizers
- link to github: [ ]
- consider where to reproducibly store the data

(2) Researching and Negotiating on Data Formats
- Curator: Construct interface for Curators and Visualizers to to utilize
- what is the most common one
- JSON versus CSV versus XML
- Data Frame versus 2-D Array versus List of Dictionaries
- Analyzers/Visualizers: research sufficient/functional data formats in terms of ~~
~~ ease-of-use and ability to produce visuals
- Presenters: decide on how to present the data
- iPython notebook, HTML, etc.
- what are the pro’s and con’s of each method
- which format could be used to make the graph dynamic?

(3) Explore additional data sources
- Curator: Find additional sources
- Add code integrate the new data, bolstering our data source
- Do everything we did for the SCEC source
- Integrity check
- format validation
- The new data must be plug-and-play with what Visualizers/Analyzers code

(4) ETAS Model: translating from MATLAB
- Working with MATLAB

• recruit people who are familiar with MATLAB syntax
  - explore D-Lab resources and communicate with on-campus
  representatives to further interpret MATLAB code
  • understand what the MATLAB code is executing; translate to Python
• Understanding the ETAS model
  • which parameters to use
  • which columns to use
  • interpretation of the models
• output ETAS model in Python

(5) ETAS Model: utilizing the ETAS R Package
- research the ETAS R Package
- Understanding the ETAS model
- which parameters to use
- which columns to use
- interpretation of the models
- output ETAS model in R

(6) Alarm Model
- talk to Professor Stark/conduct research to further understand the alarm model
- Understanding the Alarm model
- which parameters to use
- which columns to use
- interpretation of the models
- decide whether to use R or Python
- communicate with Visualizers and Group 4-5
- extract relevant data from data frame to send to visualizers

(7) Visualize raw earthquake data (Time Series)
- create graph of the RAW earthquake data
- don’t have ETAS/Stark model yet
- CDF for earthquake occurences
- refine code for plotting earthquakes for particular regions
- make it dynamic to location

(8) Create Visual for ETAS and Alarm Data in Report
- understand the parameters of the model
- what are our axes
- PDF versus CDF
- create graph output for the coordinate data we receive from the analyzers
- output the two graphs on the same coordinate plane
- create a residual plot to compare the two models
- is there a correlation between the two models? Is the residual plot white
noise?
- how do we determine the fit between the lines in the plot?

My group is working on Task 3.

(3) Explore additional data sources

• Curator: Find additional sources
• Add code integrate the new data, bolstering our data source
• Do everything we did for the SCEC source
• Integrity check
• format validation.
• The new data must be plug-and-play with what Visualizers/Analyzers code

Our group will handle this:

(5) ETAS Model: utilizing the ETAS R Package

• research the ETAS R Package

Understanding the ETAS model
which parameters to use
which columns to use
interpretation of the models
output ETAS model in R

Group 7: Alex, Sunny, He, Carl

@ Office Hour, approved to have 5 members in our group:

Hong Shon Presenter @tzenarr
Christina Ho Visualizer/ Operational Lead @chocoho
Jinsoo Lee (Jason) Visualizer @annyoengjs
Hyungkyu Chang Visualizer @hkchang89
Sung Hoon Choi Visualizer

My group will be handling this:

OVERALL TASK - 8

Create Visual for ETAS and Alarm Data in Report

• Understand the parameters of the model
• What are our axes
• PDF versus CDF
• Create graph output for the coordinate data we receive from the analyzers - output the two graphs on the same coordinate plane
• Create a residual plot to compare the two models
• Is there a correlation between the two models? Is the residual plot white noise?
• How do we determine the fit between the lines in the plot?

our group's SMART goals can be viewed here:
https://github.com/annyeongjs/visualheart.task8

Thursday, December 12, 11am in Sutardja Dai Hall

Here is also link to ics file of the event to import.

https://drive.google.com/file/d/0BwKdB_QKlH2vdmtYSDg4WTZ4Y2s/edit?usp=sharing

Members:

Ashley Sia (Visualizer, Operational Lead) @ashleysia
David Lau (Presenter, Technical Lead) @davidopluslau
Yoojin Jang (Presenter) @all4ujin
Raymond Ma (Visualizer) @raymondma1

Task:

Visualize raw earthquake data (Time Series)

• create graph of the RAW earthquake data
• don’t have ETAS/Stark model yet
• CDF for earthquake occurences
• refine code for plotting earthquakes for particular regions
• make it dynamic to location

The SMART Goals:

• Figure out what kind of graph(embedded in R) will be best for showing RAW earthquake data
• Figure out what parameters will be received from the analyzers to input into graphs
• Create skeleton for seismic and time series graphs
• Create a way so that graphs will be dynamic to location
• Time frame: by Tuesday of next week?