We'll be aiming to have more direct synchronous interaction during this sprint than usual, so we will communicate primarily via Adobe Connect, rather than IRC.
How to Participate
Add your name to the list on this wiki page (with any comments about your availability). If you want to join after the sprint has started just join the IRC channel mentioned above and say hello.
Before we start, you need to download and install these pieces of software:
- Pentaho BI Server: (Pentaho BI Server 3.10.0-stable ONLY)
- Pentaho Data Integration (PDI 4.2.1-stable ONLY)
- Pentaho Schema Workbench (Schema Workbench 3.3.0-stable ONLY)
- If you're on a Mac or Linux, make sure to download the .tar.gz file, not the .zip.
- If you don't have MySQL installed, install that.
- If you don't have Java, install the latest version of JRE 6.
Core OpenMRS developers who will be working on this sprint will be using a deidentified dataset from MVP. You need to sign the confidentiality forms, which you've received by email. Non-core developers participating in this sprint need to bring their own dataset.
The general process:
- Pick a ticket from the available tickets in the top-left of the dashboard.
- Make sure it does not depend on a ticket that is incomplete.
- If you have any questions about the ticket, ask on the group chat
- Do the ticket
- Commit code and click "Committed Code" (preferred) or attach a [patch|docs:Patches] and click "Request Code Review"
- Darius Jazayeri
- Ben Wolfe (3 days)
- Daniel Kayiwa (3 days)
- Rafal Korytkowski
- Mykola Vorobey
- Add your name here
Please try to attend the kickoff meeting (see above for timing).
Replay of training & brainstorm sessions
- Day 1: Pentaho Introduction (2h11m): http://breeze.iu.edu/p6h8pfwrqec/
- Day 2: Unknown topic (39m): http://breeze.iu.edu/p6f452wb8av/
- Day 3: Using the BI server (45m): http://breeze.iu.edu/p3f020jq6i3/
- Day 3: Building the fact table (1h17m): http://breeze.iu.edu/p7bddwjchb3/
Check this space again for the JIRA dashboard for this sprint
- Alpha version of a reporting web service module that lets you evaluate cohort definition x dataset definition.
- Describe/design and/or spike on a kettle plugin that works with that web service
- Documentation for row per patient and row per encounter
- Learn more about data warehousing, OLAP, and analytics
- Proceed further with using MVP as a spike for general OLAP looks like for OpenMRS
- Implement indicators for MVP, improving or validating the existing pilot OLAP Data Model .