1. Proposed Logistics: (10 min)

1.1 Internal weekly meetings:

Each task is allocated 5 minutes for updates, and the task lead will present slides. Upload the weekly slides into the shared GoogleDrive folder

1.2 Sync-up on Slack:

Every Tuesday morning, each task lead will do a quick sync-up on the ISI CriticalMAAS-AIM channel with 1-2 sentences. Describe what you'll be working on and what (if) you need from others.

1.3 External meetings with other TA1 (and TA4) performers:

[TO_BE_SCHEDULED] First, find a time that works for most of us (USC/UMN/Inferlink). Ideally, we'll have one person from each org to attend the meetings and then sync-up in our internal meeting.

All internal and external meetings will be open with a dedicated shared calendar so that DARPA/USGS/other performers can join if they like.

2. Shared Repos & Google Drive Folders (5 min)

Github Project Repo: https://github.com/knowledge-computing/CriticalMAAS_AIM
- Send Zekun your GitHub ID to grant access to the repo
Google Drive: https://drive.google.com/drive/folders/1SPdN8hxFWTZRwf4MAykvZFgwWmY3bcQk
Project Website: https://github.com/knowledge-computing/criticalmaas-aim

3. Discuss about the proposed tasks (Summary Doc) (30min)

3.1. Leads (10 min)

3.1.1. Line Feature Extraction @Weiwei

Input: Scanned raster map & cropped line symbol
Output: Binary segmentation mask (.geotif), vector with attributes (.geojson, decide on the schema, e.g., type, map URI, processing model)
To discuss:monocle_face: : output data schema

3.1.2 Text spotting on the map images (@Leeje Jang)

Input: Scanned raster map
Output: Geojson that contains spotted labels (follow mapKurator schema)

3.1.3 Build overall end-to-end system and data production (@Inferlink)

Needs to collaborate with UIUC and Uncharted to incorporate other modules
Input: Scanned raster map
Output: Outputs from all the modules
To discuss: :monocle_face: Define the required modules and input/output of each module Whether to use mapKurator?

3.2 Other Components (20 min)

3.2.1 Point Feature Extraction @Ju Sun @Leeje

Input: Scanned raster map & cropped point symbol
Output: Binary segmentation mask (.geotif), vector with attributes (shapefile, decide on the schema, e.g., type, map URI, processing model)
To discuss::monocle_face: output data schema

3.2.2 Polygon Feature Extraction & cropped polygon symbol @Fandel

Input: Scanned raster map
Output: Binary segmentation mask (.geotif), vector with attributes (shapefile, decide on the schema, e.g., type, map URI, processing model); List of bounding boxes for symbol detection(needs paired bounding boxes for symbol and text description)
To discuss: :monocle_face: output data schema

3.2.3 Map area segmentation (New task) @Fandel

Input: Scanned raster map
Output: Binary segmentation mask (.tif/.png/.jpg) that has map area segmented

3.2.4 Georeferencing (New task) @Zekun @Theresa

Input: Scanned raster map
Output: lat & lng of map corners?
To discuss::monocle_face: Output data schema

4. Goals & Milestones (5 min)

Month 3: Internal prototype end-to-end system ready Integrated with competition models
- DARPA's Expected Outcomes (for the hackathon) • Establish working relationships among performers within and across TAs • USGS SMEs provide details and/or clarifications of CMA processes • Reach agreement on data and file formats, naming conventions, etc. • Develop roadmap for meeting Month 6 Baselining Event objectives ▪ Not expecting a usable prototype system that integrates all TAs
- No formal evaluation, but... • The Government team will assess progress towards program objectives • Performers will be provided with feedback, and guidance as needed
Month 6: TA1 end-to-end system ready for MVT Zinc Integrate with other performers
- DARPA's Expected Outcomes (for the hackathon) Baselining Event at 6 Months • Each TA (1-3) will be evaluated separately. • Expert users will use tools to perform TA-specific tasks. • Output will be assessed for quality (and throughput) and will receive qualitative feedback. • This is an opportunity to debug each workflow, find out what works and what does not (can the user accomplish what is needed).
- EXAMPLE: MVT Zinc https://drive.google.com/file/d/1LiwnMo8-ShJsZmtIpHr9TrTuAiwek82K/view?usp=sharing

5. Kick-off Data: (5 min)

~140 GB Competition data + NGMDB data (Access Link)

To discuss: :monocle_face: How to share? Where to store?

knowledge-computing / criticalmaas-web

Internal Planning #1