# Sample Datasets: "Avery Lindqvist"

Everything in this directory is **fully synthetic**. Avery Lindqvist is a
fictional person (a software developer living in Stockholm, working at the
fictional company *Norrsken Labs*). No real person's data is included, and
all coordinates, addresses, names, and identifiers were invented for these
samples.

The datasets are intentionally cross-referential so the derivation engine
(milestone #4) has something real to chew on: the calendar, notes, and photo
metadata all describe the same fictional Q1 2025 — a weekly yoga habit, a
knee injury and physiotherapy, a sourdough hobby, and a trip to Berlin in
mid-March.

## Contents

| Path | Adapter | Description |
| --- | --- | --- |
| `calendar/avery-personal.ics` | `ics-calendar` | Personal calendar: recurring yoga and book club, therapy, dentist, physio, a birthday dinner, the Berlin trip (flight + all-day span). Exercises `RRULE`, `VTIMEZONE`, all-day events, attendees, and categories. |
| `calendar/avery-work.ics` | `ics-calendar` | Work calendar: weekday standups, weekly 1:1, an offsite, a design review, and a **cancelled** meeting (exercises `STATUS:CANCELLED`). |
| `notes/2025-01-05-new-year-intentions.md` | `notes` | Markdown journal note with YAML front matter (title, created date, tags). |
| `notes/2025-02-02-knee-pain.md` | `notes` | Health note referencing the yoga habit and the physio appointment that also appears in the calendar. |
| `notes/project-sourdough.md` | `notes` | Hobby note with a feeding schedule. |
| `notes/berlin-trip-planning.md` | `notes` | Trip planning note that cross-references the calendar trip and the friend who appears in photo locations. |
| `notes/groceries.txt` | `notes` | Plain-text note with no front matter (exercises the non-markdown path). |
| `photos/avery-photos.json` | `photos` | Mock photo EXIF metadata in `exiftool -json` style: a top-level JSON **array** of objects with `SourceFile`, `DateTimeOriginal`, `Make`, `Model`, GPS fields, etc. One record deliberately has no GPS fields (exercises missing-field handling). |

## Importing the samples

From the repository root:

```sh
python -m pmp init --node-dir /tmp/avery-node --name "avery-laptop"
python -m pmp adapters   # confirm canonical adapter names
python -m pmp import --node-dir /tmp/avery-node --adapter ics-calendar \
    samples/calendar/avery-personal.ics samples/calendar/avery-work.ics
python -m pmp import --node-dir /tmp/avery-node --adapter notes samples/notes
python -m pmp import --node-dir /tmp/avery-node --adapter photos samples/photos/avery-photos.json
python -m pmp log list --node-dir /tmp/avery-node
python -m pmp log verify --node-dir /tmp/avery-node
```

Re-running an import is safe: adapters emit stable source identifiers, so the
node deduplicates unchanged items and records supersessions for changed ones.

## What a derivation engine could later infer

These samples are seeded with derivable facts, e.g.:

- *"Avery attends a yoga class weekly on Tuesdays"* (calendar `RRULE` +
  yoga-studio photo on a Tuesday).
- *"Avery had left-knee pain in early February 2025 and saw a physiotherapist
  on 2025-02-20"* (note + calendar event).
- *"Avery traveled to Berlin 2025-03-14 → 2025-03-18"* (flight event, all-day
  span, planning note, and four geotagged photos in Berlin).
- *"Avery bakes sourdough"* (note + kitchen photo).

None of these claims are produced in milestone #3 — only the provenance-tagged
evidence operations that make them derivable.