envship_v2_datasets / DATA_CARD.md
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rebrand v2.2: EnvShip-Bench v2 → MARIS-Forecast (DATA_CARD.md); add Zenodo DOI 10.5281/zenodo.21224009
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# MARIS-Forecast Cross-Domain Extension — Data Card
*Datasheet template adapted from Gebru et al., "Datasheets for Datasets" (2021).*
This data card covers the cross-domain extension of MARIS-Forecast. It
adds three jurisdictions (NOAA, Piraeus, Norway) on top of the original
DMA-only release and introduces a long-horizon track (Track B). For the
DMA-only single-track parent benchmark see
`../ICDE_conferece_dataset_paper/DATA_CARD.md`.
## Motivation
**Purpose.** The cross-domain extension exists to test whether ship
trajectory predictors trained on one maritime jurisdiction transfer to
another, and whether long-horizon (60 min) forecasts trained on short
trajectories generalise. The four jurisdictions span three operational
regimes (Northern European coastal traffic, US open-ocean transits,
Mediterranean port/ferry mix, Norwegian fjord and coastal traffic) and
two distinct AIS time-resolutions / vessel-mix profiles.
**Authors.** Constructed by the MARIS-Forecast authors (see top-level
`CITATION.cff`).
**Funding.** No external funding earmarked specifically for cross-domain
construction.
## Composition
**What each instance represents.** A single sample is a 20-minute window
of a vessel's trajectory under Track A (10-minute observation +
10-minute prediction, 30 + 30 points at 20 s); or a 90-minute window
under Track B (30-minute observation + 60-minute prediction, 90 + 180
points). All positions are in a local planar frame centred on the
anchor (last history point), with x = east, y = north, units of metres.
**Sample counts.**
Track A (10/10):
| Subset | Train | Val | Test | Total |
|---------|--------:|-------:|-------:|--------:|
| DMA | 120,000 | 15,000 | 15,000 | 150,000 |
| NOAA | 48,000 | 6,000 | 6,000 | 60,000 |
| Piraeus | 48,000 | 6,000 | 6,000 | 60,000 |
| Norway | 48,000 | 6,000 | 6,000 | 60,000 |
| **Combined** | **264,000** | **33,000** | **33,000** | **330,000** |
Track B (30/60):
| Subset | Train | Val | Test | Total |
|---------|-------:|------:|------:|-------:|
| DMA | 46,744 | 5,414 | 6,000 | 58,158 |
| NOAA | 35,893 | 4,725 | 4,148 | 44,766 |
| Piraeus | 628 | 394 | 132 | 1,154 |
| Norway | 2,441 | 117 | 221 | 2,779 |
| **Combined** | **85,706** | **10,650** | **10,501** | **106,857** |
The Piraeus/Norway Track-B sample counts are intrinsically small because
the underlying port/coastal trajectories rarely exceed two hours; this
is a domain characteristic, not a defect.
**Time spans (verified from first-row `hist_end_ts` in standard_track_v1
train CSVs).**
| Subset | Min date | Max date | Days |
|---------|-------------|-------------|-----:|
| DMA | 2025-09-01 | 2025-09-30 | 30 |
| NOAA | 2025-03-01 | 2025-03-31 | 31 |
| Piraeus | 2019-01-01 | 2019-12-26 | 360 |
| Norway | 2025-08-01 | 2025-09-30 | 61 |
**Bounding boxes (verified from anchor coordinates).**
| Subset | lon range | lat range |
|---------|--------------------|--------------------|
| DMA | 2.13 – 19.66 °E | 52.75 – 59.85 °N |
| NOAA | -159.12 – 144.34 | 13.70 – 49.45 °N (CONUS + Hawaii + western Pacific) |
| Piraeus | 23.06 – 23.70 °E | 37.67 – 38.03 °N |
| Norway | 4.00 – 11.93 °E | 57.50 – 60.49 °N (Skagerrak + south Norwegian coast) |
**What each row contains.** Each row of
`<subset>/multi_type_mini_bench_build/track_a_short-term_Cross-domain_Datasets/dma_track_v1/{train,val,test}/part-000.csv.gz`
contains (full schema in `summary.json`):
- `sample_id`, `mmsi`, `segment_id`, `ship_type`, `ship_class`,
`ship_type_id`, `ship_class_unified`, `ship_type_id_unified` (Piraeus
+ Norway only)
- `hist_end_ts`, `pred_end_ts` (UTC ISO timestamps)
- `hist_x_json` / `hist_y_json` — 30 (Track A) or 90 (Track B) points;
metres relative to anchor
- `fut_x_json` / `fut_y_json` — 30 or 180 future points
- `hist_sog_json`, `hist_cog_sin_json`, `hist_cog_cos_json`,
`hist_heading_sin_json`, `hist_heading_cos_json` — kinematic arrays
- `hist_time_of_day_sin/cos_json`, `hist_day_of_week_sin/cos_json`
periodic time encodings
- `hist_interp_json` / `fut_interp_json` — booleans for interpolated points
- `interp_ratio_*`, `grid_interp_ratio_*` — quality scalars
- `hist_displacement_m`, `fut_displacement_m`
- `core_eligible`, `full_eligible`, `quality_tier`, `split`
**Per-sample artefacts** (context_v1):
- `environment/rasters/{split}/masks.npz` (N, 6, 128, 128) uint8 — load via `np.load(...)['masks']`
- `environment/rasters/{split}/signed_dist_shore.npy` (N, 128, 128) float16, metres
- `environment/rasters/{split}/signed_dist_nav.npy` (N, 128, 128) float16
- `environment/rasters/{split}/sample_ids.npy` (N,) object
- `environment/vectors/{split}/vectors.jsonl.gz` exact OSM polylines
- `environment/all_environment_descriptors.csv` tabular scene descriptors
- `social/<split>_social_descriptors.csv` neighbour-aware scalars
**OSM temporal-consistency artefacts** (new, see § OSM Temporal
Consistency below):
- `osm_temporal_consistency/{train,val,test}_flags.csv` per-sample flags
- `osm_temporal_consistency/summary.json` aggregate
- The 4 flag columns are merged inline into
`<subset>_track_v1/<split>/part-000.csv.gz` in the v2-final HF release;
paper-default filter is `df[df["osm_temporal_consistent"] == "true"]`.
**Phase 1+2 context columns (added 2026-06-19).** Each row of the
main CSV also carries 15 anchor-time scalar columns covering weather
(6 cols), sea state (4 cols), port proximity (2 cols), fairway/TSS
proximity (3 cols). See `README.md` for the full column-by-column
schema and the `CHANGELOG.md` v2.1 entry for coverage and
known-gap notes (Piraeus 2019 has empty wave columns).
**Splits.** Vessel-disjoint. `stable_split_from_mmsi(mmsi)` = MD5(MMSI)
mod 10; bucket 0 = val, bucket 1 = test, otherwise = train. No MMSI
appears in more than one split.
**Missing / partial fields.**
- Ship dimensions (length, beam, draught) — available only for ~20–60%
of vessels depending on subset (Piraeus best, Norway worst before
VesselFinder enrichment; see `norway_ship_trajectory_datasets/ENRICHMENT_REPORT.md`).
- Bathymetry, weather, currents — not bundled.
- Visual imagery — not bundled.
- ~0.2 % of samples have `anchor_in_water = 0` (anchor falls on land
per OSM raster, typically vessels berthed at piers); retained for
completeness.
**Class taxonomy.**
- `ship_class` — raw text class assigned at preprocess time.
- `ship_class_unified` — 7+1 canonical classes (`cargo`, `tanker`,
`passenger`, `fishing`, `tug`, `service`, `sailing_leisure`, plus
`unknown`). Implemented in `scripts/extras/taxonomy.py`; mapping rule
table is also documented there.
- `ship_type_id_unified` — integer 0…7 matching the canonical class order.
For DMA and NOAA the raw `ship_class` is reused as-is (the upstream
field is already clean). Piraeus and Norway gain the unified columns
inline; Norway's `unknown` rate dropped from ~52 % to ~18 % on the test
split after VesselFinder enrichment (`scripts/extras/enrich_norway_static.py`).
## OSM temporal consistency
OSM is a living dataset: ports, piers, breakwaters, and quays added
after the AIS date can appear as "land" in the SDF even when the
trajectory was genuinely on water. This is highest-risk for the
**Piraeus 2019** subset (6 — 7 year gap to a 2026 OSM snapshot) and
near-zero for the other three subsets (4 — 12 month gap).
**Method (Stage 17 — `scripts/extras/stage_17_osm_temporal_consistency.py`).**
For every sample, the 60 (Track A) or 270 (Track B) trajectory points are
projected onto the per-sample 128 × 128 `signed_dist_shore` raster. A
point with `signed_dist_shore < 0` is inland per the OSM snapshot used
for the build. We record `max_inland_depth_m`, `n_inland_points`,
`max_consec_inland_run`, and a default flag:
> `osm_temporal_consistent = (max_inland_depth_m ≤ 30 m) AND (max_consec_inland_run < 3)`
Thresholds are configurable; 30 m matches the SDF cell pitch of ~78 m so
a single-cell brush is permitted (within-cell positional jitter).
**Results — Track A against current 2026 OSM**:
| Subset | Train consistent | Val consistent | Test consistent |
|---------|-----------------:|---------------:|----------------:|
| DMA | 119,135 / 120,000 (99.28 %) | 14,881 / 15,000 (99.21 %) | 14,889 / 15,000 (99.26 %) |
| NOAA | 47,704 / 48,000 (99.38 %) | 5,950 / 6,000 (99.17 %) | 5,926 / 6,000 (98.77 %) |
| Piraeus | 47,797 / 48,000 (99.58 %) | 5,988 / 6,000 (99.80 %) | 5,974 / 6,000 (99.57 %) |
| Norway | 47,965 / 48,000 (99.93 %) | 5,994 / 6,000 (99.90 %) | 5,989 / 6,000 (99.82 %) |
**For Piraeus**, we additionally rebuild the env/SDF stack using a
contemporaneous OSM snapshot (`greece-200101.osm.pbf` — Geofabrik
historical extract), and publish that as `context_v1_2019osm/`.
This roughly halves the inconsistent-sample count for Piraeus
because all new-build piers from 2020 – 2025 are excluded from the SDF.
See § Piraeus historical-OSM rebuild.
**Two subsets are released:**
- `track_a_short-term_Cross-domain_Datasets/dma_track_v1/` — the full curated benchmark with the
`osm_temporal_consistency/<split>_flags.csv` side-car (no rows deleted).
- `<subset>_track_v1/<split>/part-000.csv.gz` inline filter — drop rows
where `osm_temporal_consistent != "true"`. **This is the recommended
default for paper main tables.**
## Pipeline
The cross-domain extension reuses the same 14-stage AIS pipeline from
the parent DMA-only release and adds three virtual stages:
| Stage | Name | Output |
|------:|-------------------------------------|-----------------------------------|
| 01 | Field standardisation | `data_interim/01_standardized/` |
| 02 | Validity filter | `02_filtered/` |
| 03 | Sort + dedup | `03_deduped/` |
| 04 | Ship-type-aware speed filter | `04_shiptype_speed_filtered/` |
| 05 | Trajectory segmentation | `05_segmented/` |
| 06 | Anchorage removal | `06_underway_only/` |
| 07 | Short-gap interpolation | `07_gap_imputed/` |
| 08 | 20-s UTC resample | `08_resampled_20s/` |
| 09 | Second-pass anomaly check | `09_rechecked/` |
| 10 | Minimum-length filter | `10_minlen_filtered/` |
| 11 | Sliding window generation | `benchmark/full/` |
| 12 | Quality + difficulty labels | (in-place) |
| 13 | Core/full benchmark export | `benchmark/{core,full}/` |
| 14 | Partition summaries | `benchmark/*.json` |
| 15 | Stratified standard-track curation | `multi_type_mini_bench_build/track_a_short-term_Cross-domain_Datasets/dma_track_v1/` |
| 16 | Env-SDF + social context (OSM) | `.../track_a_short-term_Cross-domain_Datasets/dma_track_v1/context_v1/` |
| **17**| **OSM temporal consistency** | `.../osm_temporal_consistency/` |
| 10b | Track-B segment-duration prefilter | `track_b_medium-term_Cross-domain_Datasets/<DS>/data_interim/` |
Track B re-runs stages 10b → 11 → 12 → 13 → 15 → 16 → 17.
## Collection process
**How acquired.**
- DMA: https://web.ais.dk/aisdata/ (aisdk-2025-09-*.zip, 30 daily ZIPs)
- NOAA: https://marinecadastre.gov/ (March 2025 daily CSVs)
- Piraeus: Zenodo 10.5281/zenodo.6323416 (CC BY 4.0; ferry-rich port AIS for 2019)
- Norway: Kystverket / Kystdatahuset public API (NLOD 2.0; Aug + Sep 2025)
**Time frame.** Documented per-subset in
`<subset>/multi_type_mini_bench_build/track_a_short-term_Cross-domain_Datasets/dma_track_v1/summary.json`.
**Ethical review.** AIS positions are broadcast publicly by vessels per
SOLAS Ch. V. MMSI is a vessel identifier, not a personal identifier. No
human-subjects review applies.
## Preprocessing / cleaning / labelling
See § Pipeline above. Stage code lives under each subset's `scripts/`
plus shared utilities in `scripts/extras/` (taxonomy unification,
Norway VesselFinder enrichment, Track-B pre-filter, OSM PBF tile builder,
OSM temporal-consistency flagger).
## Uses
**Baselines reported.** See the parent ICDE paper
(`../ICDE_conferece_dataset_paper/paper_v4.pdf`) for the full
25-baseline grid (physics, classical ML, traj-only DL, social-aware,
env-aware, joint social+env, Transformer family). Headline numbers:
Track A in-domain ADE (metres, best-of-3 seed):
| Model | DMA | NOAA | Piraeus | Norway |
|--------------------|------:|------:|--------:|-------:|
| TCN (traj-only) | 85.8 | 91.2 | 169.1 | 122.6 |
| LSTM + Env-SDF | 87.3 | 101.8 | 151.8 | 127.5 |
| LSTM + Soc + Env-v2| 87.2 | — | — | — |
| GRU-2L | — | — | — | 128.1 |
Other downstream methods that consume this dataset include
EnvSocial-TrAISformer (cross-domain Track B), GeoMode-TKDE (SDF-gradient
CVAE), ship_LLM_traj_pred_benchmark (LMTraj adaptation), MFPD-TKDE
(diffusion), AnchorDiff (DMA-only diffusion), and M-CTX-ICDE (spatial
indexing benchmark).
**Other tasks** the dataset can support:
- Anomaly / route-deviation detection
- Vessel-type classification from kinematics
- Multimodal stochastic forecasting (mixture / diffusion)
- Geographic generalisation studies (train DMA, evaluate Piraeus etc.)
- Interaction-aware planning under COLREGS
- Long-horizon multi-modal forecasting (Track B)
**Not to do.**
- Do not de-anonymise vessels for surveillance. MMSI is public but
scaling into continuous tracking crosses ethical lines.
- Do not deploy navigation-safety-critical predictors trained only on
this benchmark without operating-region validation.
## Distribution
**Code, paper, metadata.** Public Git repository (see top-level README
once released).
**Bulk data.** The bulk tensors (vectors.jsonl.gz, masks.npz,
signed_dist_*.npy, augmented CSVs) are released separately on Hugging
Face. Build pipeline + raw-source pointers are sufficient for
reconstruction from scratch.
**Licences.**
| Component | Licence |
|--------------------------|------------------------------------|
| Pipeline code (this repo)| CC BY 4.0 |
| DMA AIS subset | CC BY 4.0 (upstream) |
| NOAA AIS subset | US public domain (upstream) |
| Piraeus AIS subset | CC BY 4.0 (upstream Zenodo) |
| Norway AIS subset | NLOD 2.0 (Kystverket) |
| OSM rasters / SDFs | ODbL (© OpenStreetMap contributors)|
| Geofabrik historical PBFs| ODbL |
Top-level `LICENSE` and `NOTICE.md` carry the full text. Each sub-dataset
has its own `LICENSE` matching the upstream provider.
## Maintenance
**Maintainer.** Kun Ma (kunma1220@gmail.com).
**Versioning.** Semantic-versioned releases. Track A and Track B share
the same version (currently `standard_track_v1`). Future revisions will
bump to `v2`.
**Planned additions.**
- Bathymetry channel from EMODnet (Europe) + GEBCO global
- Tidal heights from FES2014
- Weather (wind / wave) from ERA5 / NOAA WaveWatch III
- Additional jurisdictions (Black Sea, East China Sea) pending data
availability
- Pre-computed time-disjoint OOD splits for Piraeus + DMA (full-year coverage)
**Reporting issues.** Open a GitHub Issue against the public repo.
## Piraeus historical-OSM rebuild
For the Piraeus subset only, where the AIS year (2019) is ~6 years
earlier than the current OSM snapshot, the SDF and 6-channel rasters
are rebuilt with the Geofabrik **2020-01-01** Greece extract
(`greece-200101.osm.pbf`, MD5 `9c6da7651e624ab182c20d0d629d5e8c`,
185 MB). This snapshot captures Greek coastal infrastructure as it
stood at the very end of the AIS year.
The 2026-OSM context is also retained for ablation studies. The two
contexts live side by side under:
- `Piraeus_ship_trajectory_datasets/multi_type_mini_bench_build/track_a_short-term_Cross-domain_Datasets/dma_track_v1/context_v1/` — current OSM
- `Piraeus_ship_trajectory_datasets/multi_type_mini_bench_build/track_a_short-term_Cross-domain_Datasets/dma_track_v1/context_v1_2019osm/` — 2020-01-01 OSM
Stage 17 is run against both; per-sample flag files end with
`_2019osm.csv` for the historical variant. The default
paper-default filter for Piraeus is computed from the
historical-OSM consistency, since that is the most accurate ground
truth for the 2019 trajectories.
## File map
```
Cross-domain-datasets/
├── LICENSE Top-level CC BY 4.0 + sub-licence index
├── NOTICE.md Required attribution lines
├── DATA_CARD.md This file
├── CITATION.cff Top-level citation
├── REPORT.md Build report + cross-domain study
├── DMA_ship_trajectory_datasets/ symlink → upstream DMA
├── NOAA_ship_trajectory_datasets/ symlink → upstream NOAA
├── Piraeus_ship_trajectory_datasets/ Tritsarolis 2022 / Zenodo 6323416
│ ├── LICENSE CC BY 4.0
│ ├── data_raw/ raw zips + historical_osm/
│ ├── data_interim/ per-stage outputs
│ ├── benchmark/ stage 13 windowed
│ ├── multi_type_mini_bench_build/track_a_short-term_Cross-domain_Datasets/dma_track_v1/
│ │ ├── train/ val/ test/ gzipped CSVs (per-row JSON arrays)
│ │ ├── context_v1/ env-SDF + social (current OSM)
│ │ ├── context_v1_2019osm/ env-SDF + social (2020-01-01 OSM)
│ │ └── osm_temporal_consistency/ Stage-17 flag CSVs
│ └── scripts/ pipeline + preprocess
├── norway_ship_trajectory_datasets/ Kystverket NLOD 2.0
│ └── (same layout)
├── track_b/ long-horizon variant
│ ├── DMA/ NOAA/ Piraeus/ Norway/ same per-DS layout
│ └── scripts/ Track-B pre-filter + builders
└── scripts/extras/ shared utilities
├── taxonomy.py unified ship-class taxonomy
├── apply_unified_taxonomy.py patch benchmark CSVs with unified cols
├── enrich_norway_static.py VesselFinder static-info enrichment
├── stage_10b_track_b_filter.py Track-B duration prefilter
├── stage_17_osm_temporal_consistency.py Stage 17
└── pbf_to_tile_cache.py Geofabrik PBF → Overpass-JSON cache
```
## Reproducibility
```bash
bash scripts/reproduce_all.sh
```
Reproduces the four-jurisdiction Track A from raw drops, then Track B,
then the OSM temporal-consistency stage, then the historical-OSM
Piraeus rebuild. Wall time ≈ 5 h on an 8-core CPU host with 32 GB RAM.
The build is deterministic for the same upstream snapshot.