@prefix this: . @prefix sub: . @prefix np: . @prefix dct: . @prefix nt: . @prefix npx: . @prefix xsd: . @prefix rdfs: . @prefix orcid: . @prefix prov: . @prefix foaf: . sub:Head { this: a np:Nanopublication; np:hasAssertion sub:assertion; np:hasProvenance sub:provenance; np:hasPublicationInfo sub:pubinfo . } sub:assertion { sub:dggs-benchmark-outcome-2026 a ; "2026-03-07"^^xsd:date; rdfs:label "DGGS Benchmark Outcome: Claim Partially Supported"; """The claim \"Effect of DGGS Indexing on Associating Vector and Raster Geospatial Data\" is PARTIALLY SUPPORTED. VECTOR BENCHMARK (Figure 6): VALIDATED DGGS provides orders of magnitude performance improvement over traditional vector overlay operations. At 20 layers, DGGS was 16,000x faster than vector methods. RASTER BENCHMARK (Figure 7): PARTIALLY SUPPORTED The paper's claim of \"roughly equivalent performance\" holds when comparing classification time with pre-indexed DGGS data. However, on-the-fly H3 indexing adds significant overhead. The replication using xdggs shows vectorized indexing reduces this overhead by ~100x."""; ; """
VECTOR BENCHMARK RESULTS:
| Layers | DGGS     | Vector   | Speedup  |
|--------|----------|----------|----------|
| 5      | 0.01s    | 0.4s     | 40x      |
| 10     | 0.015s   | 10s      | 670x     |
| 20     | 0.03s    | 400s     | 16,000x  |
DGGS shows near-linear scaling; vector shows super-linear growth. This validates the paper's Figure 6. RASTER BENCHMARK RESULTS (100 layers):
| Method              | Time    |
|---------------------|---------|
| Raster (NumPy)      | 0.02s   |
| DGGS Pre-indexed    | 0.01s   | ← Paper's scenario: VALIDATED
| DGGS + H3 loop      | 5.0s    | ← Includes slow indexing
| DGGS + xdggs        | 0.05s   | ← Replication: 100x faster indexing
The pre-indexed scenario matches the paper's methodology and validates the claim of equivalent performance.
"""; """
- Vector benchmark tested up to 100 layers (paper used 500)
- Raster pre-indexed scenario simulates but doesn't exactly replicate 
  Apache Parquet + Polars implementation
- Missing random misalignment (\"jittering\") from original methodology
- Single hardware configuration tested
"""; ; ; . } sub:provenance { sub:assertion prov:wasAttributedTo orcid:0000-0002-1784-2920 . } sub:pubinfo { orcid:0000-0002-1267-0234 foaf:name "Tobias Kuhn" . orcid:0000-0002-1784-2920 foaf:name "Anne Fouilloux" . this: dct:created "2026-03-30T07:02:18.572Z"^^xsd:dateTime; dct:creator orcid:0000-0002-1267-0234, orcid:0000-0002-1784-2920; dct:license ; npx:introduces sub:dggs-benchmark-outcome-2026; npx:wasCreatedAt ; prov:wasDerivedFrom ; nt:wasCreatedFromProvenanceTemplate ; nt:wasCreatedFromPubinfoTemplate , , , ; nt:wasCreatedFromTemplate . sub:sig npx:hasAlgorithm "RSA"; npx:hasPublicKey "MIGfMA0GCSqGSIb3DQEBAQUAA4GNADCBiQKBgQD4Wj537OijfOWVtsHMznuXKISqBhtGDQZfdO6pbb4hg9EHMcUFGTLbWaPrP783PHv8HMAAPjvEkHLaOHMIknqhaIa5236lfBO3r+ljVdYBElBcLvROmwG+ZGtmPNZf7lMhI15xf5TfoaSa84AFRd5J2EXekK6PhaFQhRm1IpSYtwIDAQAB"; npx:hasSignature "xCeYIu0YDLULNkkg3fcXv5iyGF9XPIi0NBGEjdsvU+CJekNtK8Q2RmoH8Stq+MB2VFJl45QBCw6+han0VpnjTOSNfBXJ2eFIN5+VrbiUyqjKWxvgXrXdRHDouKl/UaqsY60lnyGaTi+S+ySzaEATJ8aD4DpQMN0+nHDRXh99tPk="; npx:hasSignatureTarget this:; npx:signedBy orcid:0000-0002-1267-0234 . nt:hasLabelFromApi "Reproduction and Replication of DGGS Benchmark" . }