{
  "title": "Choose the right distribution — Pipe Organ Dataset",
  "text": "MODAVIS (2026). Choose the right distribution — Pipe Organ Dataset. Research notebooks, September 2026 · expanded edition. https://modavis.org/editions/2026-09-r3/dataset/access/",
  "bibtex": "@misc{modavis_dataset_access_2026_09_r3,\n  author = {{MODAVIS}},\n  title = {Choose the right distribution — Pipe Organ Dataset},\n  year = {2026},\n  month = {09},\n  version = {2026-09-r3},\n  url = {https://modavis.org/editions/2026-09-r3/dataset/access/},\n  note = {Content SHA-256: 5db2528cf357dbdec3fd0101d1d57db0b8dfcb150308301148017986f88d6bda}\n}",
  "url": "https://modavis.org/editions/2026-09-r3/dataset/access/",
  "sha256": "5db2528cf357dbdec3fd0101d1d57db0b8dfcb150308301148017986f88d6bda",
  "edition": "2026-09-r3",
  "date": "2026-09-26",
  "canonicalPayload": "{\"book\":{\"number\":\"05\",\"slug\":\"dataset\",\"title\":\"Pipe Organ Dataset\"},\"chapter\":{\"blocks\":[{\"headers\":[\"Distribution\",\"Suitable for\"],\"rows\":[[\"Navigator\",\"Interactive discovery and source-aware comparison.\"],[\"Public-core SQLite\",\"Local queries against the public relational corpus.\"],[\"Lite and application projections\",\"Smaller, task-oriented subsets for particular workflows.\"],[\"PostgreSQL projection\",\"Restoring the public relational corpus in a database server.\"],[\"N-Triples distributions\",\"Working with complete semantic mapping profiles.\"],[\"JSONL catalogue summaries\",\"Lightweight catalogue inspection, rather than full graph analysis.\"]],\"type\":\"table\"},{\"text\":\"Download files from the exact Zenodo version record. The record includes file sizes, checksums, methods, schemas and a changelog. Consult those materials before choosing a large distribution.\",\"type\":\"p\"},{\"items\":[{\"detail\":\"The fixed dataset release, methods and checksums.\",\"href\":\"https://doi.org/10.5281/zenodo.22308263\",\"label\":\"Pipe Organ Dataset 1.6.0\"}],\"type\":\"links\"},{\"id\":\"citation\",\"text\":\"An exact release citation\",\"type\":\"heading\"},{\"label\":\"Dataset reference\",\"text\":\"Ukolov, D. (2026). MODAVIS Pipe Organ Dataset (POD)\\n(Version 1.6.0) [Data set]. Zenodo.\\nhttps://doi.org/10.5281/zenodo.22308263\",\"type\":\"code\"},{\"text\":\"The dataset contribution is distributed under CC BY 4.0. Original sources, linked media and software retain their applicable rights; the dataset license does not grant unrestricted rights to those materials.\",\"type\":\"p\"},{\"id\":\"choose-input\",\"text\":\"Choose the smallest adequate starting point\",\"type\":\"heading\"},{\"text\":\"Begin with the research question and the required relationships. A map-oriented projection can be convenient for geographic browsing; an account-level analysis may require the public core or a research distribution. Check the documented profile rather than assuming that a smaller database contains every table and qualification of the full release.\",\"type\":\"p\"},{\"id\":\"inspect-sqlite\",\"text\":\"Inspect a downloaded SQLite database without changing it\",\"type\":\"heading\"},{\"label\":\"Python standard library · after unpacking your chosen SQLite distribution\",\"text\":\"from pathlib import Path\\nimport sqlite3\\n\\npath = Path(\\\"your-downloaded-database.sqlite\\\").resolve()\\n# Read-only mode fails if the file does not exist.\\nwith sqlite3.connect(path.as_uri() + \\\"?mode=ro\\\", uri=True) as db:\\n    rows = db.execute(\\n        \\\"SELECT name FROM sqlite_schema \\\"\\n        \\\"WHERE type = ? ORDER BY name\\\", (\\\"table\\\",)\\n    )\\n    for (name,) in rows:\\n        print(name)\",\"type\":\"code\"},{\"text\":\"This first inspection deliberately makes no assumptions about table names. Compare the result with the release’s schema and profile documentation before writing domain queries. Keep the downloaded input unchanged and write analysis outputs elsewhere. If you unpack a compressed file, distinguish the download checksum from the identity of the unpacked database.\",\"type\":\"p\"},{\"id\":\"other-distributions\",\"text\":\"For semantic and server-based work\",\"type\":\"heading\"},{\"text\":\"Use the complete N-Triples distributions when the analysis requires the full chosen mapping profile. Catalogue summaries are lighter discovery products and do not establish complete graph coverage. A server projection can support a different execution environment while still requiring a pinned release, documented restore and explicit query method.\",\"type\":\"p\"},{\"items\":[\"Record the version DOI and exact filenames before processing.\",\"Check the repository file information and the release’s checksum inventory.\",\"Read schema, methods, profile descriptions and known limitations together.\",\"Save queries, exclusions and output identities alongside the analysis.\"],\"type\":\"list\"}],\"intro\":\"Start with the form of access that fits your question and computing environment.\",\"slug\":\"access\",\"sources\":[{\"detail\":\"The fixed dataset release, methods and checksums.\",\"href\":\"https://doi.org/10.5281/zenodo.22308263\",\"label\":\"Pipe Organ Dataset 1.6.0\"}],\"title\":\"Choose the right distribution\"},\"date\":\"2026-09-26\",\"edition\":\"2026-09-r3\",\"figures\":{}}",
  "payload": {
    "edition": "2026-09-r3",
    "date": "2026-09-26",
    "book": {
      "slug": "dataset",
      "title": "Pipe Organ Dataset",
      "number": "05"
    },
    "chapter": {
      "slug": "access",
      "title": "Choose the right distribution",
      "intro": "Start with the form of access that fits your question and computing environment.",
      "blocks": [
        {
          "type": "table",
          "headers": [
            "Distribution",
            "Suitable for"
          ],
          "rows": [
            [
              "Navigator",
              "Interactive discovery and source-aware comparison."
            ],
            [
              "Public-core SQLite",
              "Local queries against the public relational corpus."
            ],
            [
              "Lite and application projections",
              "Smaller, task-oriented subsets for particular workflows."
            ],
            [
              "PostgreSQL projection",
              "Restoring the public relational corpus in a database server."
            ],
            [
              "N-Triples distributions",
              "Working with complete semantic mapping profiles."
            ],
            [
              "JSONL catalogue summaries",
              "Lightweight catalogue inspection, rather than full graph analysis."
            ]
          ]
        },
        {
          "type": "p",
          "text": "Download files from the exact Zenodo version record. The record includes file sizes, checksums, methods, schemas and a changelog. Consult those materials before choosing a large distribution."
        },
        {
          "type": "links",
          "items": [
            {
              "label": "Pipe Organ Dataset 1.6.0",
              "href": "https://doi.org/10.5281/zenodo.22308263",
              "detail": "The fixed dataset release, methods and checksums."
            }
          ]
        },
        {
          "type": "heading",
          "text": "An exact release citation",
          "id": "citation"
        },
        {
          "type": "code",
          "label": "Dataset reference",
          "text": "Ukolov, D. (2026). MODAVIS Pipe Organ Dataset (POD)\n(Version 1.6.0) [Data set]. Zenodo.\nhttps://doi.org/10.5281/zenodo.22308263"
        },
        {
          "type": "p",
          "text": "The dataset contribution is distributed under CC BY 4.0. Original sources, linked media and software retain their applicable rights; the dataset license does not grant unrestricted rights to those materials."
        },
        {
          "type": "heading",
          "text": "Choose the smallest adequate starting point",
          "id": "choose-input"
        },
        {
          "type": "p",
          "text": "Begin with the research question and the required relationships. A map-oriented projection can be convenient for geographic browsing; an account-level analysis may require the public core or a research distribution. Check the documented profile rather than assuming that a smaller database contains every table and qualification of the full release."
        },
        {
          "type": "heading",
          "text": "Inspect a downloaded SQLite database without changing it",
          "id": "inspect-sqlite"
        },
        {
          "type": "code",
          "label": "Python standard library · after unpacking your chosen SQLite distribution",
          "text": "from pathlib import Path\nimport sqlite3\n\npath = Path(\"your-downloaded-database.sqlite\").resolve()\n# Read-only mode fails if the file does not exist.\nwith sqlite3.connect(path.as_uri() + \"?mode=ro\", uri=True) as db:\n    rows = db.execute(\n        \"SELECT name FROM sqlite_schema \"\n        \"WHERE type = ? ORDER BY name\", (\"table\",)\n    )\n    for (name,) in rows:\n        print(name)"
        },
        {
          "type": "p",
          "text": "This first inspection deliberately makes no assumptions about table names. Compare the result with the release’s schema and profile documentation before writing domain queries. Keep the downloaded input unchanged and write analysis outputs elsewhere. If you unpack a compressed file, distinguish the download checksum from the identity of the unpacked database."
        },
        {
          "type": "heading",
          "text": "For semantic and server-based work",
          "id": "other-distributions"
        },
        {
          "type": "p",
          "text": "Use the complete N-Triples distributions when the analysis requires the full chosen mapping profile. Catalogue summaries are lighter discovery products and do not establish complete graph coverage. A server projection can support a different execution environment while still requiring a pinned release, documented restore and explicit query method."
        },
        {
          "type": "list",
          "items": [
            "Record the version DOI and exact filenames before processing.",
            "Check the repository file information and the release’s checksum inventory.",
            "Read schema, methods, profile descriptions and known limitations together.",
            "Save queries, exclusions and output identities alongside the analysis."
          ]
        }
      ],
      "sources": [
        {
          "label": "Pipe Organ Dataset 1.6.0",
          "href": "https://doi.org/10.5281/zenodo.22308263",
          "detail": "The fixed dataset release, methods and checksums."
        }
      ]
    },
    "figures": {}
  }
}