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NOTEBOOK 05

Pipe Organ Dataset

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Choose the right distribution

Start with the form of access that fits your question and computing environment.

DistributionSuitable for
NavigatorInteractive discovery and source-aware comparison.
Public-core SQLiteLocal queries against the public relational corpus.
Lite and application projectionsSmaller, task-oriented subsets for particular workflows.
PostgreSQL projectionRestoring the public relational corpus in a database server.
N-Triples distributionsWorking with complete semantic mapping profiles.
JSONL catalogue summariesLightweight catalogue inspection, rather than full graph analysis.

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.

An exact release citation

Dataset reference
Ukolov, D. (2026). MODAVIS Pipe Organ Dataset (POD)
(Version 1.6.0) [Data set]. Zenodo.
https://doi.org/10.5281/zenodo.22308263

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.

Cuntz · Illustrative scenario#

Which Cuntz identifier belongs in a citation?

Versioned citation separates the physical subject, the released research object and the explanation or derived artifact actually used.

Work through the example 3 STEPS

A reader uses the notebook’s model to discuss a geometry, while another uses the 1281 mm workbook observation. Their references should identify different evidence even though both concern Cuntz.

  1. Identify the release

    Use version DOI 10.5281/zenodo.22151203 for the inspected dataset. Record the specific realization or observation, rather than citing only the project community.

  2. Identify what was used

    For the web preview, retain the derivative’s digest and transformation note. For the observation, identify the pipe, property, source cell and workbook realization.

  3. Cite the explanation separately

    Use “Cite this page” for the notebook’s fixed edition. Its fingerprint identifies the explanation; it does not replace the source dataset or model fingerprint.

BASIS FOR THIS EXAMPLE
  • Cuntz Positiv · VAO 0.5.0-rc.2 ↗

    Published manifest: identities, measurement observations, realization digests, profiles and rights. Exact examples checked against this release.

  • VAO Standard 0.5.0 ↗

    The standard contract is separate from the Cuntz dataset content version 0.5.0-rc.2.

The dataset content version 0.5.0-rc.2, VAO format version 0.5.0 and website edition are separate version systems.

The useful distinction. A citation chain lets a reader recover both the evidence and the interpretation.

Choose the smallest adequate starting point

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.

Inspect a downloaded SQLite database without changing it

Python standard library · after unpacking your chosen SQLite distribution
from pathlib import Path
import sqlite3

path = Path("your-downloaded-database.sqlite").resolve()
# Read-only mode fails if the file does not exist.
with sqlite3.connect(path.as_uri() + "?mode=ro", uri=True) as db:
    rows = db.execute(
        "SELECT name FROM sqlite_schema "
        "WHERE type = ? ORDER BY name", ("table",)
    )
    for (name,) in rows:
        print(name)

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.

For semantic and server-based work

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.

  • 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 & further reading

  1. Pipe Organ Dataset 1.6.0

    The fixed dataset release, methods and checksums.

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