Open data is most useful when it is not merely downloadable, but explainable.
At DataCheck Research, we publish a small, reusable dataset of Israeli company-registration and status-change trends. The objective is not to claim that one monthly count explains the economy. It is to make a constrained question reproducible: what changed in the register, when, and according to which sources?
The modelling choice
A registration date, a dissolution event and a registry status update are not interchangeable. In particular, an update appearing in a public register may lag the legal event behind it. Treating all status changes as the same event creates a chart that looks decisive but is methodologically weak.
We therefore keep separate series for registrations and status changes, document their provenance, and label the combined series as a net-movement proxy rather than a census of operating businesses.
What a reusable public dataset needs
- Provenance. Every series should lead back to its source and extraction method.
- Scope. State what the record represents and what it does not.
- Stable fields. A lightweight CSV is often more durable than a dashboard-only chart.
- Citation. Reuse should preserve visible attribution to the original source.
- A human explanation. Metadata is not a substitute for a method note.
The repository includes CSV files, methodology, contribution guidance and a citation file. It is released under CC BY 4.0: reuse is welcome with visible credit and a link back to the source.
- Dataset and methodology: https://github.com/DataCheckResearch/israel-company-trends-data
- Interactive company trends: https://datacheck.co.il/trends
A public dataset earns trust when a skeptical reader can understand where it came from, what changed, and where its limits are.
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