JUDGIT!…this database allows users to look up how the Japanese national budget is being spent.
This is available for free, everyone can use it, and it can be useful to investigate journalism.
The data we have parsed is available as open data.
Using this database, we can investigate the actual flow of government money, and find the misuse of the fund.
The best part of this DB is that we can look into who and what the money was spent for, not just the amount of the budget.
For example, we examined by focusing on the special account for Fukushima reconstruction.
Search “Special Account for Recovery from the Great East Japan Earthquake” and we found there were “16 reconstruction projects” in “Ministry of Defense”.
- Data extraction of Excel file by Python.
- Data cleansing with Python
- D3.js, crossfilter.js and DC.js.
What was the hardest part of this project?
A. Data cleansing.
Since the original data of JUDGIT! was Excel, and officials have input the data manually.
Identification of names of the organization like ministries, bureau, and the department has required.
B. Collaborative journalism.
To make invisible data visible, journalists must have collaboration with other professionals like data engineers and designers or other specialists
What can others learn from this project?
JUDGIT! is in collaboration with four parties.
Japan Initiative has proposed and realized a system for reviewing Japanese government projects.
VdsLab has created a BigQuery database from Excel files that have been published only for printing.
Visualizing.JP has enabled exploratory visualization to find the hypothesis.
Waseda Chronicle has started using this database to begin investigative journalism.
This could not have been realized even if only one organization was missing.
Although the government disclosed information publicly as open data, it is often the case that the government offers it with low searchability or low accessibility. It was the same in this case.
To make invisible data visible, journalists must have collaboration with other professionals like data engineers and designers or other specialists.
In your country, there must be “Hidden Open Data.” Please find it, and make it open!