Mining Filings Data Quality Report 2026: What Breaks, What Scales, and What Sells

> Key takeaway: Mining data scale is not the hard part. Trustworthy mining data is.

Last Updated: 2026-03-02 | Reading Time: 9 min | Data Source: Mining Terminal live extraction tables snapshot

Quick summary

• Mining Terminal currently tracks 216,759 extracted filings, 905,104 drill intercepts, 263,420 resource estimate rows, and 11,181 project economics rows.
• The content opportunity is real, but the dataset still includes quality issues that matter for ranking, screening, and premium research.
• The winning move is not to hide the QA problem. It is to package it, filter it, and sell the clean workflow.

Dataset scale snapshot

| Dataset | Rows |
| --- | --- |
| Companies | 5,705 |
| Projects | 41,538 |
| Mining extractions | 216,759 |
| Drill intercepts | 905,104 |
| Resource estimates | 263,420 |
| Project economics | 11,181 |

This is enough data to support a real mining content engine. The issue is not volume. The issue is validation discipline.

Where the current dataset still breaks

| Issue | Count |
| --- | --- |
| Failed extractions | 1,453 |
| Future-dated extracted filings | 3 |
| Null company linkage in extractions | 17,975 |
| Null project linkage in economics | 3,822 |
| Economics rows with IRR > 100% | 166 |
| Drill rows with proxy/non-core commodities | 1,611 |

These counts are not theoretical problems. They directly affect what can be published, sold, or benchmarked.

1. Future-dated rows damage trust fast

The live dataset contains 3 extracted filings dated after 2026-03-02. Even if they are document typos, they break confidence in time-series content and create obvious screenshot risk in sales conversations.

2. Linkage gaps reduce institutional usefulness

Premium mining research depends on issuer-level and project-level comparability. When economics or resource rows are missing company or project linkage, the problem is not cosmetic. It distorts peer sets, watchlists, and benchmark books.

3. Drill leaderboards need filters

A raw drill database is not automatically decision-useful. The current intercept corpus includes 1,611 rows tied to gas, radioactivity, or other proxy-style commodities. Those rows can overwhelm naive gram-meter rankings.

What this means for content strategy

This dataset supports two content plays at once:

• Authority content: explain how to audit drill, resource, and economics data properly.
• Premium products: sell cleaned, benchmarked outputs rather than pretending the raw tables are ready-to-trust truth.

Best immediate content assets

• A filings QA report for funds and publishers
• A drill discovery monitor with outlier controls
• A project economics benchmark book with linkage and timestamp filters

Real examples from the live snapshot

| Company | Ticker | Doc type | Future report date |
| --- | --- | --- | --- |
| Omega Pacific Resources Inc. | OMGA | M&APressRelease | 2028-09-18 |
| Hazer Group Limited | HZR | DrillingNewsRelease | 2027-03-21 |
| Nickel Rock Resources Inc. | NICL | Half_Year | 2027-02-27 |

FAQ

Why publish data quality content instead of only polished rankings?

Because sophisticated buyers care more about process integrity than polished marketing. Showing the filter layer increases trust.

Is mining data quality really something buyers will pay for?

Yes. Anything that reduces diligence time, avoids false positives, and creates cleaner comparables has direct commercial value.

What is the best way to monetize this dataset?

Use open SEO content for authority, gated checklists for leads, and filtered benchmark products for premium revenue.

Bottom line

Mining Terminal already has enough extracted filings data to produce premium research and serious SEO content. The edge comes from owning the QA layer, not from pretending the raw corpus is perfect.