During the second half of 2024, X (formerly Twitter) received 97,006 removal requests from government entities. In October 2022, Elon Musk acquired Twitter for 44 billion US dollars. As a result of the deal, the company was taken off the stock market and no transparency reports were available in 2022 and 2023.

High Frequency Indicator: This dataset compiles year- and month-wise data from 2021 to the present on the number and distribution of user grievances received by X (formerly Twitter), along with the actions taken by the platform. The data is based on the monthly transparency reports published under Rule 4(1)(d) of the Information Technology (Intermediary Guidelines and Digital Media Ethics Code) Rules, 2021.

From June 2021 to August 2025, X reported grievance data in absolute numbers across various categories such as illegal activities, IP-related infringements, Abuse/Harassment, Child Sexual Exploitation, Defamation, Hateful Conduct, Impersonation, Misinformation, etc. During this period, the dataset reflects these absolute values directly.

Beginning September 2025, X discontinued reporting grievance counts by category in absolute numbers and instead published percentage share distributions of grievances and URLs actioned. The transparency reports continued to provide the total number of grievances received and total URLs actioned, from which the dataset estimates the absolute category-wise values by applying the reported percentage shares. Additionally, for comparability across the entire time series, percentage shares for months prior to September 2025 have been computed based on the reported absolute values.

This statistic lists the ** most transparent companies in the world with regards to corporate reporting in 2014, as calculated by Transparency International. On the transparency index scale a score of * is considered the least transparent and a score of ** is considered the most transparent. According to this source, Eni was rated as the most transparent company with a score of ***.

High Frequency Indicator: The dataset contains year- and month-wise compiled data from the year 2021 to till date on number general queries received by X (Twitter) about its user accounts.

The data compiled is based on the monthly transparency reports published by Koo in accordance with Rule 4(1)(d) of the Information Technology (Intermediary Guidelines and Digital Media Ethics Code) Rules, 2021 (IT Rules, 2021)

General description

This data file is a compilation of national greenhouse gas emissions (GHG) inventories, sourced from the Common Reporting Tables (CRTs) that countries submit to the UNFCCC. The CRTs themselves require significant manipulation before one can begin any data analysis. The objective of this dataset is therefore to put the national inventories into a tidy, consistent format that better suits user needs. I sourced the original CRT files from the UNFCCC (e.g. https://unfccc.int/ghg-inventories-annex-i-parties/2024; https://unfccc.int/first-biennial-transparency-reports) and reformatted their summary reports into a single tidy, structured data table.

Data structure

The national GHG inventories provide emissions estimates along four dimensions: countries x years x sectors x gases.

Countries: currently only Annex I countries consistently submit CRTs each year. Non-Annex I countries submit at irregular intervals, although this may change. Recently there have also been significant delays in submissions as as countries move to the new reporting format. The full list of countries covered and associated files is in the "countries" tab of the spreadsheet.

Years: reporting starts in 1990 and runs until two years prior to the publication of each inventory (e.g. inventories submitted in 2024 report up to 2022).

Sectors: emissions are split into sectors as set out by the Intergovernmental Panel on Climate Change (IPCC) Task Force on National Greenhouse Gas Inventories (TFI). The six main sectors are (1) Energy, (2) Industrial processes and product use, (3) Agriculture, (4) Land use, land-use change and forestry, (5) Waste, and (6) Other. A general description of the sectors is available in the TFI guidance. In this data file the five high level sectors are split into 41 individual categories, which is the most detailed level of reporting provided in the CRT summary sheets. I have included only the data from "leaf nodes" in the sector hierarchy, which are sectors that have no further child sectors. This means that you can safely sum up all sectors for each country without double counting. The higher level sector categories are provided as variables for convenient aggregation. The "sector" tab of the spreadsheet shows which sectors are included and how they fit into the TFI hierarchy. Memo items like international bunkers are provided as a separate tab in the data files (currently with emissions values for all available levels of the hierarchy).

Gases: countries report emissions from CO2, CH4, N2O and F-gases (HFCs, PFCs, NF3, SF6). I have converted emissions from the different gases to CO2 equivalents using global warming potentials with a 100 year time horizon from the IPCC 5th Assessment Report (GWP100 AR5). More recent GWP100 values have been published in the IPCC AR6, but I have not yet figured out if it is possible to extract F-gases from every CRT in original units, which would be necessary to update the values. CH4 and N2O can be reconverted into their original units by dividing by 28 and 265, respectively. A full list of global warming potentials can be found here.

What can I use this data for?

The national GHG inventories are a formal part of the Paris Agreement and are intended to facilitate the tracking of progress towards national and global climate objectives. As such this data can be used to evaluate whether or not countries are progressing towards their stated goals (e.g. the NDCs and long-term net zero targets). It can also be used for a wide range of other applications, such as to track the effectiveness and outcomes of different policy interventions. Finally, it provides insight on which countries have fulfilled their obligations under Paris to submit timely and complete Biennial Transparency Reports.

The dataset is currently not complete for all countries. It is therefore not suited to tracking total global GHG emissions. For that purpose, I recommend to use one of the other 3rd party datasets such as EDGAR, PRIMAP, CEDS, or the Global Carbon Budget for CO2 emissions.

Note that there is also an ongoing debate on the differences between national inventory reporting of LULUCF emissions and removals versus estimates from global bookkeeping models. This has significant implications for national and global net zero targets. It is important to be aware of those nuances when using national inventory LULUCF data.

Summary figures

You can find here: https://lambwf.github.io/Tidy-GHG-Inventories/

Potential future updates

Country coverage: I will semi-regularly check the UNFCCC submissions and include new CRTs as they are released.

Activity data: The CRTs contain underlying data on activities, fuel use and emissions factors. These are especially useful for tracking changes and attributing the impacts of policies. I may start to include these in future versions as a separate sheet.

Code availability

The Github repository is here: https://github.com/lambwf/Tidy-GHG-Inventories/

And the main script for extracting CRTs is here: https://github.com/lambwf/Tidy-GHG-Inventories/blob/main/read_crts.Rmd

Changelog

v1.0

The data is now available in two sheets: a "long" and a "wide" version.

The European Union has been created from individual national sheets of the EU-28, as it has not yet submitted a CRT.

The data now includes memo items (e.g. intl. bunkers, multilateral operations, etc.) as a separate tab.

3 countries are currently excluded as they submitted non-standard CRTs (e.g. they have missing sheets or different layouts): Tunisia, Venezuela and Zimbabwe

78 countries are available as of this version.

v0.3

10 new countries added with recent CRTs

There is now an issue with Ghana: totals do not match the bottom up accounts. Reason currently unknown.

v0.2

13 new countries added with recent CRTs

Fixed an issue where N2O emissions on unspecified managed soils were not included in bottom-up estimates for several countries. This required creating a new category in the LULUCF sector with the sector code "4.x." to capture the residual emissions here.

Fixed an issue where reported "Unspecified mix of HFCs and PFCs" were not included

Proprietary Database, Market Surveys, Strategic Consultation & Advisory Services, Industry & Competitive Intelligence. along with Report Access and Athenaeum Dashboard Subscription — Revenue, Volume, Production, Trade Analysis, value chain and supply chain analysis, Market Size, Share, Forecast, Drivers, Trends, Growth Opportunities, ESG and more.

Discover the booming X-ray detectable masterbatches market! This in-depth analysis reveals key trends, growth drivers, and leading companies shaping this crucial sector for food safety and product traceability. Explore market size projections, CAGR, and regional insights for the period 2025-2033.

Transparent polycrystalline ceramics present significant economical and functional advantages over single crystal materials for optical, communication, and laser technologies. To date, transparency in these ceramics is ensured either by an optical isotropy (i.e., cubic symmetry) or a nanometric crystallite size, and the main challenge remains to eliminate porosity through complex high pressure–high temperature synthesis. Here we introduce a new concept to achieve ultimate transparency reaching the theoretical limit. We use a controlled degree of chemical disorder in the structure to obtain optical isotropy at the micrometer length scale. This approach can be applied in the case of anisotropic structures and micrometer scale crystal size ceramics. We thus report Sr1+x/2Al2+xSi2–xO8 (0 < x ≤ 0.4) readily scalable polycrystalline ceramics elaborated by full and congruent crystallization from glass. These materials reach 90% transmittance. This innovative method should drive the development of new highly transparent materials with technologically relevant applications.

Explore the booming Catena-X Automotive Network market analysis, drivers, and future growth from 2025-2033. Discover key insights and trends shaping automotive supply chain digitalization.

Delve.co Audit Reports Exposure - Public Analysis & Documentation (2025-2026)

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Overview

This dataset provides publicly available documentation and analysis related to the controversy surrounding Delve.co (delve.co), a Y Combinator W24-backed AI compliance automation startup.

In late 2025, a publicly accessible Google Spreadsheet containing links to hundreds of draft audit reports (SOC 2, ISO 27001, and others) was discovered and widely discussed online. This led to a detailed anonymous investigation published on Substack in March 2026 by "DeepDelver". The story spread rapidly on Hacker News, Reddit (/r/startups), TechCrunch, and X, raising questions about templated reports, evidence generation, associated audit firms, and potential client risks.

Key public allegations (still under debate as of March 2026): - High similarity across many draft reports (reportedly ~99.8% identical text in some analyses, with only company-specific details changed). - Pre-generated auditor conclusions and evidence appearing before full client input. - Use of a limited set of audit firms (e.g., Accorp for SOC 2, Gradient Certification for ISO 27001). - Potential implications for clients under frameworks like HIPAA and GDPR.

Delve.co's response (from their official blog): - They provide an automation platform only and do not issue final audit reports. - Final reports and opinions come solely from independent, licensed auditors. - They use templates and drafts (common industry practice) and are investigating the reported spreadsheet exposure. - They describe some claims as misleading.

The incident has sparked broader discussion on AI-powered compliance tools, the importance of independent verification, and data exposure risks.

Dataset Content – Important Note

This dataset is for research, transparency, and educational purposes only.

It contains NO raw confidential client documents, full private audit reports, PII, or sensitive customer data.

Instead, it includes four zip files with publicly discussed overviews, extracted patterns, metadata summaries, and related documentation derived from open sources and analyses circulating online.

Files Included:

• docx_reports.zip (572.7 MB) — Publicly referenced DOCX-format overviews and pattern extractions.
• pdf_reports.zip (723.0 MB) — Publicly referenced PDF-format summaries and analyses.
• txt_reports.zip (13.2 MB) — Text-based metadata, timelines, and pattern notes.
• overview_docs.zip (254 KB) — General overviews, disclaimers, source links, and methodology.

All materials are based on open-web discussions (Substack, news articles, forum threads). No actual leaked private reports are hosted here.

Usage Notes & Disclaimer

• Intended for: Cybersecurity researchers, compliance professionals, journalists, students, and anyone studying startup governance, data exposure incidents, or regulatory compliance challenges.
• Not legal or financial advice: All details remain allegations or public interpretations as of March 2026. Always verify with primary sources and consult qualified professionals.
• Data Sensitivity: Strictly limited to publicly available summaries and patterns. Do not use this dataset to re-identify, target, or harm any individuals or companies.
• Ongoing Situation: Discussions continue (including Part II hints from DeepDelver and further coverage). Delve is investigating the reported exposure.
• License: CC0 where possible. Respect all original source copyrights for any quoted material.

Related Public Resources

• Original Substack investigation (Part I): https://deepdelver.substack.com/p/delve-fake-compliance-as-a-service
• Delve Official Response: https://delve.co/blog/response-to-misleading-claims
• TechCrunch and other coverage: Search "Delve fake compliance" (articles from March 2026)
• Hacker News thread: Search "Delve – Fake Compliance as a Service" on news.ycombinator.com
• Reddit discussions: r/startups PSA thread and related posts

Community contributions of additional verified public sources are welcome via Kaggle discussions (please keep everything non-sensitive and properly sourced).

Created for transparency and learning in the compliance technology ecosystem.