data catalog

Explore and Influence our Growing Collection of Datasets

Dive into our current catalog, featuring key environmental and regulatory datasets. Your feedback on these and upcoming datasets is crucial, as it helps shape the future of our offerings.
Coming soon
Air & Water Pollution
Dataset on corporate toxic air emissions (e.g., NOx, SOx, VOCs, CO, particulates) and corporate water pollution-related metrics (e.g., heavy metals, nitrates, phosphates, chemical and biological oxygen demand).
Coming soon
Biodiversity & Deforestation
Dataset on corporate biodiversity and deforestation efforts, including policies, commitments, traceability, habitat restoration, impact on IUCN Red List species, and proximity to protected or high biodiversity areas.
Coming soon
Energy Targets
Dataset on corporate targets to reduce energy consumption and increase the share of renewable energy in their energy mix.
Coming soon
Waste Targets
Dataset on corporate targets to reduce waste generated and increase waste recycling/recovery rates.
Coming soon
Water Management
Dataset covering corporate water flows, detailing inflow sources (withdrawal and recycling), usage and consumption, and outflows (discharge and disposal), with attributes on water quality, stress area classification, and treatment status.
Coming soon
Water Targets
Dataset on corporate targets to reduce water consumption, decrease withdrawals in high water stress areas, increase water recycling/reusability rates, and improve overall water use efficiency.
Coming soon
Board of Directors
Dataset covering board duration and tenure, meeting frequency and attendance, diversity (gender, ethnicity, race, age), composition and independance, compensation, board structure, policies, and shareholding.
Coming soon
Board Committees
Dataset covering committee duration and tenure, meeting frequency and attendance, diversity (gender, ethnicity, race, age), composition and independance, compensation, and policies for various committees (Audit, Compensation, Nomination, Executive, etc.).
Coming soon
Executive Management
Dataset covering executive management duration and tenure, diversity (gender, ethnicity, race, age), composition, compensation, policies, and shareholding.
Coming soon
Auditors
Dataset on auditors, including the name of the audit firm, tenure, fees paid, sustainability auditing practices, independence, rotation policies, and any noted conflicts of interest.
Coming soon
Shareholders
Dataset covering shareholder composition, major shareholders, ownership percentages, voting rights, shareholder engagement practices, dividends paid, shareholder resolutions, and proxy voting outcomes.
Coming soon
Business Ethics & Fines
Dataset covering the number and amount of fines related to various compliance issues (e.g. product safety, anti-competition, bribery and corruption, environmental violations, labor practices), political donations, and related corporate policies.
Coming soon
Fundamentals
Dataset on fundamentals, capturing both reported and standardized balance sheets, income statements, and cash flow statements.
Coming soon
Corporate Structure
Dataset on corporate structure, covering companies' subsidiaries and joint ventures, including parent-child ownership details, location, and name.
Coming soon
Revenues Segmentation
Dataset on revenue segmentation, capturing companies' revenue breakdown by business segment and geographical region.
Coming soon
Materiality Assessment
Dataset providing a standardized view of corporate materiality, including normalized rankings of critical topics based on importance to stakeholders and materiality impact on the company.
Coming soon
Workforce Headcount
Dataset covering corporates' total number of employees, employment ratio (FTEs and full-time/part-time breakdown), reliance on external workers (e.g., contractors, seasonal workers), and compensation types (e.g., hourly, salaried, commissioned).
Coming soon
Workforce Diversity, Equity and Inclusion (DEI)
Dataset covering gender diversity, race and ethnic diversity, disability, age, hierarchical roles, and gender pay gap.
Coming soon
Workforce Turnover & Retention
Dataset on workforce turnover and retention, including turnover rates (voluntary and involuntary) and employee length of service.
Coming soon
Workforce Health & Safety
Dataset covering fatalities, lost time incident rate (LTIR), total recordable incident rate (TRIR), lost working days, vehicle incident rate, number and rate of accidents, and occupational disease cases and rates.
Coming soon
Workforce Training & Development
Dataset covering workforce training costs, hours spent by employees, training policies, and training types (e.g., management, health & safety, supply chain).
Coming soon
Supply Chain Standards
Dataset covering supplier audit practices (percentage and numbers), supplier compliance, ethical and environmental sourcing, certifications, and risk management.
Coming soon
Community Relations
Dataset covering corporate philanthropy, community engagement initiatives, volunteer hours, and partnerships with non-profit organizations.
Coming soon
Product Responsibility
Dataset covering product safety and quality, customer satisfaction, recall procedures, lifecycle assessments, sustainable sourcing of materials, and transparency in labeling.
Coming soon
Respect of Human Rights
Dataset covering corporate policies on human rights, due diligence processes, supply chain labor practices, anti-discrimination measures, grievance mechanisms, and community impact assessments.
Data
Catalog
Philosophy
At Tracenable, we believe that finding the right data should be simple, precise, and intuitive. That's why we've structured our data catalog into four logical layers, each designed to help you navigate seamlessly from broad topics to specific data points:
  • Categories: The catalog begins with four primary categories that reflect high-level areas of corporate sustainability: Environmental, Social, Governance, and Other.
  • Datasets: Within each category, data is organized into thematic sets that represent specific sustainability and performance topics.
  • Dimensions: Each thematic is enriched by one or more dimensions, which provide different ways of analyzing or slicing the data.
  • Metrics: Metrics are the most granular layer. Each metric represents a unique combination of dimensions that defines a specific data point.