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Organizations

Jun 13, 20243 min read

Introduction

The Organizations dataset is a critical component of the open-source intelligence platform, designed to capture detailed information about various entities such as companies, non-profits, government bodies, and other types of organizations. This dataset helps to map out the relationships between organizations, their members, and the events they are involved in. By providing a thorough structure for recording and analyzing data, the Organizations dataset facilitates a deeper understanding of organizational networks and their impact on different events.

Core Organization Data:

  1. Organization ID:

    • A unique identifier for each organization.

  2. Name:

    • The full legal name of the organization.

  3. Aliases/Other Names:

    • Any known aliases or alternative names the organization might use.

  4. Type:

    • The type of organization (e.g., corporation, non-profit, government agency).

Metadata for Context and Details:

  1. Founded Date:

    • The date when the organization was founded.

  2. Headquarters Location:

    • The main location of the organization’s headquarters, including address, city, state, country, and geocoordinates (latitude and longitude).

  3. Description:

    • A brief description of the organization’s purpose, mission, and activities.

  4. Key Personnel:

    • List of key personnel within the organization, such as executives or founders, linked to their person IDs.

  5. Website:

    • The official website of the organization.

Additional Data for Connections and Activities:

  1. Industry/Sector:

    • The industry or sector the organization operates in (e.g., finance, healthcare, technology).

  2. Subsidiaries/Affiliates:

    • List of any subsidiaries or affiliated organizations, linked to their organization IDs.

  3. Related Events:

    • A list of events the organization is involved in, linked to event IDs.

  4. Financial Information:

    • Relevant financial information such as revenue, funding, or financial reports.

  5. Regulatory Filings:

    • Links or references to regulatory filings or official documents (e.g., SEC filings, annual reports).

  6. Social Media Profiles:

    • Links to any known social media profiles.

  7. Contact Information:

    • Additional contact details (e.g., general email, phone number).

  8. Known Associates:

    • Other organizations or individuals known to be associated with this organization, linked to their IDs.

  9. Keywords/Tags:

    • Keywords or tags that help categorize the organization’s activities or roles.

  10. Media:

    • Links to relevant media (e.g., news articles, press releases, interviews).

  11. Notes:

    • Any additional notes or comments about the organization that might be relevant for the dataset.

Example of an Organization Entry:

{
  "organization_id": "O12345",
  "name": "Global Finance Inc.",
  "aliases": ["GFI", "Global Finance"],
  "type": "Corporation",
  "founded_date": "1995-08-15",
  "headquarters_location": {
    "address": "456 Market Street",
    "city": "New York",
    "state": "NY",
    "country": "USA",
    "geocoordinates": {
      "latitude": 40.7128,
      "longitude": -74.0060
    }
  },
  "description": "Global Finance Inc. is a leading financial services company providing a range of services including investment banking, asset management, and financial advisory.",
  "key_personnel": ["P123", "P456"],
  "website": "https://www.globalfinance.com",
  "industry_sector": "Finance",
  "subsidiaries_affiliates": ["O678", "O910"],
  "related_events": ["E789", "E101"],
  "financial_information": {
    "revenue": "10 billion USD",
    "funding": "500 million USD"
  },
  "regulatory_filings": [
    "https://sec.gov/filing/123456",
    "https://globalfinance.com/annualreport2023.pdf"
  ],
  "social_media_profiles": {
    "twitter": "https://twitter.com/globalfinance",
    "linkedin": "https://linkedin.com/company/globalfinance"
  },
  "contact_information": {
    "email": "info@globalfinance.com",
    "phone_number": "+1234567890"
  },
  "known_associates": ["P789", "O112"],
  "keywords": ["finance", "banking", "investment"],
  "media": [
    "https://news.example.com/article/globalfinance",
    "https://press.globalfinance.com/release/2023"
  ],
  "notes": "Under investigation for alleged financial misconduct in 2022."
}

Linking with Other Data Types:

  • People Dataset:

    • Link key personnel and associates to their unique person IDs.

  • Events Dataset:

    • Link each event with the organizations involved using their unique organization IDs.

Conclusion

By structuring the Organizations dataset with detailed and comprehensive metadata, you create a robust framework for tracking and analyzing the connections between organizations, their members, and the events they are involved in. This detailed approach enhances the clarity and usability of the dataset for public information and investigative purposes.

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