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Infrastructure curated datamesh

The motivation behind the datamesh is rooted in the idea to build systems that can learn from multi-modal data and bring transparency to enhance the decisions process, particularly pertaining to the infrastructure sector. The ability to have local and global data across a variety of sources ready for synthesis will help inform decision use cases that we are not even aware of.

In our system design, we think about two high-level decision-use cases:

  • Opportunities
    • One in every three dollars spent by the government is on a contract with a company. Public contracting is the world’s largest marketplace, covering $13 trillion of spending every year.”
    • Inspired by the work of the Open Contracting Partnership, our work on scoping data around various development opportunities through projects,tenders, news, brownfield assets is to follow standards to bring transparency to the world’s largest marketplace.

  • Risks (or Outcomes

    • Risk or Outcomes based data related standards are inspired by existing frameworks including:
    • ISO 3100
    • Open Risk Manual — Risk Data Standards
    • The Risk Data Open Standards (RDOS)
    • The growing standards around specific domains such as international economy (for example, the Special Data Dissemination Standard (SDDS), or evolving threats across Sustainability, Environment Social Governance (ESG), or Climate, where lack of standards are still evolving
    • The goal is to provide a more comprehensive connection across domains and streams of risk discussions, both broad and in depth.
      The goal is to provide a more comprehensive connection across domains and streams of risk discussions, both broad and in depth.
      Our offering represents the largest collection of clean and standardized infrastructure specific data in the world. It has been assembled by aggregating over XXX data sets collected into our proprietary Taiyo datamesh. By standardizing and organizing these global, disparate data sets in a way that allows them to reference each other, we aim to provide:

  • The most comprehensive and seamless collection of project intelligence (both current opportunities and past projects)

  • The most robust universe of data from which business leaders can identify trends, correlations and/or coincident factors that may not have been obvious from traditional analysis.