The TrueView™ platform consists of high-quality semantically structured data about the environment, people, companies, NGOs and governments. The platform captures or infers both real and financial data at a local, regional, national and global level. It has built-in compass-like indicators that point in the direction of real human and environmental well-being and can evaluate their complex tradeoffs. Aggregations occur along political (e.g., cities, states, countries), environmental (e.g., HUC levels) and demographic (e.g., age, gender, financial) dimensions. The platform uses a new generation of semantic AI combined with old-fashioned statistics to structure, validate, enrich and analyze data. All socio-economic-environmental-political indicators are grounded in one upper level multidimensional ontology that provides a uniquely extensible classification logic, a novel metric for assessing wellbeing that can actually be used to direct resource allocations and a method of pricing eco and community services that supports societal change in fiscally responsible ways.
The platform supports multi-stakeholder collaboration: for monitoring, assessments, analysis, planning, budgeting and decision making. The result is improved community understanding of complex topics, transparent assessments that garner wider stakeholder support, more complete analyses and thus better decisions that improve organizational value and wider stakeholder impact to better wellbeing.
What can TrueView™ do for your Organization?
The TrueView™ platform is comprised of a well-ordered stack of state-of-the-art components that can be efficiently customized to meet your specific needs.
TrueView’s physical layer is a hybrid Geospatial-Relational database that can run on our elastic cloud-hosted environment or on your own.
TrueView’s Ontological Basis Types layer is comprised of a new kind of semantic-AI technology we call a Composable Ontological Representation Engine or C.O.R.E. Developed by our partners at BlenderLogic, who were recently selected by a national government center for AI to present their work on advanced AI algorithms, C.O.R.E. unifies traditional symbolic computing and neural networks in a hybrid neuro-symbolic computing architecture. C.O.R.E. provides a computing basis for all of TrueView's concepts/indicators/attributes/relations in terms of four root types that combine through a grammar that makes it possible to define anything in a traceable fashion, no matter how complex. And it allows for machines to reason with and humans to understand whatever has been created. This is absolutely critical for properly representing and reasoning with the complexities of sustainable economics. C.O.R.E. is the product of over $5M in government funding to solve the problem of reasoning and learning across multiple domains based on any kind of sense data or natural language.
TrueView’s Sustainable Economics Base layer is an extensible set of formal definitions and algorithms combined with high quality data about the environment, people, businesses, NGOs and governments that comprise our world.
It is composed of three layers:
- At the bottom is an extensible classification logic built from an ontological reconstruction of the concepts Stakeholder (e.g., people, companies, governments or the environment) and Capital (e.g., assets/resources as stocks and/or flows) which are common to all representations of any portion of the market economy and/or associated non-market flows. These are built in terms of C.O.R.E.’s ontological basis types
- Sitting on the classification layer is a novel framework for wellbeing (sometimes referred to as vitality, wealth, health, happiness, and/or utility) that does not fall prey to the ‘more is better’ trap of other wellbeing frameworks
- Sitting on top of the wellbeing framework is a formally grounded method to fairly price non-market services (e.g., ecosystem and the human counterpart of ecosystem which we call community services) for the purpose of changing human behavior without going through the computationally and philosophically problematic steps of valuation.
TrueView’s Sustainable Economics Base layer provides a computationally meaningful foundation upon which customers’ additional data, definitions and/or algorithms might be brought to solve their specific problem. It reflects decades of research and international experience in the specifics of integrating and co-computing with real and financial values. Because of its upper ontological grounding, customers can add any relevant data to the platform – data about water or about land use or about demographics or migration, skilled wages, unemployment rates or about state budgets; anything – literally anything, and TrueView can absorb it and relate it in meaningful ways to everything else in the platform.
Our sustainable economics layer also has a built-in notion of a reporting entity and of both financial and non-financial reports. The reports capture stocks and flows, real and financial indicators, quantities and qualities of things and their prices. The TrueView reporting model captures the semantics of both US-based P&L as well as Euro-based Value-Add notions of flow. It can also track assets that are used but not owned by a company such as the people who work for it or are its customers. In short, the TrueView reporting model captures the essential semantics of standard financial reports in a systematic fashion that makes it easy to track in a principled fashion the impact relations that exist between a business, the environment, people, organizations and governments.
TrueView’s Customizable Domain layer includes a growing collection of single and multi-domain data, definitions and algorithms. We currently have platform-enhancing domain-specific data for water rights, land use, municipal assets and at-risk populations. We are continually adding to this collection.
The TrueView platform lets you add any mix of domain-specific information and will always result in a single queryable store of information – never any isolated silos.
Whatever your specific problem, whether you need to integrate water budgets with land use and water rights; or whether you need to project funding needs to take care of persons at risk; or adjust your own financial projections in light of the negative impact your business or your portfolio is having on the environment; you can add your specific data to TrueView, define who the stakeholders are in your world and start solving problems.
TrueView’s Customizable User Interface (UI) layer is comprised of dashboard, messaging and optionally Natural Language Processing (NLP) frameworks that can be customized to meet your specific UI needs.
TrueView’s Customizable Stakeholder layer is comprised of UI templates with embeddable logic that capture the relations that exist and the processes that get realized between stakeholders. For example, when stakeholders span different organizations, data sharing may be restricted. When stakeholders span a chain-of-command, the actions of some stakeholders may create obligations for others. When some stakeholders (e.g., the Earth) are not users of the solution, TrueView can generate a view that includes estimates of that stakeholder’s well-being that all users can see.
TrueView Indicators are intended to enhance your existing reporting with needed ESG impact information captured in real and financial terms. They combine with:
- Financial accounting indicators (e.g., GAAP or FASB)
- Emerging environmental indicators (e.g., the UN SEEA EA)
- Conservation groups’ environment indicators (e.g., TNC, WWF, IUCN)
- Public health indicators (e.g., CDC, RWJF)
- National and international wellbeing indicator frameworks (e.g., New Zealand, Canada and OECD)
- ESG indicator frameworks used in the private sector (e.g., GRI, IRIS).
TrueView indicators also include a suite of meta information indicators (e.g., coverage, sources, accuracy, precision, timeliness) that enable users to implement data-driven processes of continual improvement.
Unlike other wellbeing (or ESG) indicator frameworks, TrueView indicators directly support wellbeing-driven analysis, planning, and budgeting for both public and private sector organizations.
- TrueView indicators can help ESG analysts transform corporate ESG reports into ESG risk-adjusted financials that can be used by investors to better value companies
- TrueView indicators can help national statistics departments turn measures of GDP into measures of societal wellbeing that can be used to drive public policy and budget allocations in support of wellbeing-based budgeting
- TrueView indicators can help ecologists represent the state of the environment in ways that make it easy to see and analyze its interdependencies with human society (including its financial economy) and to calculate the ecosystem service pricing required to achieve societal goals
- TrueView indicators can help planners formulate, in a well-grounded fashion, financially sound projects and portfolios of such projects (whether for corporations, NGOs or governments) whose expected outcome is the improvement of wellbeing for each of its stakeholders
TrueView implementation architectures may include a data ingest component, a data storage component, map, tabular and/or graphic views, an analysis module, a planning module, and a communications module.
Semantically Structured Data
Sustainability minded researchers and policy analysts are drowning in data. There are hundreds of government- and NGO-produced data sources on almost every facet of human society and the environment.
The problem is each data source stands on its own. Thinking of data sources as drinks, each data source comes with its own straw. It’s Babel; it’s crazy; it’s data chaos.
Solving the data chaos problem means combining all the data sources in a meaningful way so that users can ingest all the data with just one straw.
A lot of research has gone into solving the data chaos problem. It is a hard problem. And until now, data and software providers use the term ‘semantic’ to mean that all the data under their control can be queried through a single language. The weakness with these kinds of solutions is that they are static. The minute you try to allow researchers to add their research, to extend the database, it’s either not possible within that data framework or the single language aspect of the data is lost. Either way, it’s back to data chaos.
The only way to truly solve the problem of data chaos is to have a kernel of meaning in a multi-dimensional structure that can be extended through subtyping, subdividing, and composition to cover any possible expression. Anything that any researcher might encounter would have to be generatable as a particular subtype and/or component and/or composition of what had gone before. Since BlenderLogic developed the world’s first upper ontology language that provides for subtyping, subdividing and composition, this is why sciGaia has partnered with them to produce TrueView’s semantic data handler. The base dimensions in TrueView e.g., dimensions for stakeholders, capital and wellbeing are derived from BlenderLogic’s ontology engine.