![[Pasted image 20230708140512.png]] Photo by [Petr Magera](https://unsplash.com/@mpetrucho?utm_source=unsplash&utm_medium=referral&utm_content=creditCopyText) on [Unsplash](https://unsplash.com/photos/MwzjyclkQo8?utm_source=unsplash&utm_medium=referral&utm_content=creditCopyText) The role of ontology is to define the scope of what needs to be interpreted. By extrapolation of this axiom into ecosystem way of thinking, our statement is as follows: The #SPHERES (Ecosystem philosophy interpreted as combination of Ecosystem Architecture and Methodology) enables **compositional semantics** (of Ecosystem) with ontology centric knowledge recognition and **situational interpretation** to affected entities / actors. Ratio of Ecosystem interpretation accuracy is tightly connected to selected interpretation techniques (selected machine learning methods) and granularity of entities, their relations and events within the timeline. Furthermore, ecosystem ontology is poised to change continuously - **the only constant is the change**. Temporary recognized and active ecosystem entities are present / prioritized within the ecosystem in dependency of their behavioral patterns or involvement within the ecosystem thresholds categorized as critical factors for ecosystem equilibrium. The current mainstream in technology and business worlds, regards an ontology compliant solutions and systems only as an "good to have" category. Without recognition of benefits achieved by connecting solution concepts with ecosystem abstracts, it is impossible to realistically plan and execute dynamic enterprise transformations and infuse of sustainability to the daily life to customers and consumers. The SPHERES enforces usage of high level ontology concepts with richly **axiomatized ecosystem patterns** applied to critical components of ecosystem. Clearly, the instantiation of #SPHERES approach lacks robustness and deep insights into the ontology and semantic web terminology to support claims mentioned above. However, there is not a deficiency of #SPHERES itself, but of the particular implementation which relies on existing platforms, databases, tools and availability of relevant data sets. Production ready implementation and robustness might be incorporated by creation of dedicated ecosystem repository, decoupled ecosystem agents. frontend visualization and advanced machine learning techniques. Our future work (and long term vision) is devoted to construction of minimum viable products exemplifying value provided by ecosystem thinking for technology and business worlds. --- In information science ontologies are classified in various ways, using criteria such as the degree of abstraction and field of application [1]: - Upper ontology: concepts supporting development of an ontology, meta-ontology. - Domain ontology: concepts relevant to a particular topic, domain of discourse, or area of interest, for example, to information technology or to computer languages, or to particular branches of science. - Interface ontology: concepts relevant to the juncture of two disciplines. - Process ontology: inputs, outputs, constraints, sequencing information, involved in business or engineering processes. Which one is #SPHERES focused on? Fundamentally, #SPHERES is **combination of upper ontology and domain ontology**. Both are represented within the MetaX. The Meta ontology (or upper ontology) is MetaX-s ability to connect and build any MetaSystem and connect it (or not) with existing internal or distributed (external) ontologies. Domain ontology is encapsulated within the #SPHERES itself and represented in MetaX by particular Ecosystem which itself can be used as a domain ontology (an ecosystem blueprint). Leveraging the web and the open web standards in order to create a web-based ecosystem is a one way to gain insights into the ontologies needed (by leveraging linked data and existing ontologies). This approach alone is not enough to support purpose built ecosystems and time-sensitive temporary entities - we aim to combine ontologies with agile structures and deal with variable speed of change increasing complexity of highly granular entities. ## References [1] Wikipedia; Definitions ## Related to [[How is MetaNotation connected to Semantic WEB]] [[Ecosystem building blocks and CIEL visualization]]