wordsmithing

docs/geospatial-tracking.md

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 <p>CCO has been used to integrate heterogenous data concerning entities that move through space over time. By introducing entities such as geospatial boundary, geospatial line, and geospatial polygon, CCO’s geospatial design patterns resemble those of <a href="https://duckduckgo.com/?q=geosparql&ia=web">GeoSPARQL</a> which maintains a vocabulary of points and polygons from which users may construct query patterns concerning spatial location. However, GeoSPARQL does not provide query extensions or native support for interactions between both space and time, instead directing users to leverage <a href="https://www.w3.org/TR/owl-time/">OWL TIME</a> to model the latter. In contrast, CCO integrates spatial, temporal, and spatiotemporal aspects of tracking.</p>
 
-<p>Suppose there is a need to represent the path taken by a ground vehicle over some geospatial region. Figure 1 illustrates how such a use case would be modeled using CCO. The class material artifact - a material entity designed by some agent to realize some function - is the parent of vehicle, instances of which convey material entities from one location to another. Subclasses of vehicle are divided largely along the lines of aircraft, ground vehicle, spacecraft, and watercraft, all of which are designed to realize some conveyance function across some environment type. While any instance of truck is a ground vehicle, the latter class is further divided into rail transport vehicle – conveyance by railway - and ground motor vehicle – conveyance by motive power by an engine absent rails – where we find truck.</p>
-<div class="center-text"><img src="https://raw.githubusercontent.com/CommonCoreOntology/cco-webpage/main/docs/assets/logos/geospatial.png" alt="Common Core Ontologies" style="width:50%;"></div>
+<p>Suppose there is a need to represent the path taken by a ground vehicle over some geospatial region. The first figure below illustrates how such a use case would be modeled using CCO. The class material artifact - a material entity designed by some agent to realize some function - is the parent of vehicle, instances of which convey material entities from one location to another. Subclasses of vehicle are divided largely along the lines of aircraft, ground vehicle, spacecraft, and watercraft, all of which are designed to realize some conveyance function across some environment type. While any instance of truck is a ground vehicle, the latter class is further divided into rail transport vehicle – conveyance by railway - and ground motor vehicle – conveyance by motive power by an engine absent rails – where we find truck.</p>
+<div class="center-text"><img src="https://raw.githubusercontent.com/CommonCoreOntology/cco-webpage/main/docs/assets/logos/geospatial.png" alt="Common Core Ontologies" style="width:75%;"></div>
 <p>Tracing the path of an instance of truck involves identifying an act of vehicle use in which that truck participates. The act of vehicle use in turn has process part some location changes which occur at instances of vehicle track point. Generally, the relation occurs at holds between a process and a site, where a site is a three-dimensional immaterial entity whose boundaries coincide with some material entity, e.g. a hole in a straw, the trunk of a car. To say then that a process part of the act of vehicle use occurs at some vehicle track point is to imply the latter is a site. Each instance of vehicle track point is associated with latitude and longitude text values, and each is a part of distinct instances of geospatial region, which is a site at or near the surface of the Earth. Each geospatial region has a different location, such as Buffalo NY, or the New York State Thruway Exit 33 Toll Plaza, or Rome NY.</p>
-
-<p>The temporal aspect of this scenario is illustrated in Figure 2. Suppose the act of vehicle use occurs at the Baghdad city of al-Kadhimya over the course of several months. One such occurrence happened during the month of May 2004. Any act of vehicle use will happen over a temporal interval, which is a continuous temporal region of one-dimension exhibiting no gaps, such as May 17th at 1:38PM EDT. This time of day is an interval during May 2004, which in this scenario is an interval during a multi- month temporal interval, perhaps consisting of June, July, and August as well. Note that, despite the label choice, multi-month temporal interval may, unlike the BFO class temporal interval, exhibit discontinuities and temporal gaps. The class exists to track repeated occurrences of a process across months. For more fine-grained representations, CCO additionally contains similarly contains multi-day temporal interval, multi- second temporal interval and so on.</p>
-<div class="center-text"><img src="https://raw.githubusercontent.com/CommonCoreOntology/cco-webpage/main/docs/assets/logos/tracking.png" alt="Common Core Ontologies" style="width:50%;"></div>
+<p>The temporal aspect of this scenario is illustrated in the next figure below. Suppose the act of vehicle use occurs at the Baghdad city of al-Kadhimya over the course of several months. One such occurrence happened during the month of May 2004. Any act of vehicle use will happen over a temporal interval, which is a continuous temporal region of one-dimension exhibiting no gaps, such as May 17th at 1:38PM EDT. This time of day is an interval during May 2004, which in this scenario is an interval during a multi- month temporal interval, perhaps consisting of June, July, and August as well. Note that, despite the label choice, multi-month temporal interval may, unlike the BFO class temporal interval, exhibit discontinuities and temporal gaps. The class exists to track repeated occurrences of a process across months. For more fine-grained representations, CCO additionally contains similarly contains multi-day temporal interval, multi- second temporal interval and so on.</p>
+<div class="center-text"><img src="https://raw.githubusercontent.com/CommonCoreOntology/cco-webpage/main/docs/assets/logos/tracking.png" alt="Common Core Ontologies" style="width:75%;"></div>
 <p>These resources allow for the representation of partial descriptions of processes that refer to the same event using different granularities of time. For example, the statements “The truck is in Baghdad at 8:42PM on March 17th, 2004” and “A truck was in Baghdad on the evening of March 17th, 2004” may refer to the same event, and if so, would be linked using interval during relations.</p>

docs/index.md

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 <body>
     <h1>Common Core Ontoloies (CCO)</h1>
     <p>The <a href="https://github.com/CommonCoreOntology" target="_blank">Common Core Ontologies (CCO)</a> is suite of eleven ontologies which, collectively, comprise a <a href="https://arxiv.org/pdf/2404.17757" target="_blank">mid-level ontology</a>. CCO - initiated by CUBRC, Inc. in 2010 under an IARPA Knowledge Discovery and Dissemination grant - is widely-used in defense and intelligence sectors to support data standardization, interoperability, reproducibility, and automated reasoning across numerous domains. Accordingly, CCO development and application was, for many years, conducted without much transparency. As of 2017, however, CCO has been available under a BSD-3 license with a public GitHub repository open to collaboration. Making CCO publicly available has led to significant increase of interest in CCO development. For example, in 2022 the Institute of Electrical and Electronics Engineers (IEEE) <a href="https://standards.ieee.org/ieee/3195/11025/" target="_blank">P3195 Standard for Requirements for a Mid-Level Ontology and Extensions working group</a> initiated a review of CCO to become the first mid-level ontology standard. More recently, in 2024 CCO was endorsed as a “baseline standard” for all <a href="https://www.buffalo.edu/ubnow/stories/2024/03/smith-ontology-standard.html" target="_blank">formal ontology development across the Department of Defense and Intelligence Community</a>. 
-     <div class="center-text"><img src="https://raw.githubusercontent.com/CommonCoreOntology/cco-webpage/main/docs/assets/logos/BFO-CCO.png" alt="Common Core Ontologies" style="width:50%;"></div>
+     <div class="center-text"><img src="https://raw.githubusercontent.com/CommonCoreOntology/cco-webpage/main/docs/assets/logos/BFO-CCO.png" alt="Common Core Ontologies" style="width:75%;"></div>
 <h1>Common Core Ontologies</h1>
     <table>
         <thead>

docs/information.md

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 <p>The Information Entity Ontology distinguishes content of information both from the information bearing entities which may carry that content and from the patterns exhibited by those information bearing entities. A computer monitor screen, for example, bears qualities such as shape and color that are said to concretize information content entities, i.e. generically dependent continuants that are about something. These distinctions allow for flexible representations of various relationships arising among information bearing entities, patterns, and information content entities. Any of the following patterns ‘π’, ‘pi’, ‘3.14...’, or ‘3.14159265358979323...’ on your monitor might concretize the same information content entity. Similarly, such patterns in a textbook would concretize the same information content entity.</p>
-
 <p>Importantly, in making this trifold distinction, CCO denies that information transmission, provenance, and evaluation can be adequately represented without reference to information carriers. Carriers are, for example, crucial when modeling the provenance and pedigree of data across multi-modal sensors [24]. That said, users are not required to track provenance; CCO includes an annotation property is tokenized by to link literal values directly to instances of information content entity without having to represent relevant information content entities.</p>
-
 <p>Designative information content entities are used to uniquely denote entities, while directive information content entities consist of either propositions or images used to prescribe behaviors, actions, designs, etc. The class descriptive information content entity consists of propositions used to describe some entity and is the parent to the extensive collection of measurement and measurement unit CCO classes. CCO distinguishes what is being measured, information about what is measured, units encoding measurements, and the findings regarding measurements. For example, measuring John’s height in inches involves John, a length quality that inheres in John, the inch unit of measure, and the value associated with John’s height, e.g. “70”</p>
-
-<p>To illustrate features of CCO’s information design pattern, consider that automobiles are often designed by agents or organizations according to some blueprint or modeling pattern. The Agent Ontology contains classes for agents, organizations, and roles borne by either. In CCO, agents are in every case those material entities capable of performing planned acts, i.e. acts directed by some directive information content entity. Moreover, by leveraging a sub-relation of participates in, namely agent in, CCO distinguishes between agents making causally relevant contributions to some process as opposed to passive contributions. For example, engineers working for Honda at some point created a blueprint for the Honda Civic, and so provided causally relevant contributions to the creation of this blueprint. Expanding on this example, CCO introduces the class artifact model, a directive information content entity that prescribes a common set of functions and qualities to inhere in a set of artifact instances. Instances of artifact model are, moreover, designated by specific artifact model names, such as “2018 Tesla Model 3-EU var2” which may similarly be represented using CCO resources</p><div class="center-text"><img src="https://raw.githubusercontent.com/CommonCoreOntology/cco-webpage/main/docs/assets/logos/prescription.png" alt="Common Core Ontologies" style="width:50%;"></div>
+<p>To illustrate features of CCO’s information design pattern, consider that automobiles are often designed by agents or organizations according to some blueprint or modeling pattern. The Agent Ontology contains classes for agents, organizations, and roles borne by either. In CCO, agents are in every case those material entities capable of performing planned acts, i.e. acts directed by some directive information content entity. Moreover, by leveraging a sub-relation of participates in, namely agent in, CCO distinguishes between agents making causally relevant contributions to some process as opposed to passive contributions. For example, engineers working for Honda at some point created a blueprint for the Honda Civic, and so provided causally relevant contributions to the creation of this blueprint. Expanding on this example, CCO introduces the class artifact model, a directive information content entity that prescribes a common set of functions and qualities to inhere in a set of artifact instances. Instances of artifact model are, moreover, designated by specific artifact model names, such as “2018 Tesla Model 3-EU var2” which may similarly be represented using CCO resources</p><div class="center-text"><img src="https://raw.githubusercontent.com/CommonCoreOntology/cco-webpage/main/docs/assets/logos/prescription.png" alt="Common Core Ontologies" style="width:75%;"></div>
 <p>Given an artifact model prescribing the production features for a type of automobile, manufacturers also engage in planned acts the goal of which is to satisfy the artifact model prescriptions. Manufacturers may, for example, produce an automobile that is meant to bear a certain weight or have a certain transportation range function. These dependent entities will then inhere in the automobile produced and may be measured by some information content entity. As depicted in Figure 3, each ratio measurement information content entity corresponds to its own information bearing entity, which we may assume without loss of generality that in this case is part of some database or table. With respect to the weight of the automobile, the relevant database part has a literal value “1250” and uses measurement unit kilogram measurement unit.</p>
-
 <p>Artifact models are rarely, if ever, faithfully produced. CCO resources allow for representations of the goals of an artifact model, the extent to which attempts to produce that model were successful, and manufacturer plans in pursuit of such production. When representing data reflecting failures of plans, missed opportunities, or perhaps even unobtainable goals, such nuanced representations are invaluable.</p>

docs/stasis.md

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 <p>CCO provides sophisticated resources for representing time without delving into the more sophisticated temporal representations of previous versions of BFO. Nevertheless, there is a need to represent constancy over time, such as Mary’s temperature being normal over a series of measurements, the average altitude of flight, or how long a suspect was detained. Consider repeated measurements of Mary’s temperature over the course of a day. One strategy for representing the phenomenon in question is to assert that Mary is the bearer of an instance of temperature that carries some text value within a normal range, and so warrants classification as a ‘normal measurement’. Such a strategy does not, however, provide the ability to represent a single measurement datum in a record indicating that, say, “On Friday 3/15/24, Mary’s temperature was normal.”</p>
-
 <p>The strategy adopted by CCO is to introduce the class stasis, a process in which an aspect of one or more independent continuants endures in an unchanging condition. Intuitively, the constancy of Mary’s ‘normal’ temperature is represented by connecting measurements of Mary’s temperature to a proper process part of bodily processes she participates in over some interval, during which qualities that impact Mary’s temperature are measured as within some range of normalcy. In this case, the relevant proper process part count as a stasis. Put another way, we can think of Mary’s ‘normal’ temperature as the subject of some interval measurement information content entity - since such measurements typically have no absolute zero. Mary’s temperature stasis has participant the temperature that is subject of that interval measurement information content entity. Mary’s ‘normal’ temperature is then captured by asserting Mary’s temperature stasis occurs on some temporal interval designated by a date identifier, a CCO class used to denote specific days, which in this case will have value “3/15/24”.</p>
-<div class="center-text"><img src="https://raw.githubusercontent.com/CommonCoreOntology/cco-webpage/main/docs/assets/logos/stasis.png" alt="Common Core Ontologies" style="width:50%;"></div>
-<p>Related, CCO provides resources for the representation of the gain or loss of dependent entities because of some process. The extensive class structure of CCO’s Quality Ontology – initiated by adapting classes from the <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6169674/">Phenotypic Trait Ontology (PATO)</a> - provides a storehouse of qualities that may be involved in such processes. The CCO class change represents a process in which some independent continuant endures and 1) one or more of the dependent entities it bears increase or decrease in intensity, 2) the entity begins to bear some dependent entity or 3) the entity ceases to bear some dependent entity. Following the BFO hierarchy of dependent entities, subclasses cover decrease, gain of, increase of, and loss of dependent continuants, each of which contains subclasses for specifically dependent continuants and generically dependent continuants. Regarding the former, if a portion of H2O is frozen, it loses its liquidity disposition, represented as this portion of H2O participating in a loss of disposition. Regarding the latter, receipt on your local network of a PDF file sent via email reflects a gain of generically dependent continuant.</p>
-
-<p></p>
+<div class="center-text"><img src="https://raw.githubusercontent.com/CommonCoreOntology/cco-webpage/main/docs/assets/logos/stasis.png" alt="Common Core Ontologies" style="width:75%;"></div>
+<p>Related, CCO provides resources for the representation of the gain or loss of dependent entities because of some process. The extensive class structure of CCO’s Quality Ontology – initiated by adapting classes from the <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6169674/">Phenotypic Trait Ontology (PATO)</a> - provides a storehouse of qualities that may be involved in such processes. The CCO class change represents a process in which some independent continuant endures and (1) one or more of the dependent entities it bears increase or decrease in intensity, (2) the entity begins to bear some dependent entity or (3) the entity ceases to bear some dependent entity. Following the BFO hierarchy of dependent entities, subclasses cover decrease, gain of, increase of, and loss of dependent continuants, each of which contains subclasses for specifically dependent continuants and generically dependent continuants. Regarding the former, if a portion of H2O is frozen, it loses its liquidity disposition, represented as this portion of H2O participating in a loss of disposition. Regarding the latter, receipt on your local network of a PDF file sent via email reflects a gain of generically dependent continuant.</p>