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CHARACTERIZATION, CATEGORIZATION AND CLASSIFICATION

Characterization, categorization and classification are three cognitive processes that enable us to systematically reference our sensory perceptions; to organize, store and retrieve artifacts of those experiences; and to reassemble those artifacts for the purposes of understanding (making sense of) our experience and communicating our intentions. Individuals who have difficulty performing any of these fundamental cognitive information management functions tend to experience a variety of difficulties in acquiring new information, recalling previously acquired information, associating related bits of information, understanding the usefulness or meaning of acquired information, and finding coherence in experience . Individuals impaired in any of these capacities also exhibit varying degrees of difficulty in communication.

Of these three related cognitive functions, characterization, being the definitive source of symbolic reference, serves as the progenitor of categorization and classification; in other words: if there are no reference symbols, there is no “content,” therefore, there can be no categories or classes.

The object “mommy” is initially perceived by the newborn as a complex amalgam of shape, scent, sound and texture without any symbolic reference medium . These aggregations of presymbolic sensory perceptions are registered in the amygdala by the emotions as patterns of experience that trigger the electro-chemical stimulus of either pleasure or pain receptors. At this presymbolic stage of cognitive development, “pleasure and pain” are merely alternative physiological auto-responses to sensory stimuli, and are not yet legitimate categories of “information” that have been created through cognition to organize experiential references for the purposes of storing, retrieving, associating or communicating the receiver’s experience.

THE EMERGENCE OF SYMBOLIC REFERENCE

In the animal kingdom, we humans appear to reign supreme in our capacity to contrive and employ symbols , and whether or not an individual is endowed with the hardware to visualize or vocalize symbols, there is convincing evidence < ref> Helen Keller </ref> that other sensory means such as touch can be recruited to the task of sophisticated and complex communication. Symbols, whether aural, visual, or tactile are the tools we use to describe our experience of the “outside” world beyond our bodies, and to create “imaginary” worlds (alternate realities) inside our minds. Symbols, whatever their nature, are the referential medium of the senses. They ‘package’ the elements of perception into recognizable ‘containers’ that allow the transference of experience, information and knowledge from one person’s mind to another’s . Symbols enable cognition, recognition and association by serving as the brain’s most controllable synaptic triggering device .

Language is the systemization of symbolism, with its organization and structure acting upon, and in the service of, its individual differentiated symbols; but language must also serve the demands of communicative efficiency . In this service, languages become inherently ambiguous as they achieve concision through various forms of conceptual and symbolic aggregation, such as metaphor, metonymy, and simile .

SEMANTIC OBJECT CHARACTERIZATION:

Semantic Object Characterization serves as the basis of experiential reference and thus, serves as the essence of our capacity to communicate. Object characterization is a prerequisite to categorization and is, thus, a predicate to classification; meaning that neither classification, categorization nor communication can take place without prior object characterization. Other fundamental linguistic mechanisms such as grammar and syntax are esential to the organization and efficient communication of experience, but they too are dependent upon a priori characterization of the experience. Ontologically, "objects" in the sense used here, refers to any tangible or intangible, dimensioned or dimensionless entity capable of description and, therefore, includes time, action, events and abstract concepts. As used here, "semantic characterization" refers to the use of natural language descriptors as the referential medium.

Unlike the structural conventions of grammar and syntax that have evolved as essential elements of language in the service of communication, no such conventions have evolved to order, or systematize, object characterization. The absence of such a linguistic convenvention at the elemental semantic level can be explained by the more compelling evolutionary need for communicative efficiency that lead to the organization of human experience into the broader, more aggregated efficiency of metaphorical concepts .

What was gained by conceptual metaphor's cognitive and linguistic efficiency was lost in its diminished communicative precision and specificity. This lack of communicative precision and specificity remained rather unimportant until the relatively recent emergence of industrialization, but the importance of communicative precision and specificity has risen dramatically with the increase in social complexity stemming from population growth, and the dramatic advances in science, precision materiale and information technologies.

OBJECT CLASSIFICATION

Man's prodigious cognitive abilities to categorize and classify the objects of his experience appear as if they may have evolved as methods of simplifying a world of increasingly complex social interactions, with the result being the emergence of experiential aggregation in the form of conceptual metaphor . Categorization and classification require the existence of meaningful differentiators whose granularity is a function of user-warranted demands of specificity; and as the need for specificity rises, the differentiating descriptors must become ever-more precise and granular, thus demanding an inversely proportional(ever-less)amount of conceptual aggregation.

In their primary roles as cognitive information management tools, categorization and classification serve not only as organizational frameworks, but as conceptual navigation aids that facilitate the efficient sharing of experience by quickly locating (re-cognizing) concepts by characteristic association, and discriminating among them by characteristic differentiation; thus, the efficiency and efficacy of this communication and cognitive information managment system is entirely dependant upon effective semantic object characterization.

THE LIMITATIONS OF CLASSIFICATION

In the absence of highly granular characterization, classification systems serve primarily as navigational tools. For example, they assist greatly in locating objects and concepts among a vast universe of possibilites, but even great classification systems offer little to the fundamental understaning of, or the comparative analysis of, the found object or concept. Knowing that medications can be found in a pharmacy will dramatically improve the efficiency of your search by avoiding a trip to the hardware store, but will do little for improving your understanding of drugs - for this, we require explicit characterization. Deriving understanding and meaning from our experince requires an explication of its component parts and features. It has generally been held in western thought that the measure of one's depth of understanding or meaning is directly proportional to the granuarity or specificity of explication - or, directly proportional to the degree to which one can be semantically differentiated one "object"(concept or experience)from another.

Whether housed in one's brain, on a piece of paper or in a machine, categorization and classification systems are essentially metadata systems for the management of underlying data and information, with the individual terms (category and class nomenclature) acting as semantic metadata tags. Categorization and classification systems are essentially navgational aids; whereas, object characterization systems actually contain the fundamental data and information essential to deriving meaning and understanding of the object or concept being characterized.

THE CATEGORIZATION OF CHARACTERISTICS (or ATTRIBUES)

At the deepest, most granular level of object characterization, the object attributes themselves are organized rationally into coherent groups, with the attribute "name" serving as a natural language metadata tag that is associated with ONE, and ONLY ONE attribute value. Every attribute NAME (metadata tag) must be a natural language term; however, the attribute VALUE may, or may not, be expressed in a natural langage. Examples of non-natural langusge attribute values are numerical, formulaeic, or coded alpha-numeric identifiers.

The navigational virtues of highly rational and coherent classification and categorization structures, such as enhanced finadability, apply just as well to the taxonomy of the object characterization structures. The benefits of systemization, such as extensibility; the benefits of normalization, such as error reduction; the beneits of standardization, such as efficient retrievability; and the benefits of user-warrants, such as high relevancy, all apply as well to achieving functional universality in the structure of an object-characterization schema.

ABSTRACT: THE IMPERATIVE OF A UNIVERSAL AND SYSTEMATIC OBJECT-CHARACTERIZATION SCHEMA

This article presents a conceptual framework for a universal system of semantic object-characterization, built upon a rational object-attribute classification schema. This article argues that the absence of such a UNIVERSAL OBJECT-CHARACTERIZATION schema is inflicting tremendous-yet-avoidable inefficiencies and waste upon a vast number of human endeavors; and argues further that the failure of commerce and industry to adopt object-classification schemas that are predicated upon universally applicable and systemmatic object-characterization will ultimately prevent the full integration and optimal application of advanced computing,information, and communications technologies. The central postulate presented here is that all OBJECT CLASSIFICATION SHOULD DERIVE FROM SYSTEMMATIC OBJECT CHARACTERIZATION based upon irreducable and unambiguous semantic descriptors of object attributes, and that these characterizations should conform to a normative, open-source, user-warranted, taxonometric structure.

Many fragmented industries, and disaggregated enterprises that involve large numbers of independant participants, suffer tremendous inefficiencies and waste stemming from faulty and ineffective communications, where messages fraught with semantic uncertainties are repeated, exchanged and built upon without a central source of validation or quality assurance; thus propagating uncertainty and error throughout the subject population, and perpetuating a cumulatively detrimental condition throughout the lifecycle of the project or enterprise . The author suggests that much of this semantic uncertainty is borne of metaphorical imprecision in the characterization of the "objects" that are the subjects of every industry, enterprise, initiative, or project.

This article presents a taxonometric and ontological object-oriented information management schema designed to mitigate the uncertainties inherent in metaphorical object characterization; and proposes further, that such a schema is the natural predicate to any system of object classification. Taxonometrically, the proposed schema is two-dimensional and is infinitely extensible along both axis; however, it is recommended that extension along the horizontal, "information domain" axis be limited to assist in human retention and findability . The information domains of the proposed schema are normative, functionally coherent, and fixed in sequence according to presumptive user-warrants. The subject headings of these information domains are fully normalized in natural language and read horizontally from left to right as column headings in a table. The "object attributes" comprise the schema's vertical dimension; the object attributes are infinitely extensible, comprised of funtionally coherent attribute groups and subgroups arranged sequentially within their respective information domains by user-warrant. The individual attribute dimensions are natural language terms that read from top to bottom within each group or subgroup, again sequenced within their cohort by user-warrant. The sequencing of the Groups and Subgroups are rational wherever possible, i.e.,listed in an order of natural occurance such as first-to-last, or newest-to-oldest, or top-to-bottom, or front-to-back, etc.. Where there is no obvious sequence of natural occurance, the Groups and Subgroups are listed by user-warrant (frequency of use). These qualities of the proposed schema are illustrated and described in this article.

Ontologically, this schema considers that an "object" may be either tangible or intangible, and may be either dimensioned or dimensionless; thus, conceptually classifying time periods, events and actions as veritable (characterizable) objects. Further, this schema is conceptually "experiential" (rather than exclusively "objectivistic" or "subjectivistic" - in that the schema characterizes objects according to both their "objective" (measurable), and "subjective" (contextual) attributes.

Linguistically, because the schema itself does not perform navigational or syntactic funtions, it seeks to use normalized, "basic-level" terms of characterization that are ideally "irreducible" (atomic in terms of their semantic granularity), non-metaphorical, and "intrinsic" to the object itself, and "inherent" within the user-warranted context of the subject object's characterization.

To achieve an increasingly robust normalized nomenclature and user-warranted attribute sequencing, the author proposes in this article a taxonomic, ontological, conceptual and linguistic framework from which to build a collaborative open-source characterization environment. This schema has been developed by the author over the past several years in a personal/business effort to improve efficiencies and reduce wastes throughout the development and operational lifecycles of building projects, by minimizing uncertainty in the characterization and communication of building specifications. Real world tests in 2006-2008 proved the author's theory that a considerable savings of time and money (25% in the test case)could be had by simply improving communications (richness of meaning and fidelity of transmission through better information management - without resorting to the existing and traditional savings paradigm of reducing cost by reducing project scope, quality and/or builder profits. The methodology and results of this test are included in an appendix to this article.

INTRODUCTION:

WHY THESE FUNDAMENTAL PROBLEMS PERSIST AND GROW:

The continued growth of specialization in industrialized societies has further disaggregated historically fragmented industries, and exacerbated their inability to recognize their systemic flaws and endemic shortcomings. The growth of social, academic and technological specialization has also led to highly independant, disaggregated and specialized resource pools from which new enterprises must be assembled, and around which new organizations must operate. It is the pervasive, insidious and evolutioary nature of social and cultural change that gives rise to, and disguises, those systemic conditions (and problems) that both individuals and societies grow to accept as the inviolate nature of civilization ; and it is for these reasons that fundamental systemic problems such as language flaws go largely unrecognized and unchallenged. These systemic problems become even more intractable in historically fragmented industries such as real estate development and construction, where the paradigm has also grown from a deeply parochial professional culture.

WHY SOLUTIONS TO-DATE HAVE BEEN SUPERFICIAL:

While the illusion of progress is being spread by the proliferation of new software tools, the reality is that most of these tools serve only very narrow and specific sectors of the industry and do little to advance the efficacy of the industry as a whole. No single sector of the real estate deveopment industry, for example, has yet risen to assume a leadership role in advancing new technologies or promoting innovative new protocols that address the full spectrum (all sectors)of the industry’s needs.

IDENTIFYING SEMANTIC AMBIGUITY AND NON-NORMATIVE SYNTAX IN OBJECT CHARACTERIZATION AS THE ROOT CAUSES OF ERROR AND THE DEGRADATION OF FIDELITY IN PROJECT COMMUNICATION:

Getting to the root of the systemic communication problems that plague fragmented organizations led the author to conclude that: uncertainty, borne of ineffective communication and fundamentally flawed information management, is the insidious problem that has persisted, untreated, at the core of the building industry’s chronic inefficiencies and waste; uncertainty is the most pervasive and treatable of the primary causes of the industry’s inefficiency and waste; and finally, that these uncertainties originate in the semantic ambiguities of object characterization and are exacerbated by non-normative characterization syntax. The author also suggests in this article that it is the harmful effects of uncertainty on human behavior and decision-making that lie untreated as the root causes of inefficiency and waste; and, that the fundamental nature of these critical problems (non-normative linguistics and semantics)explains in great measure the development and construction industry’s inability to effectively leverage advances in computing and communications technologies relative to other major industries.

These conclusions are based in the propositions that: 1) the built environment is comprised primarily of "objects and events" linked by transactions; 2) the industry continues to communicate critical object and event related information in the outmoded tradition of imprecise, highly-aggregated metaphorical and/or representational data; 3) as a result, much of the industry’s technical communication is still being conducted using archaic expository grammatical structures whose inefficiency and imprecision propagate uncertainty; and, 4) the non-normative syntax of these communications results from the absence of a structured characterization taxonomy.

WHY SOLUTIONS TO OUR CURRENT PARADIGMATIC PROBLEMS ARE INCREASINGLY URGENT:

As human population growth and increasing industrialization places ever-greater strain on the planet's ability to sustain human life, it beomes increasingly important that we make more efficient and less wasteful use of our finite resources in every aspect of human endeavor.

SOLVING PROBLEMS WITH THE PROPOSED SCHEMA:

Over the past several years, in an effort to solve many seemingly related industry-wide problems, the author has been crafting the conceptual framework of a new information and communications infrastructure built upon the foundations of a universally applicable, semanitcally unambiguous, object-characterization system. Aimed initially at meeting the needs of the architectural, interior design, and construction sectors of the home-building industry, the author built such an infrastructure by integrating a variety of application tools (information management software and protocols) based on the principles described in this article, and beta tested several key software components by applying them to the real-world needs of a turnkey home design portfolio being marketed by the author's design company.

This article focuses primarily on the taxonometric, ontological, semantic and organizational principles that underlie the conceptual framework being proposed for such an information and communications infrastructure; therefore, this article deals only peripherally with specific applications, and does so for the purposes of illustration only. Subsequent articles will focus on specific, task-oriented applications, because to better appreciate the merits and utility of such an integrated infrastructure, it is helpful to understand its conceptual framework through the integration of multiple applications into an information management process that improves the outcome of a meaningful and specific task (or set of tasks) such as the tasks ofigning and specifying buildings.

BENEFITS OF SYSTEMATIC, UNAMBIGUOUS OBJECT CHARACTERIZATION

A structured approach to the anatomy of objects that deals systematically with the description, identification, naming and classification of fundamental object attributes, could do for the advancement of information management what the taxonomy of living organisms did for the advancement of biology and the life sciences, and what the periodic table of elements did for the advancement of chemistry and the physical sciences.

With its usefulness reaching well beyond the ‘built’ environment’, a systematic object-characterization schema based upon a standardized universal object/attribute classification system could hold the key to a unified object information database with dramatic global economic and trade implications. Such a system could enable an infinitely expandable world-wide object information utility.

PRIMARY APPLICATIONS:

A systematic object-characterization schema based upon a universal attribute classification system represents a fundamental new concept in the organization and management of object data. With its universal taxonomy applicable to ALL inanimate objects, whether tangible or intangible, dimensionable or dimensionless, such a system would apply to and greatly benefit all industries and enterprises that deal with objects.

PRIMARY BENEFITS:

The primary contributions of a standardized universal object/attribute classification system to the field of information management are: 1) Such a system enables a much greater degree of information granularity which yields the potential for much higher descriptive specificity; 2) Such a system enables automated comparative analysis on the basis of intrinsic properties; 3) Such a system enables the creation of a single machine-readable universal object database. 4) A standardized classification system would allow all object and event data to reside in a single database, or unified data platform, which would enable the full spectrum of object and event data to be accessed by all data users across the full spectrum of design, manufacture, construction, sales and management disciplines, thus allowing all data users access to the information from the same source files, thereby enhancing communication and data reliability. 5) Standardized information sequencing improves the findability of relevant object and event data. This improves search and sort efficiency, enables more concise reporting, expedites comparative analysis and generally improves user comprehension. By enabling uniform data entry protocols, standardization promotes higher quality data. 6) Normalized object and event attribute nomenclature further enhances the precision, concision, clarity and comprehension of object and event related data, resulting in more effective communication and reduced uncertainty. 7) Systematic and structured information management improves process efficiency (productivity) by speeding the exchange of reliable, high-quality data and information, and reduces resource waste by enabling greater specificity and precision.

SYSTEMATIC OBJECT-ATTRIBUTE CLASSIFICATION SCHEMA

DEFINITIONS:

Information Domain: An Information Domain is a coherent set of object attributes that is fixed in a prescribed position within a prescribed sequence. Theoretically there is no limit to the number of Information Domains; however, IBISS recommends that the number be as small as possible so that their names and sequence can be easily committed to human memory. Currently there are Fourteen (14) object Information Domains in the IBISS system. These Information Domains are:

0. Metadata These are attributes describing the location and qualities of the data. 1. Identity* These attributes are assigned by object creators, handlers and users 2. Source* These attributes identify the creators and sources of the objects 3. Commercial Domain* These attributes describe the commercial aspects of the objects. 4. Material* These attributes characterize the tangible matter of the objects. 5. Methods* These attributes describe the methods of production and handling. 6. Dimensions* These are measurable attributes that do not change under differing environmental or use conditions. 7. Properties* These attributes are inherent in the object, and are derived by testing. They do not change under differing environmental or use conditions. 8. Energy* These are the input requirements and output attributes of power, energy and heat 9. Performance * (1) These are attributes that change according to environmental and/or conditions of use, or the characteristics of the object under prescribed test conditions. 10. Aesthetic* (2) These attributes characterize the sensual effects of the objects. 11. Destination** These attributes are assigned by the specifier to indicate the intended location, use, application or destination of the object. 12. Associative (Interface)** These attributes characterize the relationship of the object to other objects. 13. Derivative** These attributes are derived by conditions of use, such as: total quantities, total deflections under live load, etc. 14. Statements These are various natural language messages pertaining to the design, manufacture, handling and use of the object

• = Catalog Data

These are the data normally supplied by the creators of the objects. These “source” data attributes are inherent in the object at the completion of manufacture, may include manufacturer’s options, but are generally not changeable by the specifier. The catalogs may be searched by any one or combination of these attributes.

• =Specification Data

These attributes are assigned by the specifier/user in connection with a specifically intended use, application or destination.

(1) Loads and conditions of use are highlighted upon entry by the specifier. (2) Manufacturer’s standard options may be listed under each attribute. Upon specification only the selected option is recorded.

DATA GROUPS: Each Information Domain is comprised of one or more DATA GROUPS. Each Data Group is identified by a Capital Letter (A-Z) and represents a coherent subset of object attributes. Theoretically there is no limit to the number of Data Groups within a Domain; however, it is recommended that their number remain as small as possible to enhance human findability.

DATA SUBGROUPS: Each Data Group may be divided in one or more DATA SUBGROUPS. Each Data Subgroup is identified by a Lower Case Letter (a-z) and represents a coherent subset of object attributes. Theoretically there is no limit to the number of Data Subgroups within a Domain; however, it is recommended that their number remain as small as possible to enhance human findability.

DATA DIMENSIONS: Data Dimensions are unique, individual, and irreducible object attributes. Generally, Data Dimensions fall within a Data Group or Data Subgroup and are individually identified by a two-digit number. This number may be followed by a decimal point and two additional digits. There is no limit to the number of Data Dimensions and no practical reason to limit or minimize the number of dimensions for any object. Any object attribute or characteristic that is relevant to any person, use or purpose of the object throughout the object's lifecycle shall have one and only one coded taxonometric identifier.

UNITS OF MEASURE: A variety of Units of Measure are used or preferred by the various manufacturers, handlers and users of the various materials and objects being characterized by the system. For example, Measurement of Area may be expressed as Square Meters, Square Feet, Acres, etc. The system presents SI Units first, followed by Imperial Units, followed by industry specific units (e.g. nautical).

STANDARD LANGUAGE: English is the Standard Language of the system from which translations are derived. All Notations shall use the letters of the English alphabet.

STANDARD ABBREVIATIONS: All materials, chemicals, units of measure, shall be abbreviated using the Standard Abbreviations adopted by the International Organization for Standardization (ISO) 17:05, 25 March 2009 (UTC)Ibiss (talk) Ibiss (talk) 21:41, 25 March 2009 (UTC) Ibiss (talk) 05:24, 26 March 2009 (UTC) Ibiss (talk) 05:30, 26 March 2009 (UTC) Ibiss (talk) 06:46, 26 March 2009 (UTC) Ibiss (talk) 16:19, 27 March 2009 (UTC) Ibiss (talk) 16:49, 27 March 2009 (UTC) Ibiss (talk) 17:37, 27 March 2009 (UTC) Ibiss (talk) 20:19, 28 March 2009 (UTC) Ibiss (talk) 20:21, 28 March 2009 (UTC) Ibiss (talk) 20:23, 28 March 2009 (UTC)