Archive for October, 2022

The Demand for Empirical Knowledge Organization*   1 comment

Posted at 9:35 pm in ontology,theory

People ask me all the time what our institute “does.” When I say simply “research” I usually get a blank stare for a response. After all, what kind of “research” could there be in the organization of knowledge? And for that matter, what “is” the structure of knowledge—how could there be research into that?

Fortunately, the world press reports research about the order and structure of knowledge all the time. For example, in the October 25th (2019) Economist there was a report about how a meta-analysis of museum research demonstrated there were more male specimens than female in museum collections used for research, and therefore, that the results of the reported research were not (as we might have it) ontologically sound. Meanwhile, on television 60 Minutes reported on November 24th 2019 that specific concepts are recognizable by electrical patterns in the brains of humans who embrace them. In other words, a biometric sign that specific meanings actually do, despite the influence of phenomenological philosophies and epistemological stances, cause commonality of understanding across the human species. Both of these studies are meta-analyses of prior empirical studies—from simple descriptive research to experimentation—thus both contribute to the growth of the theory of the order of knowledge, and in the latter case its structure as well.

In Elements of Knowledge Organization (2014, 7) I wrote: “At the most basic level, theory is a frequently‐tested (and thereby affirmed) statement of the interacting requirements of a phenomenon. In empirical research, theory is both the accumulated wisdom of the paradigm from which hypotheses are cast and the constant reaccumulation that occurs as each hypothesis is tested” and “theory exists in domains where a large quantity of research has been very productive at generating workable explanations and also at identifying inadequate or erroneous statements.” The growth of theory requires both large numbers of replicable research studies, and meta-analyses of those studies that demonstrate both results and gaps. In knowledge organization, it is critical that studies of ontological spaces be conducted, replicated and analyzed across studies and across time. In post-modern knowledge organization, which is domain-centric, this means analysis of specific concepts within specific domain ontologies. But we also have in meta-analysis the opportunity to compare ontological structures, which can themselves be classified, compared and tested, to understand how domains are or are not comparable. These are the goals of our institute. We work with the theoretical underpinnings of working knowledge organization applications. But we do so at a meta-level, seeking to understand both the ontological priorities of a domain and the ontical structures of its conceptual knowledge base.

My last two editorials in Knowledge Organizationwere pleas for empirical research. In (2017) I pleaded with the community to take up replication and theory building. On ISKO conference program committees (both regional and international) referees frequently criticize research with the phrase “we have seen this before.” But, of course, replication is critical to create reliability across results of different studies. Until we have replications of the same data from the same methodologies and even the same data from diverse methodologies, until then we cannot have faith in the reliability of our theoretical constructs. Empirical science relies on theoretical statements that indicate the probability of occurrence more than 99% of the time. Although systems for the organization of knowledge are as old as civilization itself, the empirical study of KO stems only from the past half century. In 2015 (31-33) I analyzed the existing domain analytical studies; at that time only a few very broad domains (archives, image searching, LGBT, physics and social media) had been studied 3 times, and only music (an immense domain) had been studied 4 times, and KO itself had been studied 22 times. It is critical to deepen the understanding of domain ontologies if we are to grow theory of both knowledge organization and knowledge structure.

In my most recent editorial (2020) I tried to point to increasingly problematic behavior of scholars in KO with little or only casual regard to referencing. References often are crafted rather than extracted from source publications. Authors often cite works that have not been read. I consider this is a form of intellectual dishonesty that pushes ethical boundaries. The importance of replication extends to the evidentiary component of every published study—if the sources cannot be consulted in replication how can we have confidence in published results?

The role of IKOS then is to meet the demand for empirical KO by pursuing in real time the work of empirical research in domain ontologies and ontical structures. To that end we first took up a meta-analysis of studies of KO. The results of that study are now compiled in our first technical report (IKOS 2020). Two products of that study are visible on our website in the form of the corpus bibliography ( and a dynamic Formal Taxonomy of Knowledge Organization (

In late 2019 we tackled the phenomena of music for a phenomenon-based classification. The result of that work, which is still underway, will include new facets for medium of performance, and form and genre. An exciting development will be a facet for audiography, derived from meta-analysis of empirical studies of music information retrieval (Szostak and Smiraglia 2020). This facet will include details of capture, production and dissemination, and user purpose and emotion.

In 2020 it is our intention to tackle homosexual nomenclatures. We also have begun to work on the domain of nursing information behavior, basing our initial analysis on the 2005 dissertation by Edmund Pajarillo. A teaser visualization of simple phrases appears in Figure 1.

Figure 1. 3-dimensional Visualization of Core Phrases in Nursing Information Behavior.

We can see here the potential outline of facets for a taxonomy—geographic health, information leads, nursing process, information behavior, information resources. We will work to grow that taxonomy as we are able.

In all of this research we are doing what we can to contribute—to give back—through research by meeting the demand for empirical knowledge organization.


IKOS (Institute for Knowledge Organization and Structure, Inc.). 2020. Technical Report: Meta-Analysis of Knowledge Organization as a Domain. IKOS Technical Reports Series no. 1. Lake Oswego, OR: IKOS.

Pajarillo, Edmund J.Y. 2005. “Contextual Perspectives of Information for Home Care Nurses: Towards a Framework of Nursing Information Behavior (NIB).” PhD diss., Long Island University.

 “Scientists are using MRI scans to reveal the physical makeup of our thoughts and feelings.” 60 Minutes November 24, 2019.

“Sexual Selection: Collections of Animals Favour Male over Female Specimens.” Economist October 25th (2019): 74.

Smiraglia, Richard P. 2014. The Elements of Knowledge Organization. Cham: Springer.

Smiraglia, Richard P. 2015. Domain Analysis for Knowledge Organization: Tools for Ontology Extraction. Chandos InformationProfessional Series. Oxford: Elsevier/Chandos.

Smiraglia, Richard P. 2017. “Replication and Accumulation in Knowledge Organization—An Editorial.” Knowledge Organization 44: 315-17. 

Smiraglia, Richard P. 2020. “Referencing as Evidentiary: An Editorial.” Knowledge Organization 47: 4-12. doi:10.5771/0943-7444-2020-1-4

Szostak, Rick and Richard P. Smiraglia. 2020. “Identifying and Classifying the Phenomena of Music.” In Linking Knowledge: Linked Open Data for Knowledge Organization and Visualization, ed. Richard P. Smiraglia and Andrea Scharnhorst. Baden-Baden: Ergon Verlag, 2021, 143-48. Also in Knowledge Organization at the Interface: Proceedings of the Sixteenth International ISKO Conference, 2020, Aalborg, Denmark, ed. Marianne Lykke, Taja Svarre, Mette Skov and Daniel MartÍnez-Ávila. Advances in Knowledge Organization 17. Baden-Baden: Ergon Verlag, 421-27.

*Published in print as: Smiraglia, Richard P. 2020. “The Demand for Empirical Knowledge Organization.” IKOS Bulletin 2, no.1 : 8-10.

Written by admin on October 17th, 2022

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Iconic Knowledge, Iconic KO*   1 comment

“Iconic .…” According to the Oxford English Dictionary Online the word means “Of or pertaining to an icon, image, figure, or representation; of the nature of a portrait.” The first usage reported there was in 1656. OED also has variant definitions for “use in worship” and Semiotics. Ah, there we are: … “pertaining to or resembling an icon” (first usage reported in 1939. And finally: “designating a person or thing regarded as representative of a culture or movement; important or influential in a particular (cultural) context.” WordNet has: “relating to or having the characteristics of an icon.”

We all know, I hope, what an icon is. I have many that I have collected on my travels to Crete. In Orthodox spirituality, these icons are pathways to prayer. It is a bit difficult to explain, but the idea is that in praying with an icon (by focusing on the figures in meditative prayer) the saint in the icon is able to enter your consciousness and become a vector for your prayer.

The word has become ubiquitous in the news these days, to mean “emblematic.” I have to laugh, because once not so long ago when I used the word “iconic” in a manuscript I was told it would not be understood by LIS readers (people, mostly, with PhDs). At the same time I was writing regularly for the Philadelphia Gay News with instructions to write at a fourth grade reading level, and of course, the word “iconic” was part of that vocabulary. Well, we hear the word constantly these days. Unfortunately, that means it has lost a lot of its meaning as it has become colloquially “iconic.” It should mean “stands for a gate to spirituality.” Too often instead it just means “looks familiar.”

In KO what does the word mean? In KO it preserves aspects of its original connotation: something precious that is a gateway to better understanding, particularly with regard to visualization of culturally representative entities.

How do we at IKOS turn our own work into iconic work? We are rooted in empirical methods. Our work is eminently replicable. We report our references impeccably. For us, references are the evidence that what we describe is truly representative of a concept. Dahlberg implied and other since have written that the concept was the “atomic” element of knowledge organization (Dahlberg 2006; Smiraglia and Van den Heuvel 2013). This means that concepts paint pictures in people’s brains, those pictures are shared culturally, and from the very tiniest impression (what Peirce (1991, 181) might have called a “representamen”), the shared conception grows. There is “cultural synergy” (Smiraglia 2014)—the concept enters a knowledge organization system (KOS) that is itself a cultural disseminator and thus the concept becomes part of the cultural consciousness. This is then the iconic status of a concept.

At IKOS we are dedicated to sorting out the particularities of concepts, including the concept of “iconic.” We invite you to help us reclaim this critical term from public incoherence.


Dahlberg, Ingetraut. 2006. “Knowledge Organization: A New Science?” Knowledge Organization 33: 11-19.

Oxford English Dictionary Online, s.v. “Iconic,” accessed 12 October 2019.

Peirce, Charles Sanders. 1991. Peirce on Signs: Writings on Semiotic, ed. by James Hoopes. Bloomington: Indiana Univ. Pr.

Smiraglia, Richard P. and Charles van den Heuvel. 2013. “Classifications and Concepts: Towards an Elementary Theory of Knowledge Interaction.” Journal of Documentation 69: 360-83.

WordNet. Search 3.1, s.v. “Iconic.”accessed 12 October 2019.

*Published in print as: Smiraglia, Richard P. 2019. “Iconic Knowledge, Iconic KO.” IKOS Bulletin 1, no.1 : 6-7.

Written by admin on October 10th, 2022

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The Value of Knowledge Organization Systems*   no comments

We are scientists of knowledge and of its order, we have identified the atomic elements of our science (“concepts”) and we have empirically described their behavior, which eerily (or perhaps excitingly) mimics that of elements of quantum theory. That is, we have defined the domain of knowledge, identified its entities (concepts, works, etc.) and the forces that compel them (syntax, semantics, etc.). Ideation is the matter of knowledge and expression compels the conceptual particles that are made up of signs and can be grouped into taxons. Spacetime is represented by the notion of instantiation in which knowledge as concepts move from ideation to expression along a continuum. Spin is the representation of what we know as semiosis, the motion of signification. Strings are spatial objects analogous to instantiation networks or canons. I admit I have presented here a tiny bit of a partial explanation to make my point; for details see please van den Heuvel and Smiraglia 2010, 2013, 2021; Smiraglia and van den Heuvel 2013).

But what is the value of knowledge organization? What value is ascribed to the massive systems for the ordering of knowledge that are the applied products of our science? The question is not new. We can look to classificationists of the late 19th and early 20th centuries for notions of the “economies” of a KOS, usually expressed as the simple elegance with which a complex concept can be expressed (Smiraglia and Szostak 2018).

We can look to the appropriate social outcry at the demise of card catalogs (Baker 1994). What brilliant feats of engineering were the catalogs of major libraries built over a century by armies of catalogers, typists, card printers, card filers, filing revisers, etc., etc. What was the cost of that infrastructure?

(University of Illinois at Urbana-Champaign library catalog S-Z along Wright Street dividing Champaign from Urbana.)

What is the value of a knowledge organization system (KOS)? Is it cost divided by benefit? How do we measure benefit? How do we know the true costs? What is the cost of the UDC? What is the cost of the DDC? What about systems like NANDA-I nursing vocabulary (2018) or the NAICS: North American Industrial Classification ( )

(Elichirigoity and Malone 2005) or the United Nations Standard Products and Services Code (UNSPC) classification ( ). What was the total cost of conversion of card catalogs to digital form? What is the cost of conversion of KOSs to linked data (see for example Szostak et al. 2020).

There is, of course, no direct answer to these questions.

A few years ago Greenberg (see for example 2015; 2017) began a series of musings about metadata capital, consulting with economists about the idea that capital was invested in the construction of metadata systems and therefore, metadata should be considered as an economic asset.

It seems that there must be an equation of sorts to the extent that the cost of a KOS can be determined such that the cost should be in ratio to the benefit of the system. IKOS exists for the purpose of identifying gaps in the structure of the science of KO. Each clinic must, from now on, pursue questions of value.


Baker, Nichols. 1994. “Discards.” The New Yorker :70, no. 764-86.

Elichirigoity, Fernando and Cheryl Knott Malone. 2005. “Measuring the New Economy: Industrial Classification and Open Source Software Production.” Knowledge Organization 32: 117-27.

Greenberg, Jane. 2015. “Metadata Capital: Raising Awareness, Exploring a New Concept.” Bulletin of the Association for Information Science and Technology 40, no. 4: 30-33.

GreenbergJane. 2017. “Big Metadata, Smart Metadata, and Metadata Capital: Toward Greater Synergy Between Data Science and Metadata” Journal of Data and Information Science 2, no.3: 19-36.

NANDA International. 2018. Nursing Diagnoses: Definitions and Classification 2018-2020, ed. T. Heather Herdman and Shigemi Kamitsuru. 11th ed. New York: Thieme.

Smiraglia, Richard P. and Rick Szostak. 2018. “Converting UDC to BCC: Comparative Approaches to Interdisciplinarity.” In Challenges and Opportunities for Knowledge Organization in the Digital Age: Proceedings of the Fifteenth International ISKO Conference, 9-11 July 2018, Porto, Portugal, ed. Fernanda Ribeira and Maria Elisa Cerveira. Advances in Knowledge Organization 16. Baden-Baden: Ergon, 530-38.

Szostak, Rick, Richard P. Smiraglia, Andrea Scharnhorst, Aida Slavic, Daniel MartÍnez-Ávila and Tobias Renwick. 2021. “Classifications as Linked Open Data: Challenges and Opportunities,”. In Linking Knowledge: Linked Open Data for Knowledge Organization and Visualization, ed. Richard P. Smiraglia and Andrea Scharnhorst. Baden-Baden: Ergon Verlag, 2021, 24-34

van den Heuvel, Charles and Richard P. Smiraglia. 2010. “Concepts as Particles: Metaphors for the Universe of Knowledge.” In Paradigms and Conceptual Systems in Knowledge Organization: Proceedings of the Eleventh International ISKO Conference, 23-26 February 2010 Rome Italy, ed. Claudio Gnoli and Fulvio Mazzocchi. Würzburg: Ergon-Verlag, 50-56.

van den Heuvel, Charles and Richard P. Smiraglia. 2013. “Visualizing Knowledge Interaction in the Multiverse of Knowledge.” In Classification and Visualization: Interfaces to Knowledge, Proceedings of the International UDC Seminar, 24-25 October 2013, The Hague, The Netherlands, ed. Aida Slavic, Almila Akdag Slah and Sylvie Davies. Würzburg: Ergon Verlag, 59‐72.

van den Heuvel, Charles and Richard P. Smiraglia. 2021. “Knowledge Spaces: Visualizing and Interacting with Dimensionality.” In Linking Knowledge: Linked Open Data for Knowledge Organization and Visualization, ed. Richard P. Smiraglia and Andrea Scharnhorst. Baden-Baden: Ergon Verlag, 200-18.

*Published in print as: Smiraglia, Richard P. 2022. “The Value of Knowledge Organization Systems.” IKOS Bulletin 4, no.1 : 23-26.

Written by admin on October 3rd, 2022

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