lazykoblog   occasional musings about knowledge organization

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 25^th (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 24^th 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 (https://knoworg.org/meta-analysis-of-the-knowledge-organization-domain-corpus-bibliography/) and a dynamic Formal Taxonomy of Knowledge Organization (https://knoworg.org/a-formal-taxonomy-of-knowledge-organization-version-1-0/).

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.

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.

References

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. https://www.cbsnews.com/news/functional-magnetic-resonance-imaging-computer-analysis-read-thoughts-60-minutes-2019-11-24/

“Sexual Selection: Collections of Animals Favour Male over Female Specimens.” Economist October 25^th (2019): 74. https://www.economist.com/science-and-technology/2019/10/26/why-museums-animal-collections-favour-males

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.

I am gratified to be among those receiving research grants from the 2016 fourth round of the Digging Into Data challenge, sponsored by the Trans-Atlantic Platform for the Social Sciences and the Humanities (https://www.transatlanticplatform.com/). Our project is called “Digging Into the Knowledge Graph”; principal investigators include, besides me, Andrea Scharnhorst of the Royal Netherlands Academy of the Arts and Sciences and Rick Szostak of the University of Alberta. A brief abstract of our project is available here: https://diggingintodata.org/awards/2016/project/digging-knowledge-graph

I am sure to be reporting here often about the specifics of the project so I won’t take space to do that now. What I want to say, for those who read this blog, is that this fairly compact project represents a major step up in research profile for the knowledge organization community. We are among a group of fourteen international projects being funded to explore making more effective use of “big” data. And we are proposing to use knowledge organization systems–both existing systems and systems we plan to develop–to do so. From our proposal, just as a teaser, is this exciting line: “This project aims for nothing less than to provide means of support for [the] self-organising process of knowledge creation.”

Pretty exciting stuff, if I do say so myself.

I famously wring my metaphorical hands about the number of authors who submit manuscripts to Knowledge Organization reporting research that is topically relevant, but showing absolutely no inculcation in the theories or values of the science of KO. Emotions range from demoralized to furious on these occasions. Fortunately, rational academic policies dictate manuscript acceptance, and in almost all cases we return these errant papers to the authors with instructions to go do their homework. Some of them do, happily.

I am in the midst of a domain analysis of the 75 papers presented at the recent ISKO International Conference in Krakow (http://www.isko2014.confer.uj.edu.pl/en_GB/-start). The complete results of that analysis will appear in an editorial in a future issue of KO. But the interesting thing I am seeing this time is that there is, indeed, a core of knowledge organization. Seventy-five papers, 1200-some citations, from 20 countries, citing over 400 journal articles, 300 books and 200 anthologies. And yet, most of the citations are to a tightly-knit intellectually coherent core of KO. Most journal citations by far (44%) are to Knowledge Organization, the majority of conference papers cited are in ISKO international conferences or regional chapter conferences, and the most-cited monographs are by Hjørland and Ranganathan.

It is good news, that there is such a strong and resilient and theoretically useful core of knowledge organization. The challenge, it seems, is to require those interloping into our topical areas to encounter our theoretical base.

It is appalling the number of manuscripts we receive for review for Knowledge Organization, that are about things like ontologies and taxonomies and domain analyses, and that cite absolutely no literature from the domain of knowledge organization.

Usually my first intuitive reaction is to think the authors simply were negligent in submitting their siloed papers to us without checking that our journal is published by a scientific society that might expect its own science to be used. Sometimes I have a second intuitive reaction that the authors are so siloed they do not even know that domains other than their own exist and have their own literatures. I suppose both of these are true to some extent.

Lately I have come to see that there is increasingly no connection–no synthesis, no syndesis, not even any syncopation–in the evolution of theory. I think this has something to do with the habits of researchers to conduct so-called literature reviews online using Google Scholar, or worse just Google alone, and never bothering even to go to the many multi-disciplinary indexing services available online through most research libraries (this ought to be demonstrable empirically; perhaps one could take a random sample of published articles and actually search for relevant literature? Never mind that this is the responsibility of peer-reviewers!). Internet resources usually provide something quasi-relevant (remember Patrick Wilson’s excoriation that relevance often means “satisfactory”?–see Two Kinds of Power), enough to fill out the tiny tweet-like excuses for paragraphs most people manage to type these days. But this is no proper approach to science.

Theory requires connection and connection requires sequence in human thought. In order to make sense of an empirical observation all of the science available that can be brought to bear must be connected. To move that empirical observation forward as an hypothesis, or to move the hypothesis forward as a theory requires that observations be classified cumulatively. It all requires “syn”–synthesis, syndesis, syncopation.

If either of the people reading this blog are considering contributing to the science of knowledge organization let them hie at once to the ISKO website and use the powerful new KO literature search tool: http://www.isko.org/lit.html. While they’re at it, let’s urge them to go to the ISKO member’s portal at Ergon-Verlag http://www.ergon-verlag.de/isko_ko/ where they now can find KO from 1993 to the present and AIKO from 2006 to the present (and soon will find the entire backlog).