Epistemology, Theory, and Methodology in Knowledge Organization: Toward a Classification, Metatheory, and Research Framework

This paper proposes a preliminary classification of knowledge organization research, divided among epistemology, theory, and methodology plus three spheres of research: design, study, and critique. This work is situated in a metatheoretical framework, drawn from sociological thought. Example works are presented along with preliminary classification. The classification is then briefly described as a comparison tool which can be used to demonstrate overlap and divergence in cognate discourses of knowledge organization (such as ontology engineering).

A Benefit-Risk Assessment Framework for Development of Clinical Guidelines in Diagnostic Radiology

Thesis (Ph.D.)--University of Washington, 2015-12

The Weight of Language and Action: Epistemic Stance, Methodological Action,and Theoretical Perspective in Knowledge Organization

Knowledge organization (KO) research is a field of scholarship concerned with the design, study and critique of the processes of organizing and representing documents that societies see as worthy of preserving (Tennis, 2008). In this context we are concerned with the relationship between language and action.On the one hand, we are concerned with what language can and does do for our knowledge organization systems (KOS). For example, how do the words NEGRO or INDIAN work in historical and contemporary indexing languages? In relation to this, we are also concerned with how we know about knowledge organization (KO) and its languages. On the other hand, we are concerned with how to act given this knowledge. That is, how do we carry out research and how do we design, implement, and evaluate KO systems?It is important to consider these questions in the context of our work because we are delegated by society to disseminate cultural memory. We are endowed with a perspective, prepared by an education, and granted positions whereby society asks us to ensure that documentary material is accessible to future generations. There is a social value in our work, and as such there is a social imperative to our work. We must act with good conscience, and use language judiciously, for the memory of the world is a heavy burden.In this paper, I explore these two weights of language and action that bear down on KO researchers. I first summarize what extant literature says about the knowledge claims we make with regard to KO practices and systems. To make it clear what it is that I think we know, I create a schematic that will link claims (language) to actions in advising, implementing, or evaluating information practices and systems.I will then contrast this with what we do not know, that is, what the unanswered questions might be (Gnoli, 2008 ; Dahlberg, 2011), and I will discuss them in relation to the two weights in our field of KO.Further, I will try to provide a systematic overview of possible ways to address these open questions in KO research. I will draw on the concept of elenchus - the forms of epistemology, theory, and methodology in KO (Tennis, 2008), and framework analysis which are structures, work practice, and discourses of KO systems (Tennis, 2006). In so doing, I will argue for a Neopragmatic stance on the weight of language and action in KO (Rorty, 1982 ; 2000). I will close by addressing the lacuna left in Neopragmatic thought – the ethical imperative to use language and action in a particular good and moral way. That is, I will address the ethical imperative of KO given its weights, epistemologies, theories, and methods. To do this, I will review a sample of relevant work on deontology in both western and eastern philosophical schools (e.g., Harvey, 1995).The perspective I want to communicate in this section is that the good in carrying out KO research may begin with epistemic stances (cf., language), but ultimately stands on ethical actions. I will present an analysis describing the micro and the macro ethical concerns in relation to KO research and its advice on practice. I hope this demonstrates that the direction of epistemology, theory, and methodology in KO, while burdened with the dual weights of language and action, is clear when provided an ethical sounding board. We know how to proceed when we understand how our work can benefit the world.KO is an important, if not always understood, division of labor in a society that values its documentary heritage and memory institutions. Being able to do good requires us to understand how to balance the weights of language and action. We must understand where we stand and be able to chart a path forward, one that does not cause harm, but adds value to the world and those that want to access recorded knowledge.

Layered Information Modeling and a Knowledge Organization Paradigm: Inherent Classification and the Design of Interoperable Systems

In knowledge technology work, as expressed by the scope of this conference, there are a number of communities, each uncovering new methods, theories, and practices. The Library and Information Science (LIS) community is one such community. This community, through tradition and innovation, theories and practice, organizes knowledge and develops knowledge technologies formed by iterative research hewn to the values of equal access and discovery for all. The Information Modeling community is another contributor to knowledge technologies. It concerns itself with the construction of symbolic models that capture the meaning of information and organize it in ways that are computer-based, but human understandable. A recent paper that examines certain assumptions in information modeling builds a bridge between these two communities, offering a forum for a discussion on common aims from a common perspective. In a June 2000 article, Parsons and Wand separate classes from instances in information modeling in order to free instances from what they call the “tyranny” of classes. They attribute a number of problems in information modeling to inherent classification – or the disregard for the fact that instances can be conceptualized independent of any class assignment. By faceting instances from classes, Parsons and Wand strike a sonorous chord with classification theory as understood in LIS. In the practice community and in the publications of LIS, faceted classification has shifted the paradigm of knowledge organization theory in the twentieth century. Here, with the proposal of inherent classification and the resulting layered information modeling, a clear line joins both the LIS classification theory community and the information modeling community. Both communities have their eyes turned toward networked resource discovery, and with this conceptual conjunction a new paradigmatic conversation can take place. Parsons and Wand propose that the layered information model can facilitate schema integration, schema evolution, and interoperability. These three spheres in information modeling have their own connotation, but are not distant from the aims of classification research in LIS. In this new conceptual conjunction, established by Parsons and Ward, information modeling through the layered information model, can expand the horizons of classification theory beyond LIS, promoting a cross-fertilization of ideas on the interoperability of subject access tools like classification schemes, thesauri, taxonomies, and ontologies. This paper examines the common ground between the layered information model and faceted classification, establishing a vocabulary and outlining some common principles. It then turns to the issue of schema and the horizons of conventional classification and the differences between Information Modeling and Library and Information Science. Finally, a framework is proposed that deploys an interpretation of the layered information modeling approach in a knowledge technologies context. In order to design subject access systems that will integrate, evolve and interoperate in a networked environment, knowledge organization specialists must consider a semantic class independence like Parsons and Wand propose for information modeling.