Information Retrieval and Knowledge Organization: A Perspective from the Philosophy of Science
2. The Field of Knowledge Organization (KO)
- the practical classification and indexing of books and other kinds of documents in libraries and bibliographical databases;
- philosophical principles, including Aristotle’s logic and Francis Bacon’s classification of knowledge, among many others; (The reader should be warned, however, that there are many misunderstandings about philosophical issues, including Aristotle’s role in classification. What is commonly attributed to Aristotle is a myth (see, e.g., , Chapter 2: “The Aristotelian Framework”).
- scientific and scholarly contributions, including, for example, the contributions of Aristotle, Carl Linnaeus, Charles Darwin and many other scientists to the classification of living organisms and all other things in the world;
- developments in information technology (IT), such as databases, communication networks and social media.
- To consider KO an intuitive process that does not need deeper justification. The original classification of journals in the citation indexes published by the Institute for Scientific Information, for example, was just intuitive (cf., , p. 602). In practice, many KO activities have been driven by this view: you simply start constructing a classification and stop when it seems to suit the purpose. A criticism of this perspective may state that any classification is always serving some interests at the expense of other interests, and if unanalyzed, it cannot be optimized for the purpose it is going to serve (cf., ). Of course, this view challenges the whole idea of KO as a needed field of study.
- To claim that since only the individual user knows their own “information need”, they are the only person qualified to set principles of what should be found in IR and how documents should be indexed or classified. This is the view underlying user-oriented and cognitive approaches in information science and KO and is discussed a little in the present article and more detailed in .
- To say that the best way, both economically and qualitatively, is to base KO on user tagging or related “social technologies”, implying that a deeper theoretical understanding of KO is unnecessary. User tagging is by some both seen as “democratic” and economically preferrable, while there are also critical voices (for a discussion, see ).
- To claim that KO is basically a technological problem, that, for example, when enough computer power and optimal algorithms are available, the problems of IR will be solved without a deeper theoretical understanding of KO. A version of this view is that the principles underlying systems such as Google are sufficient. This view dominates the IR tradition in computer science and shall be discussed further in Section 2. (Computer science is, however, also dominating in knowledge representation and ontology development; therefore, a simple dichotomy between knowledge organization and computer science cannot be made.)
3. Challenges from IR
- If you type in a sentence, such as: “It seems to be based on the problematic assumption that relations between concepts are a priori”, Google will retrieve the one article (and its possible copies and versions) that contains this exact sentence. This exact match is obtained because the search applies proximity operators and thereby can retrieve documents identical to the query. This is not, however, what is generally understood by “exact match” techniques (or “set-retrieval”), which were defined by  (p. 284):
- If you type in a number of terms such as “concepts”, “relations” and “a priori” from the example in point (a), Google will make a so-called “best match” search (also called “partial match”, “relevance ranking” or “weighted retrieval”) and retrieve millions of documents in a ranked order according to some principles, which are more or less business secrets. (The one article retrieved in point (a) is not among the top results).
- It is well known that Google also uses a kind of popularity measure; the more in-links a certain document has, the greater the weight it is given and the higher it is listed in the ranked order shown to the user. This is often, if not in most cases, working very well because people often want the same as the majority. However, in searching for rare diseases, for example, this has proven a bad principle because rare diseases are, by definition, not a majority issue (for empirical demonstration of the failure of this principle for IR about rare diseases, see [37,38].
- The fourth major principle in search engines is personalization; Google can identify users’ IP address and thereby their physical location as well as their search history on Google, and may adapt, not just the advertisements, but also the so-called “organic results” in the ranked list presented to the user. This provides an element of subjectivity and randomness into the search and harms the ability to make conscious search strategies. It is also a double-edged sword; sometimes, it works well, but other times, you may want to eliminate this element, you may want more objective searches, you may have changed interests, or you may be searching on behalf of others. This is why the focus on past search interests may be harmful rather than fruitful.
- selecting high-quality sources (e.g., journals with high impact factors); (See , Section 6 about the quality of indexed documents. Some citation indexes such as the Web of Science cover more limited amounts of indexed sources (based on journal impact factors), compared to, for example, Google Scholar, and use this to argue for a higher quality in the retrieved documents. This is, however, an open hypothesis, which seems to have been challenged by , who found that important papers are more and more published in non-elite journals. For a criticism of the journal impact factor, see, for example, ).
- selecting documents based on principles used in so-called evidence-based research (e.g., studies based on double blind clinical trials); In evidence-based medicine (or evidence-based practice in general, EBP) the trustworthiness of claims about the effectiveness of a given treatment are classified according to the quality of the research methods employed. Explicit norms should be made for investigations that are most relevant, and a hierarchy of the value of different kinds of research methods as evidence should be made (where randomized controlled trials are considered to be a high level of evidence, while, for example, evidence from expert committee reports is considered to be a low level of evidence). There has been criticism of such views, and there is an example of two different systematic reviews based on this procedure that provide very different conclusions (cf., ). Regarding IR, the EBP model provides clear criteria for prioritizing information sources, although, as already said, they are not uncontroversial.
- Selecting documents based on their influence measures, e.g., their number of citations, in general or within some specifications (e.g., papers highly cited within leading journals in the field).
- basing IR on quality KOS (such as our thought experiment with Swedish cities). In addition to such KOS, it is necessary that each document is assigned to the most relevant classes in the KOS, which is not a trivial issue, but depends both on the specific qualifications by the indexer and by the indexing philosophy used by the system, e.g., the operationalization of the concept “subject” (cf., ). (Ref.  Section 5.2, put forward the hypothesis, that indexing done by MEDLINE, one of the most important bibliographical databases in the world, may be based on principles that are too mechanical.)
4. Knowledge Organization Systems (KOS) and the Semantic Staircase
4.1. Classification Systems
- derives_ from
4.4. The Semantic Staircase
5. Concept Theory and Realism
5.1. Challenges from “Smithian Realism”
- Universals have an observer-independent objective existence; they are invariants of reality.
- Bad ontologies are those whose general terms lack a relation to corresponding universals in reality, and thereby also to corresponding instances.
- Good ontologies are representations of reality. A good ontology must be based on universals instead of concepts.
5.2. What Are Concepts?
5.3. Does a KOS Need to Contain Universals and Symbolic Structures in Addition to Concepts?
- Concept  (p. 301–302): “Concepts are categories that are expressed by linguistic expressions and which are represented as meanings in someone’s mind. Concepts are a result of common intentionality which is based on communication and society (Searle, 1995) ”. (Ref.  (p. 302, footnote 7): “The mental representation of a concept allows us to understand a linguistic expression. Concepts are outside of individual minds, but they are anchored, on the one hand, in individual minds by the concepts’ mental representation, and on the other hand, in society as a result of communication and usage of language”.)
- Category  (p. 301): “Categories are entities that are expressed by predicative terms of a formal or natural language that can be predicated of other entities. […]. We distinguish at least three kinds of categories: universals, concepts, and symbol structures. We hold that any reasonable foundational ontology must include these three types of categories”.(It is difficult to understand Herre’s difference between categories and concepts. Both categories and concepts may be expressed by linguistic expressions and predicative terms and may be represented in somebody’s mind. Ref.  wrote: “Categories are hard to describe, and even harder to define. This is in part a consequence of their complicated history, and in part because category theory must grapple with vexed questions concerning the relation between linguistic or conceptual categories on the one hand, and objective reality on the other”. Concepts and categories are often defined in ways that make them synonyms, but categories may also, and probably better, be used about the highest kinds or genera, such as Aristotle’s 10 categories: substance, quantity, quality, relation, place, date, posture, state, action, and passion. This way of understanding categories has its own philosophical history (see, e.g., ). For more detail about the relation to Ranganathan’s categories in KO, see )
- Symbol/symbol structure  (p. 302): “Symbols are signs or texts that can be instantiated by tokens. There is a close relation between these three kinds of categories: a universal is captured by a concept which is individually grasped by a mental representation, and the concept and its representation is denoted by a symbol structure being an expression of a language. Texts and symbolic structures may be communicated by their instances that a[re] physical tokens”. Further (p. 304): “One must distinguish between symbols and tokens. Only tokens, being physical instances of symbols, can be perceived and transmitted through space and time”.Ref.  (p. 120): “Tokens are said to instantiate types: they exemplify, embody, manifest, fall under, belong to types; they’re occurrences, instances, members of types. Tokens are treated as individuals, singles, particulars, substances, objects; they’re concrete, real, material. Types, on the other hand, are like sorts, kinds, forms, properties, classes, sets, universals; they’re said to be abstract, ideal, immaterial.”
- Universal  (p. 301): “Universals are constituents of the real world, they are associated to invariants of the spatio-temporal real world, they are something abstract that is in the things”.
- It seems unnecessary to define categories and concepts as entities that are expressed by terms or linguistic expression. We might conversely say that concepts may be expressed by words, and that concepts that have a linguistic or symbolic expression are lexicalized. Ref.  (p. 237) wrote that WordNet introduced the non-lexicalized concept “wheeled vehicle”: “The argument is that people distinguish between the category of wheeled vehicles and vehicles moving on runners independently of whether this distinction is lexically encoded in their language”.
- As already presented in Section 4.1, there is a discussion in the ontological literature between a realistic position that rejects concepts as units for KOS and another realist position (like Herre and the present author), which defends concepts as units in KOS. Herre’s statement that concepts are “represented as meanings in someone’s mind” may, however, make it more difficult to see his position as representing realism (although his argument is partly saved by his addition that concepts are a result of a common intentionality, that they are social). We shall return to this problem about realism in Section 5.4.
- Herre finds that ontologies/KOS must include universals, but his position on this point seems not to be crystal clear. On the one hand, he writes  (p. 305): “In sum, the nodes in an ontology are labeled by terms that denote concepts. Some of these concepts, notably natural concepts, are related to invariants of material reality”. This is in line with the semiotic triangle and in accordance with the view expressed by the present author. However, he  (pp. 326–327) also speaks of facts, defined as “The simplest combinations of relators and relata”. Perhaps Herre’s view is opposed to that of  (p. 4): “In hermeneutics, we defend the idea that there are no pure facts. Behind every interpretation lies another interpretation. We never reach an understanding of anything that is not an interpretation”. If we follow this view, it seems that universals are not elements in ontologies since we can only know them as interpretations and concepts. This is further discussed in Section 5.4.
5.4. Pragmatic Realism
- Go to a given domain,
- Look at how it is classified according to contemporary knowledge (including different views),
- Discuss the basis, the epistemological assumptions and which interests are served by proposed classifications,
- Suggest a motivated classification.
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Hjørland, B. Information Retrieval and Knowledge Organization: A Perspective from the Philosophy of Science. Information 2021, 12, 135. https://doi.org/10.3390/info12030135
Hjørland B. Information Retrieval and Knowledge Organization: A Perspective from the Philosophy of Science. Information. 2021; 12(3):135. https://doi.org/10.3390/info12030135Chicago/Turabian Style
Hjørland, Birger. 2021. "Information Retrieval and Knowledge Organization: A Perspective from the Philosophy of Science" Information 12, no. 3: 135. https://doi.org/10.3390/info12030135