This paper is intended to be a representative literature review on the topic of mapping different thesauri and the uses of such for the organization of information to meet the needs of interdisciplinary scientists. Related ideas will be brought in at the end to highlight some of the other possibilities for information science to have a positive impact on the needs of interdisciplinary researchers.
In our attempts to make functional systems out of piles of intellectual content, librarians make many decisions that influence the course of exchange. … Some of our most important work is navigational. We plot intellectual connections by deciding how to represent materials and how they relate to each other. We further influence intellectual discussions by steering, or failing to steer, users in advantageous directions. The established academic disciplines and our current systems of information do not always explicitly represent newer territories and the interdisciplinary associations that link them. To find the answers that lie in the networks between disciplines, we learn to collect and combine elements by engineering paths around and through disciplinary divisions (Palmer, 1996b, p. 129-130).
As more than adequately expressed in the various articles in the Fall 1996 issue of Library Trends (Palmer, 1996b), interdisciplinary researchers face different issues in their information needs and usage than the typical disciplinary researcher. While these differences are not yet fully expressed, it is evident that they are often vastly different.
Bates (1996) addressed the need for more study of the “information needs and information-seeking behavior of scholars and students in interdisciplinary fields” (p. 155). What are “interdisciplinary fields” and what makes them so?
Interdisciplinarity is, at once, both an ancient and a new concept (Klein, 1990, p. 19), one that elicits much confusion. Klein attributes this confusion to three reasons: “general uncertainty over definition, lack of professional identity, and dispersion of discourse,” (p. 13) with the dispersion of discourse being the most fundamental (p. 13). Many attempts at defining interdisciplinarity have been attempted, to include teasing apart the difference between it and pluridisciplinarity, multidisciplinarity, and transdisciplinarity (see Klein, 1990; Iyer, 1995). Palmer (2001) states that “Over time, the term has become more commonplace but no less ambiguous” (ix) and that “debate about what it really means goes on” (ix). Taking a cue from Palmer (2001), I will not attempt to define interdisciplinarity. By looking at a variety of studies of interdisciplinary scientists’ information work I hope to cut across all of the various formulations of interdisciplinarity.
There have been as many attempts at measuring, quantifying and identifying interdisciplinarity, and at analyzing the specific problems faced by interdisciplinary researchers, as there have been at defining it. For example, McCain (1986) uses co-citation analysis, Hurd (1992) uses out-of-field citation rates, Palmer (1999, 2001) uses a qualitative practice-based approach, Borgman and Furner (2002) use bibliometric techniques, and Haythornthwaite (2006) looks at the kinds of exchanges that form the basis for collaboration. Weisgerber (1993) provides a comprehensive look at problems of searching experienced in interdisciplinary information work.
Mote (1962) introduced the concept of high and low scatter. He found that researchers in high scatter fields (large number of subjects, little organization) made ten times the number of requests for information than those in low scatter fields (well-defined subject, organized literature). Following up on Mote’s work, Packer and Soergel (1979) found that selective dissemination of information (SDI) services were helpful to those in high scatter fields, while in low scatter fields SDI reduced efficiency. Hurd (1992) showed that even in a discipline as “core” as chemistry there are almost as many out-of-field citations as within field.
The International Council for Scientific and Technical Information (ICSTI) Group on Interdisciplinary Searching was convened specifically “to study problems of interdisciplinary searching” (Weisgerber, 1993, p. 233-4). Their report is divided “into six distinct categories of problems” (p. 232): 1. Coverage and technical content of database; 2. Bibliographic information; 3. Textual content; 4. Numeric data; 5. File organization; and 6. Interdisciplinary searching on multiple hosts. Processes as simple as searching “journal titles, document titles, authors’ names, or patent assignees” require different search strategies for these researchers (p. 235). Improvements in all six areas would be realized by the use of classificatory structures, particularly standardized, interoperable structures.
“Classification is a tool that aids the storage and retrieval of information. Organizing information helps us learn new information and relate it to what we already know, and organization allows us to make sense of a world that continues to change and evolve” (McInerney, 1997, p. 1). Classificatory (or knowledge) structures are used to do this. Research in this area is one of the oldest areas of research, and it crosses as many or more disciplinary boundaries as any other concept.
Aristotle claimed that, “Man is by nature a political animal” (bk. 1, 1253a 2-3). Aristotle, Marcus Aurelius, Spinoza, and others, have claimed that man is a social animal. This author is in no position to disagree with these luminaries, but I would argue that before humans can be either of these we are first and foremost “the classificatory animal.” Conceptual division of the world by the human mind far proceeds either our social, or, political natures. In fact, human sociality (as considered by these writers) and politics are impossible without our ability to divide, sort and classify the world around us.
Categorization is not a matter to be taken lightly. There is nothing more basic than categorization to our thought, perception, action, and speech. Whenever we see something as a kind of thing, for example, a tree, we are categorizing. … Without our ability to categorize, we could not function at all, either in the physical world or in our social and intellectual lives (Lakoff, p. 5-6.)
Linguists, psychologists, and cognitive scientists are just a few of the many researchers who are actively working to understand the classificatory abilities of the human, and other, species. Researchers from these and other disciplines, such as information science, and computer science, are hard at work to understand the classificatory systems that humans instantiate through external, technologically-based (broadly construed) means. Some of these external means, of particular importance to information science, include classification schemes, indexing systems, and thesauri. At this point we will turn to the use of thesauri as a classificatory structure.
Thesauri are a form of controlled vocabulary, which includes lists, synonym rings, taxonomies, and thesauri, which exhibit increasingly complex structure (ANSI/NISO Z39.19-2005, p. 16-17). ANSI/NISO Z39.19-2005, Guidelines for the Construction, Format, and Management of Monolingual Controlled Vocabularies, is the U.S. standard for monolingual controlled vocabularies. Definitions of these concepts will come from the standard.
Controlled vocabulary: A list of terms that have been enumerated explicitly. This list is controlled by and is available from a controlled vocabulary registration authority. All terms in a controlled vocabulary must have an unambiguous, non-redundant definition (p. 158).
According to the standard, a minimum of two rules must be enforced.
1. If the same term is commonly used to mean different concepts, then its name is explicitly qualified to resolve this ambiguity. NOTE: This rule does not apply to synonym rings.
2. If multiple terms are used to mean the same thing, one of the terms is identified as the preferred term in the controlled vocabulary and the other terms are listed as synonyms or aliases (p. 158).
Thesaurus: A controlled vocabulary arranged in a known order and structured so that the various relationships among terms are displayed clearly and identified by standardized relationship indicators. Relationship indicators should be employed reciprocally.
Its purpose is to promote consistency in the indexing of content objects, especially for postcoordinated information storage and retrieval systems, and to facilitate browsing and searching by linking entry terms with terms. Thesauri may also facilitate the retrieval of content objects in free text searching (p. 166).
Thesaural structure comes from making explicit relationships between terms, which represent concepts. Most thesauri include three types of relations; equivalence, hierarchic and non-hierarchic (Iyer, p. 61). Equivalence relationships represent synonymy of concepts for the purpose of information retrieval, but not necessarily strict synonymy. For example, “children,” “preschoolers,” and “teens” may be considered synonymous in a thesaurus which has no need to differentiate the concepts (Iyer, p. 63). Hierarchical relations are generally either genus-species (generic) relations or part-whole (partitive) relations (Iyer, p. 62). For example, a “dog” is a “mammal” is a generic relation. Properties are inherited from the broader concept to the narrower. That is, a mammal is a warm-blooded animal which gives live birth to its young, and nurses the newborn on milk produced in the female’s mammary glands, …, thus, a dog is a warm-blooded animal which…. The part-whole relationship can be explicated by the following example. A “piston” is part of an “engine” which is a part of a “car.” These relationships are generally straightforward.
Non-hierarchical (associative) relationships are generally referred to as related terms. These relationships are usually contextually based, and are, thus, much harder to specify in advance. “Put simply, the associative relationship is found between two terms that are closely related conceptually but not hierarchically and are not members of an equivalence set” (Aitchison, et al., p. 60). There has been much analysis of non-hierarchical relations, and much disagreement. Khoo and Na (2006) report that some authors claim fourteen types (Aitchison, et al.), some ten (Lancaster, 1986; Raitt, 1980), while the Medical Subjects Headings (MeSH) have been shown to have sixty-seven (Bean, 1998) (p. 181). In one study cited by Aitchison, et al. (1997, p. 62), Perrault (1965) distinguished 120 different kinds of relationships. Some of the more typically recognized associative relationships include the whole-part associative relationship, a discipline and the objects of its study, an operation/process and its agent/instrument, an occupation and the person in it, an action and its product, an action and its patient, concepts related to their properties, concepts related to their origins, concepts linked by causal dependence, a raw material and its product, an action and a property associated with it, and a concept and its opposite (Aitchison, et al., p. 63-66).
While it is important to conceptually understand the kinds of relationships that make up the set of related terms, until recently, all the various kinds of associative relationships have been coded as generic related terms (RTs). More recently, many researchers have been taking a harder look at relationships in classificatory structures and systems. Bean and Green (2001) is representative of this work, while Khoo and Na (2006) present a good overview in their ARIST chapter, “Semantic Relations in Information Science.” Green (1995a, 1995b) has researched syntagmatic (as opposed to paradigmatic) relationships and how they might be expressed in information retrieval systems, and maintains that “conceptual syntagmatic relationships” can increase both recall and precision in information retrieval (1995b, 316). Tudhope, et al. (2001) have demonstrated how associative (and hierarchical) relationships can be extended via subtypes of these relationships and still maintain compatibility with traditional thesauri.
The rapidly increasing literature on interdisciplinarity and collaboration has clearly demonstrated that interdisciplinary researchers face issues in information retrieval of a kind different than the typical disciplinary researcher. Bates (1996) cites Mote (1962) and Packer and Soergel (1979) on scatter, Weisgerber’s (1993) summarization of the International Council for Scientific and Technical Information report, and Hurd (1992) on out-of-field citations as suggestive “that scholars in interdisciplinary fields may have to engage in both substantially more information seeking—and of a different kind—than scholars in a conventional discipline” (p. 159). Klein (1990) states that interdisciplinary researchers “need to know what information to ask for and how to acquire a working knowledge of the language, concepts, information, and analytical skills pertinent to a given problem, process, or phenomenon” (p. 183). What is not mentioned in this statement is that besides acquiring the knowledge and skills of knowing the what and the how of their core discipline—like a scholar in a conventional discipline—they must be able to do this in disciplines and subject areas for which they have no formal training or professionalization. Besides the problem of scatter—the dispersed nature of potentially relevant information—there is a second major problem faced by the interdisciplinary researcher according to Smith (2000), “the risk of information overload in extending a search across multiple sources without tools that aid in locating items likely to be of particular interest” (p. 103). The already mentioned ICSTI Report (Weisgerber, 1993) provides a dense listing, comprising over twenty pages, of the problems faced by interdisciplinary searchers. Reading the ICSTI Report (Weisgerber, 1993), I could not help but notice that a large number of the issues mentioned could be helped via a combination of controlled vocabularies, authority control, and the implementation of standards. Weisgerber mentions these solutions in many cases, but the use of controlled vocabularies would be appropriate as (partial) solutions in even more of them. Palmer (1996b) provides a good overview of these issues.
One tool that has been mentioned as a possible means of overcoming many of the problems experienced by interdisciplinary researchers is the use of mapped thesauri (Weisgerber, 1993; Bates, 1996; Palmer, 1996a; Smith, 2000; Chaplan, 1995).
In 1974, Smith (1974) wrote, “Two trends, the growth of interdisciplinary research and the proliferation of machine-readable databases, require that new techniques and tools be applied to facilitate use of scientific and medical literature in support of research” (p. 343). These two trends have not only continued since then, they have accelerated. Smith (1974) reports on the manual mapping of a portion of the Medical Subject Headings (MeSH) to three other thesauri—Subject Headings for Engineering (SHE), NASA Thesaurus (NASA), and Subject Headings Used by the USAEC (AEC)—for the purpose of automatic search extension (p. 344, 351). The mapping process consisted of following ten algorithmic rules. Testing was done with real world searches with no term expansion, and then with term expansion. Results showed that precision remained flat while recall increased (p. 349). With the particular thesauri used in this experiment, or more accurately the indexes that used them, the increase in recall was primarily for resources not normally found in Index Medicus, that is, technical reports and conference proceedings (p. 350). Smith suggests that a need for high recall (comprehensiveness), and a need for currency (technical reports, proceedings) might justify the resources needed to do mappings (p. 351). Other suggested uses for mapped thesauri are to provide automatic term suggestion for both indexers and searchers, and as a tool for improving individual vocabularies by exposing their weaknesses during the mapping process (p. 351).
Chaplan (1995) reports on a manual mapping of the Laborline Thesaurus to LCSH for assessing “the potential for automatic vocabulary switching” (p. 39), and “to identify the nature of the matches discovered during the mapping” (p. 43). Degree of match was indicated by the use of one or more of nineteen codes. The mapped thesauri were to be used to “facilitate multiple database searching in the Institute of Labor and Industrial Relations Library at UIUC (p. 43). Chaplan concludes that “manual mapping from a controlled vocabulary to LCSH, while extremely labor-intensive and time-consuming, is not impossible for a small, specialized thesaurus” (p. 59-60).
Ruan (2001) reports on a manual mapping of terms from LCSH, MeSH, the National Emergency Training Center’s Learning Resource Center (NETC) Subject List, and other specialized vocabularies, along with a local term list. This mapping has generated the FireTalk Thesaurus, which is used for both patron searching and for cataloging and indexing of all materials in the Illinois Fire Service Institute’s Library. FireTalk provides “consistency and integrity in the subject access mechanisms” provided by the FSI Library (Ruan, p. 233-234).
Manual mapping of thesauri is both “extremely labor-intensive and time consuming” (Ruan, p. 233). Research on the automatic generation and the automatic mapping of thesauri addresses the resource issues of manual mapping. Chen, et. al. (1995) report on the automatic generation of a thesaurus for the Worm Community System, and demonstrate “the feasibility of an automatic, domain-independent approach to the creation of online thesauri for scientific domains” (p. 190). The thesaurus “suggests related worm concepts that serve to trigger the searcher’s recognition and thereby broaden or sharpen the search” (Chen, et. al., 1997, p. 18). Chen, et. al. (1997) reports on the continuation of this research, which included the automatic generation of a thesaurus for the Drosophilia fly community and an automatic mapping between it and the worm thesaurus. Analysis of their experimental results showed a substantial increase in recall and a small increase (9.97%) in precision (p. 28). Other studies on the automatic generation of thesauri are reported in Chen, et. al. (1997).
Mapping of thesauri—manual and automatic—have been shown to be effective tools for use by researchers needing to cross disciplinary and subject boundaries. While there is still plenty of research needed in this area, particularly in automatic mapping, much research is taking place in areas closely related to mapping and thesauri.
Schatz, et. al. (1999) report on a Digital Libraries Initiative (DLI) project for federating search across multiple collections. Using a concept space approach to automatically index millions of documents their large-scale production system employed vocabulary switching to allow “interactive navigation across concept spaces” (p. 57).
MacMullen and Denn (2005) report on several studies “done in the development of ontologies and thesauri” designed to alleviate cross-domain searching in molecular biology, and others that address “the issue of fragmentation of knowledge in the literature across subdisciplines” (p. 452). In doing so, they have mapped “some broad research streams and specific “insertion points” for information scientists” (p. 454) to make a positive difference in the research of molecular biologists and bioinformatics researchers.
Tagging and folksonomies are another form of indexing, one which puts the description of aboutness in the hands of the users. Kipp and Campbell (2006) studied the collaborative tagging system del.icio.us and “suggest that there is continuity between conventional indexing and user tagging: a continuity that could form the basis for a complementary system of subject access that could enrich conventional indexing rather than crowding it out,” and that “the differences suggest that user tagging extends beyond the traditional objectives of subject access, and expresses a dynamic relationship between document and user, and between subject and task, which may lead to new ways of modeling subject access.” Kipp (in press) looks at the difference between user tagging on the collaborative tagging system for scholars citeulike, keywords assigned by traditional indexers, and keywords assigned by authors. This study is highly related to the concept of traditional thesauri as it compares terms based on thesaural relations (equivalance, BT, NT, RT). The majority of user terms fell into the related term category, which the author suggests could be used as entry terms into the formal vocabulary (p. 13).
Research into various forms of embedded services, particularly for the Web, hold out great promise for helping interdisciplinary researchers engineer “paths around and through disciplinary divisions” (Palmer, 1996b, p. 130). Soergel (1996) proposes SemWeb, which would be “an open, multifunctional, multilingual system for the integrated access to many kinds of knowledge about concepts and terminology” (p. 165). Johnson (2004) proposes a form of distributed Web services called Thesauro-Web, “a network of thesaurus access and navigation services,” which would “provide enhanced subject access for the World Wide Web and enhance the functionality of information retrieval applications” (p. 121). Tudhope, et. al. (2006) reports on the Terminology Services work of the Joint Information Systems Committee (JISC). As described by the JISC report,
Terminology Services (TS) are a set of services that present and apply vocabularies, both controlled and uncontrolled, including their member terms, concepts and relationships. This is done for purposes of searching, browsing, discovery, translation, mapping, semantic reasoning, subject indexing and classification, harvesting, alerting etc.
Besides being a partner in the JISC TS efforts, OCLC is also conducting their own research into Terminology Services. Their web site lists the various cross vocabulary mappings they have undertaken so far.
While there are certainly difficult issues to overcome in effectively mapping thesauri, and in generally achieving interoperability (see Aitchison, et. al., 2000; Lancaster, 1986; NISO, 2005), the work cited in this paper demonstrates that it is possible. At this point I would like to speculate on some efforts that I think might do more to assist interdisciplinary researchers. Bates (1996) reminds us that students in interdisciplinary fields may well face many of the same problems as interdisciplinary scientists do.
Based on my own experiences as a habitually “probing generalist” (see Palmer, 1999), I can fully empathize with the commenter in Palmer (1999) who said, “I need a translator—an easy way to learn the basics about other disciplines without being an expert, an easy way to read about things” (p. 252). One of the suggestions for “facilitating boundary-crossing information work” made in Palmer (1996a) is digitize integrative reviews of research and to provide links to the full text of each reference (p. 184). While fully agreeing with this suggestion, I would like to take it a step or two further.
Lancaster (1986) discusses micro- and macrothesauri, or as the NISO standard calls it, a microcontrolled vocabulary (NISO, p. 162).
Microcontrolled vocabulary: A subset of a controlled vocabulary, covering a limited range of topics within the domain of the controlled vocabulary. A microcontrolled vocabulary may contain highly specialized terms that are not in the broad controlled vocabulary. Such terms should map to the hierarchical structure of the broad controlled vocabulary. A microcontrolled vocabulary is internally consistent with respect to relationships among terms.
Information scientists could produce thesauri—manually or automatically—from both leading textbooks and these integrative reviews, which would serve as a macrothesaurus for a field. Microthesauri could be generated from the more in-depth literature, such as journal articles, white papers, conference proceedings, etc. It may even be possible to do this in three levels, instead of two. In that way, one (or a very few) overarching macrothesaurus could be generated for the sciences. Integrative research reviews and other mid-level forms of documentation would be used to generate an intermediate thesauri for each discipline, with these intermediate-level thesauri being the ones that are mapped between research areas. Finer-grained specialist thesauri would serve the needs of a specific set of researchers. Mappings could, of course, happen at all levels of thesauri, but it seems the intermediate level might provide the most productive level of mapping.
With more and more work taking place on and across the Internet, the pioneering work of projects like the Alexandria Digital Library’s ADL thesaurus protocol (Janée, et. al., 2004), Thesauro-Web (Johnson, 2004), the RDF thesaurus specification (Cross, et. al., 2000), JISC Terminology Services (Tudhope, et. al., 2006), OCLC’s Terminology Services (OCLC, 2007), along with research into extending thesaurus relationships (Tudhope, et. al., 2001; Green, 1995a and 1995b; Bean & Green, 2001), hold out great hope for enabling interdisciplinary scientists and students engineer “paths around and through disciplinary divisions” (Palmer, 1996b, p. 130).
I have found this subject and the work associated with it to be fascinating, to say the least. It was extremely hard for me to narrow my topic enough for a seminar paper. While I believe I have succeeded in doing so, there is so much more that I want to learn. It is my intention to continue my research into the topic of thesauri, particularly around the questions of interoperability and embedding in disparate services, in an independent study during the Spring 2007 semester. Depending on how far down this road my interests take me, it could turn into the basis of my CAS project. I am looking forward to the next semester or two to see where these interests, in fact, lead me.
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