Museum Management and Curatorship (1990), 9, 73-83

Automating the Documentation of Museum Collections

PHILIP DOTY

The history of the automation of museum information is full of false starts and false promises. While new information technologies and systems offer great power and new capabilities to museums, the majority of museum information systems are manual or personal, i.e. kept in staff members’ heads. Automation is obviously not the solution to all information problems in any organization, but, like any tool, it can be quite useful when used in the proper context. This paper focuses on the automation of information related to the documentation of museums’ collections. It discusses some of the history of the automation of collection documentation and some of the major issues involved. The perspective taken here emphasizes the museum as an information system, of which information about collections is one component. The paper also assumes that museum information systems are intended to serve the varied and often conflicting needs of a number of diverse audiences.

Introduction

It is by now a commonplace to say that information technology has evolved quite rapidly in the last thirty-five years and that computing power has increased dramatically. The cost of that power and the size of the machines have decreased just as dramatically. While business and higher education have taken advantage of these advances, museums have been markedly slower in adapting sophisticated information technologies to support their information activities. Nonetheless, there has been considerable interest, in both the museum and information professions, in the application of computer-based information technologies to museum problems. (See for example, Light et al., 1986; Markey, 1984; Raben and Burton, 1981; Roberts and Light, 1980; Samuel, 1988; Stam, 1988; Williams, 1987; for descriptions and analyses of the history of museum information automation. These authors also identify important trends and issues regarding museum computeriza- tion.)

One of the first major events in the automation of museum information was the conference held at the Metropolitan Museum of Art in New York City in 1968 (Computers and Their Potential Applications in Museums, 1968; Markey, 1984). That conference was characterized by commitment, however tentative, to the computerization of museum information and a belief in the promise of computerization in fulfilling museum functions. That promise has yet to be fulfilled as completely as the attendees of the conference had hoped.

While the reasons for museum computerization’s failure to live up to expectations are complex, several have been identified, and they are discussed on the following pages.

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74 Automated Documentation

They include:

(a) characteristics of museums; (b) the communications gap between museum professionals on the one hand and the

designers and implementers of automated information systems on the other; (c) lack of sufficient planning and research by both museum and information

professionals; (d) lack of resolution about authority control issues; (e) unique characteristics of museum collections and their documentation; (f) the nature of art historical research; (g) philosophical/epistemological issues concerned with museum objects and their

surrogates.

Why the Automation of Collection Documentation Has Been Slow

Characteristics of Museums

Museums have been described as storehouses of objects and knowledge about them, and, like other cultural institutions, museums aim to preserve traditional knowledge and generate new knowledge (Ambach, 1980: 14; Andersson, 1988: 290). While the museum community is not monolithic, since a museum may be dedicated to a collection in science, history and/or the applied and fine arts, museum staffs of all types are usually steeped in the humanist tradition and are concerned with protecting its heritage. Such conservatism, coupled with the financial strictures most museums must face, encourages a fundamentally slow rate of change and a perception among some that information technology may pose a threat to the world of learning that the museum is meant to serve (Blackaby, 1988: 32; Lindsay, 1968: 19; Moffett, 1988; Raben and Burton, 1981: 258).

In addition, the museum world has been called ‘factional’ (‘Museum Automation . . . ‘, 1988: 47) and museums ‘isolated’ (Williams, 1987: 59). This factionalism is especially acute in the United States where there is no sense of a national cultural patrimony and where other cultural factors militate against inter-institutional cooperation.’ Institutional isolation, in turn, discourages the development of profession-wide standards, and such standards, especially in object cataloguing, are essential to the success of information automation even within individual museums. As a result, museum computer projects are characterized by individualism and a lack of coordination (Markey, 1984: 292). Thus, few museums learn from the successes or failures of other institutions’ automation of their collection information.

Communications Gap

Even within individual institutions, lack of communication is a major obstacle to the success of a project to automate collection information. One reason for communication problems stems from museum professionals’ preference for subtlety and ellipsis in their description of objects. Computerized systems, based on gross matching algorithms, demand specificity, exactness and consistency (Stam, 1987a: 56, 59). The computer’s demand for rigor in documentation may be somewhat foreign to museum professionals, who, because of uncertainty about technology, have sometimes been ‘forced to tailor their information handling needs to the limitations imposed’ by often inadequate and inappropriate systems (Avedon, 1988; Sarasen, 1981: 46). Also, there are few information automation companies experienced in working with museums and able to help them

PHILIP Don

bring their language into conformity with information systems’ limitations.

75

At the same time, however, ‘the vagaries of nomenclature and variant spellings so deprecated by data managers are the very stuff of much scholarly research’ in museums (Cannon-Brookes, 1988: 228). To bridge the gap between museums and automation vendors and consultants, museum professionals must overcome both ignorance about technology and any technophobia. These changes must occur if museum staffs are to be realistically demanding about information automation systems and as informed as necessary to ensure that such systems do justice to the museum’s information needs and mores. Information automation also offers a splendid opportunity for museum professionals to re-examine assumptions and presumptions about their fields of expertise and to understand them more completely. Computerization demands a thorough understanding of one’s area of competence and of its information problems (Furth, 1968: 10; Hoving, 1968: ix).

The literature is full of references to failed automation projects for collection information that were doomed by museum professionals’ unrealistic expectations (see, for example, Chenhall and Vance, 1988; Roberts and Light, 1980; Samuel, 1988; Sarasan, 1981; Turner, 1988; Vance, 1979; Williams, 1987). Documentation automation projects often also suffer from a lack of full administrative support and commitment in the form of money, expertise and adequate staff time.

Research and Planning

One of the paradoxes of an automation project is that planning, which is essential to success, must take place at the beginning of a project when museum staff are the least knowledgeable about their own information needs and behavior and about possible information systems. This paradox is another reason for museums to encourage cooperation and sharing of information and experience. Lack of adequate planning is recognized as a major cause of project failure.

The overall controlling factor for any information system, manual or computerized, is its purpose. The goals and objectives of an information system must be consonant with the goals and objectives of the institution at large, but consonance cannot be achieved without a clear understanding and articulation of institutional mission. A major gap in the museum world is the lack of clear, specific mission statements in many institutions. Only by identifying its specific intended audiences, purposes and methods of achieving those purposes can a museum begin to understand how an automated collection documentation system can support museum activities.

One of the first steps is an information audit, that is a systematic study of the museum as an information system. The questions to be answered include: Who in the organization generates information? Who needs it? In what form or format is it needed? Where is information stored? Which people share information? Who controls the various flows of information? Who organizes the information? How is it organized? These questions are applicable to any organization, but, since a museum is fundamentally concerned with knowledge, education and the transmission of information, the answers to them are essential to any museum’s identity.2

Once these questions are asked and addressed, additional questions must be asked about the automated system for collection documentation, including: Who will use it? For what purposes ? How much will it cost initially, and to maintain and update? Who will have access to the system ? Is it strictly for in-house use or will non-staff be able and/or encouraged to use it? What will the records look like? Who will enter data? Who

76 Automated Documentation

will supervise and be responsible for implementation and staff training? How long will it take to implement? How will it be evaluated? What will the relationship be between the new system and the old one(s)? Who will decide how to answer these and other questions? All of these issues are concerned with policy; therefore, they must be considered and answered by those high enough in the organization to have the power and will to decide before the project leaves the planning stage.

All museums can undertake an information audit and analysis of an automated automation project, using either staff on hand (if they are granted sufficent time for study and related activity) or consultants and vendors. The automation of collection documentation emphasizes that information is an organizational resource and that its successful management depends upon adminstrative commitment of other resources, including staff time, money, administrative attention and other support.3

Authority Control

A question of particular importance in museum documentation involves the control of terms used to describe artifacts. As noted earlier, there is no general cataloguing convention for museum artifacts. Scientific nomenclature, especially in the biological sciences, provides science museums with a decided advantage over history and art museums which have no such universally accepted vocabulary.4 Thus, the terms in most museum catalogue records (vocabulary), the manner in which they are arranged (syntax) and the rules according to which they are arranged (grammar) are not commonly agreed upon from institution to institution. It is clear, however, that at least a uniform syntax is necessary for museums to maximize the usefulness of automating the documentation of their collections (Samuel, 1988: 152).5

There are a number of vocabularies and vocabulary projects in the museum field. Foremost among these are ICONCLASS, the Art and Architecture Thesaurus (AAT), Chenhall’s nomenclature and the work of Fransois Garnier (Markey, 1984; Raben and Burton, 1981). Just as purpose determines the design and implementation of an information system, so does purpose determine the words applied to museum artifacts. In fact, all cataloguing, whether of museum objects or not, involves interpretation and a subjective stance (Stam, 1987a). Thus, the development of vocabulary alone is insufficient to solve all museum documentation problems: syntactic rules must be specified and implemented and cataloguing policies articulated and shared.

Museum Collections and Documentation

Museum objects, unique or otherwise, have claim to value by the very nature of their being in a museum. As such, these artifacts are cared for, preserved and exhibited. In addition, museum professionals’ responsibility has grown to include accurate and complete documentation (Samuel, 1988: 143). Several factors have contributed to an increased emphasis on documentation in museums :

1. The mobility of museum personnel (Sarasan, 1981: 40) and explosive growth in the size of collections have effectively decreased the likelihood that a single person or group of people could store all salient information about a collection in their personal memories.

2. Tightened budgets and closer government and public scrutiny of museum operations have necessitated the fuller documentation of museum artifacts, especially with regard to insurance coverage and intercultural theft.

PHILIP Don 77

3. The educational functions of museums are being increasingly stressed, and documentation helps to support that function (Miles, 1987: 73).

Thus, while there is a greater demand for artifact documentation, the lack of a uniform vocabulary and cataloguing format virtually guarantees that documentation’s usefulness is severely limited by an emphasis on purely local concerns.

The evidence suggests that there is often considerable overlap from museum to museum in the kinds of information considered important (Stam, 1988: 17). At the same time, however, this advantage is outweighed by the multiple uses to which museum documentation is put, e.g. to support curatorial and registrarial activities, to aid outside scholars, to demonstrate accountability to museum boards and government officials, and to support public exhibitions. Such multiple uses (identified, of course, during the information audit/planning stage of an automation project) militate against the formation of common records and formats for records of museum artifacts, thus decreasing the likelihood of automation success.6

A further difficulty lies in the fact that museum ‘object information is dynamic and changing’ (Allen, 1988: 179). As knowledge about artifacts increases and as scholarly opinions and perspectives change, artifact records grow in size and complexity. The dynamic nature of documentation keeps the records from ever being closed (Roberts and Light, 1980: 58; Samuel, 1988: 146). This dy namic nature is not easily accommodated by computerized systems which depend most often upon fixed vocabularies, fixed data fields, unambiguous entries and fixed-length fields. In addition, most curators regard their records, often the heart of documentation records, as individual scholarly contributions to their disciplines and are, therefore, unwilling to share them except under very controlled conditions (Bearman and Gary, 1987: 74; Stam, 1987b).

Art Historical Research

Bearman and Szary also note that ‘more important than facilitating the retrieval of artifacts in the museum’s collection, the museum catalog provides access to recorded scholarly judgments concerning the artifacts’ (1987: 74). Scholarly judgments, especially in art historical research, include multiple and often conflicting viewpoints and a great deal of apparent redundancy. Both these characteristics conflict with the ‘clean’ record desired by the data manager of an automated information system,7 as does the existence of ‘multiple truths’ (Stam, 1987b). A recent development that supports the computerization of documentation information, however, is the appearance of hybrid, interdisciplinary scholars, who concentrate on micro-units of information (Raben and Burton, 1981: 248-249).8 Such scholars need the power of automated information systems, and if museums hope to support the work of these scholars, collection information must be computerized.

Philosophical Issues

The final reason to be discussed for the relatively limited success of museum documentation’s computerization involves the status of object surrogates, whether optical or textual. Library cataloguing, sometimes seen as a model for museum object cataloguing, relies exclusively on linguistic representation of the object at hand. The inadequacy of language as a medium for describing an artifact, particularly a work of art, has been commented upon, e.g. by Stam (1988: 5), and deserves further investigation and discussion.’ In addition, while bibliographic records are usually not ends in themselves,

78 Automated Documentation

museum records, especially of art objects, ‘are often a [full] surrogate for the object itself (Allen, 1988: 192). The objects in science and history museums also are often experienced by viewers in representations, as (analogue) textual/optical reproductions in slides, books and museum catalogues, or as digitized images in an online environment. The epistemic status of all these representations is further called into question because the connection between objects and their images (textual or visual) and information about them is not necessarily desired or desirable in all museum settings (Stam, 1987b: 34).

As noted above, scholars in the humanities are becoming increasingly interested in micro-units of information. Unlike music and literature, however, ‘content in the visual arts is seldom unitized as it comes’ (Paisley, 1968: 199), and this situation underscores the difficulty inherent in artifact cataloguing. Does a museum cataloguer specify all the ‘information’ related to an object (size, material, date, ‘creator’, ‘subject’, object represented, ad infinitum), or should the cataloguing record be more strictly defined? Even if a common vocabulary and syntax were to develop for artifact cataloguing, this question would still be extremely difficult to answer.

Museum professionals and scholarly researchers of all types also question the easy assumption that increasingly sophisticated optical and digital representations can duplicate the experience of actually looking at and handling an object itself. Some commentators, caught up in enthusiasm about laser and other sophisticated storage media, dismiss artifacts as nothing more than the information that can be stored about them. Such is not the case.

A more engaging issue is raised by Howard Besser, (1987: 78-80; and Honan, 1988: 2-9). Besser maintains that the ability to digitize, store and manipulate images of museum artifacts, an ability given by increasingly sophisticated information technolo- gies, promises to democratize access to museums and their stores of objects. More fundamentally, however, this ability questions and erodes the authoritative positions of makers of objects, exhibition designers, curators and museums as a whole. Besser concludes that ‘as a result of the democratization, the museum loses its authority as the only place to view objects and becomes less of a sanctified place’ (1987: 80). Museums and museum professionals may be unwilling to surrender their staus as the authorities about artifacts.

Current Trends

In 1968, Allon Schoener noted that ‘no longer object recognition, museum education has become information distribution’ (p. 363). Both museum professionals and others who use museums have new, digitized, optical and textual storage media at their disposal which support information distribution and manipulation in ways unthought of even just a few years ago. Hypermedia especially, which give the user simultaneous access to multiple sources and points of information, offer great potential for documentation of museum artifacts (Cash, 1988: 58-59). lo The images stored in such hypermedia, however, are subject to the epistemic and social doubts noted above.

Some commentators also see great promise in integrated software for all museum operations, usually based on the fixed formats of relational database management systems (DBMS). Such systems might control curatorial, collection management, documentation and other activities in one coordinated and connected structure (‘Integrated Museum Database . . . ‘, 1987: 115-116; Vance, 1988a: 67-69). These

systems, of course, have major drawbacks, often demonstrated by the difficulties of certain database management systems in business, library and other educational settings.

PHILIP Don 79

Dixon (1987) offers an interesting counterpoint to the usual DBMS, and Bearman (1988: 34-35) argues that museums could purchase more off-the-shelf software if they were more willing to give up their indigenous systems and aim at greater cooperation.

Roberts and Light (1980: 57), speaking f rom experience with museum computing in the UK, assert that ‘potential is offered by the approach of developing small catalogues within a restricted field of interest’, e.g. type specimens, rather than by large-scale, national/international efforts. The meteoric rise of the microcomputer also tends to encourage smaller projects as opposed to the ‘union catalogue’ systems envisioned in the early days of museum computerization (Light et al., 1986; Roberts and Light, 1980; Stam, 1988). The tendency for museums to cooperate more fully in smaller groups will probably continue.

Another trend, described above, is an increasing emphasis on collection documenta- tion. Although Allen (1988: 185) notes the creation of the position of ‘computer documentation coordinator’ at the Museum of Fine Arts in Boston, Homulos (quoted in ‘Museum Automation . . . ‘, 1988: 45) asserts that although ‘distinct professions exist within the museum field . . . documentation or information management is not recognized as one of them’. In addition, documentation research has received relatively little coordinated and sustained support in both the museum and information professions (Roberts and Light, 1980: 71), despite projects like the major vocabulary efforts noted earlier and the Getty Foundation’s Museum Prototype Project.

Future Possibilities

The future holds many opportunities for museum professionals and the computerization of collection documentation. Even such a brief review as this paper suggests several areas for change that might improve the success of automation projects for museum documentation information. These areas include:

(a) development of greater technical and computer expertise among museum professionals;

(b) insistence of museum professionals upon responsive information consultants, knowledgeable about museums and their information needs;

(c) management of museum information as an institutional resource and examination of the museum as an information system;

(d) further research into museum documentation, with special emphasis on vocabulary (authority) control, syntax and grammar of records, digitized optical storage media and the open-ended nature of artifact records;

(e) identification and analysis of museums’ audiences, missions and information policies;

(f) most importantly, administrative recognition of the value and necessity of planning and the commitment of adequate resources to any museum automation project, including documentation automation.

Of course, any such list is only tentative, and is neither comprehensive nor prescriptive. If, however, museums do not re-examine themselves and the issues discussed above,

many of them will never enjoy the benefits of automated documentation because projects will never begin, while those projects which do start may never reach fruition. Thus, museums may never reap the full benefits of their investment of money, time and their staffs’ good faith.

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10.

Light et al., 1986; Stam (1987a: 26ff.; 1987b: 63-64) identifies and discusses important internal and external factors that affect museum information systems. Some nations, especially France, Canada and the United Kingdom, have made progress in developing automated ‘national’ systems, and it is in such national efforts that the internal and external factors are most fully expressed (Chenhall and Vance, 1988: 100; Roberts and Light, 1980). Information Resources Management (IRM) is an area of information studies that emphasizes the identification and management of organizational information resources, flows and patterns. Some of its tenets can be fruitfully applied to museum settings. See the bibliographic appendix for a short list of useful, basic sources. Sources for general issues on museum automation planning are Chenhall (1968), Chenhall and Vance (1988), Light, (1982), Miles (1987), ‘Museum Automation . . . ’ (1988), Sarasan (1988), Turner, (1988), Vulpe (1986).

Sources with specific guidance on automation planning for museums include Biddle (1988), Friedman (1988), ‘Integrated Museum . . . ’ (1987), Orna (1982), Sarasan (1981, 1987). These authors provide clear ‘how-to’ and ‘how-not-to’ information.

Thompson (1987) gives a fairly comprehensive list of the names, addresses and other pertinent information about professional organizations; networks and databases; vendors of systems for collection information and management, membership, development and fund accounting; systems and projects for exhibitions, education and communication; and books, directories and periodicals. This list, although now two years old, is useful for its specificity, coverage and explanatory annotations. The powers of the Linnaean system, in particular, to describe and classify may help explain why zoo animals are particularly well inventoried and documented (see Greene, 1988: 30). This taxonomy, of course, does have its limitations, especially with intermediate forms. There has been some movement towards the sharing of collection documentation information, and some commentators have suggested that shared technologies and systems may offer such sharing of information a greater chance of success, e.g. Stam (198713). Stam (1987b: 32) notes that information in art history documentation is composed of both private and public elements, a distinction which also mitigates against an automated system’s success. Bearman (1988: 74) lists three major attributes of a scholarly database useful in artifact documentation: ‘discipline-specific access points, vocabularies and views; conflicting authorities at the field level; and multiple independent attributions of authority’. Micro-units are the ‘bits of information that are observed, encoded and manipulated’ by scholars (Raben and Burton, 1981: 249). This approach supposedly encourages greater objectivity, deeper understanding of an artifact as the result of process, and fuller revelation of the scholar’s methodology than does traditional scholarship. See Gardin (1968) who is especially good on these and other theoretical, ‘semiological’, and deconstructionist issues, and whose comments are still evocative twenty years after having been made. Also see Honan (1988) and Besser (1987). Many articles in the Summer 1988 issue of Museum News also refer to hypermedia and their possibilities in museums: for exhibitions, tours, remote access, and so on. Oddly enough, however, the terms ‘hypermedia’, ‘hypertext’ and ‘interactive multimedia’ hardly ever appear in the museum and museum documentation literature. This lack is not purely a function of the relative youth of these concepts because the same literature discussess the concepts and technologies enthusiastically and at length.

Bibliography

Allen, Nancy S. (1988) ‘The Museum Prototype Project: A View from the Library’, Library Trends, 37: 175-193.

Ambach, Gordon (1980) ‘Why Museums Need Networks’, Museum News, fi9 (3): 13-17. Andersson, Paul (1988) ‘Computers II: The New IBM AS/400 Computer-Its Significance for

Museums’, International Journal of Museum Management and Curatorship, 7: 289-292. Avedon, E. M. (1988) ‘Entity-Relationship Modeling’, Museum Computer Network Annual

Conference, 1988. Bearman, David and Szary, Richard (1987) ‘Beyond Authorized Headings: Authorities as Reference

Files in the Multi-Disciplinary Setting’, in Karen Muller (ed.), Authority Control Symposium,

PHILIP DOTY 81

Occasional Papers No. 6, 69-78. Tucson, AZ: Art Libraries Society of North America. Bearman, David (1988) ‘Software Trends for Museums’, Museum News, 66 (6): 34-35. Beniger, James R. and Freedman-Harvey, Georgia (1987) ‘High Tech-The Dilemma For Museums’,

Museum Studies Journal, 3: 66-72. Besser, Howard (1987) ‘Digital Images for Museums’, Museum Studies Journal, 3: 74-81. Biddle, Mark I-I. (1988) ‘The Legal Side of Buying a Computer’, Museum News, 66 (6): 76-77. Blackaby, James R. (1988) ‘On Learning to Use a New Appliance’, Museum News, 66 (6): 32-33. Brite, Rebecca (1988) ‘Parlez-Vous Computer?‘, Museum News, 66 (6): 12-14. Cannon-Brookes, Peter (1988) ‘Control of Terminoiogy but not Its Limitation’, ~~~er~a~~o~~~~ou~~~

of Museum Management and Curatorship, 7: 227-230. Cash, Joan (1988) ‘Picture Power: Optical Discs and Video Computing Come of Age ‘, Museum News,

66 (6): 58-60. Chaffee, Holly M. and N&f, Jeffrey M. (1979) ‘Computers and Registration: A Case Study’, in

Dorothy H. Dudley and Irma Bezold Wilkinson (eds.) Museum Registration Methods, 3rd ed., 335-339. Washington DC: American Association of Museums.

Chenhall, Robert G. (1968) ‘The Analysis of Museum Systems’, in Computers and Their Potential Applications in Museums, pp. 59-79. New York: Arno Press.

Chenhall, Robert G. and Vance, David (1988) M useum Collections and Today’s Computers. New York: Greenwood Press. Computers and Their Potential Applications in Museums (1968) New York: Arno Press.

Computers and Their Potential Applications in Museums (1968). New York: Arno Press, Dixon, Rob (1987) ‘CMASS: A R p es onse to the Smithsonian Institution’s Statement of the Problem

Document’, International Journal of Museum Management and Curatorship, 6: 201-206. Dreyfus, Hubert L., Dreyfus Renee B. and Dreyfus, Stuart E. (1987) ‘Skilfully Coping with the World:

Man vs. Machine’, Museum Studies Journal, 3: 45-57. Friedman, B. Albert (1988) ‘Computers III: Selecting a Museum Computer System’, Z~ternat~onal

Journal of Museum Management and Curatorship, 7: 293-297. Furth, Stephen E. (1968) ‘Data Processing for Information Storage and Retrieval’, in Computers and

Their Potential Applications in Museums, pp. 5-18. New York: Arno Press. Gardin, J.-C. (1968) ‘On Some Reciprocal Requirements of Scholars and Computers in the Fine Arts

and Archaeology’, in Computers and Their Potential Applications in Museums, pp. 103-124. New York: Arno Press.

Green, Dee F. (1968) ‘A Prototype Computerized System for Archaeological Collections”, in Computers and Their Potential Applications in Museums, pp. 39-57. New York: Arno Press.

Greene, Melissa (1988) ‘Counting the Animals’, Museum News, 66 (6): 29-30. Heller, Jack (1968) ‘The Values of a Computerized Data Bank as an Adjunct to a Card Catalogue’, in

Computers and Their Potential Applications in Museums, pp. 307-322. New York: Arno Press. Honan, William H. (1988) ‘The Museum of the Future: It’s All in the Chips’. New York Times, 27

November: 2-l and 2-9. Hoving, Thomas P. F. (1968) ‘Museums, Computers, and the Future’, in Computers and Their Potential

Applications in Museums, pp. v-xii. New York: Arno Press. ‘Integrated Museum Databases and Office Automation’, (1987) International Journal of Museum

Management and Curatorship, 3: 115-120. Light, Richard (1982) ‘Today’s Microcomputers for Museum Documentation?’ Museums Journal, 82:

77-78. Light, Richard, Roberts, D. Andrew and Stewart, Jennifer D., (eds) (1986) Museum Documentation

Systems: Developments and Applications. London: Butterworths. Lindsay, Kenneth C. (1968) ‘Computer Input Form for Art Works: Problems and Possibilities’, in

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of ~nfo~a~ion Science and Technology f, Volume 19, pp. 271-309. White Plains, New York: Knowledge Industry Publications.

Miles, Roger S. (1987) ‘Museum Audiences’, International Journal of Museum Management and Curatorship, 3: 73-80.

Moffett, Jonathan (1988) ‘Computing in the Ashmolean Museum, Oxford, England’, Museum Computer Network Annual Conference.

‘Museum Automation: Defining the Need’, (1988) A round table with Rosanne McCaffrey, David Bearman, Jane Sledge, Peter Homulos, Lenore Sarasan and Paul Perrot, Museum News, 66 (6): 42-48.

82 Automated Documentation

Orna, Elizabeth (1982) ‘Information Management in Museums: There’s More To It Than Documentation and Computers’, Museums Journal, 82: 80-83.

Paisley, William J. (1968) ‘The Museum Computer and the Analysis of Artistic Content’, in Computers and Their Potential Applications in Museums, pp. 195-216. New York: Arno Press.

Peters, Susanne (1987) ‘An International Museum Documentation Network: Idle Dream or Realizable Idea?‘, International Journal of Museum Management and Curatorship, 6: 399-402.

Raben, Joseph and Burton, Sarah K. (1981) ‘Information Systems and Services in the Arts and Humanities’, in M. E. Williams (ed.) Annual Review of Information Science and Technology, Volume 16, pp. 247-266. White Plains, New York: Knowledge Industry Publications.

Ricciardelli, Alex F. (1968) ‘Inventorying Ethnological Collections in Museums’, in Computers and Their Potential Applications in Museums, pp. 81-91. New York: Arno Press.

Roberts, D. Andrew and Light, Richard B. (1980) ‘Progress in Documentation: Museum Documentation’, Journal of Documentation, 36: 42-84.

Rush, Carol E. and Chenhall, Robert G. (1979) ‘Computers and Registration: Principles of Information Management’, in Dorothy H. Dudley and Irma Bezold Wilkinson (eds) Museum Registration Methods, 3rd ed. Revised, pp. 319-334. Washington DC: American Association of Museums.

Samuel, Evelyn K. (1988) ‘Documenting Our Heritage’, Library Trends, 37: 142-154. Sarasan, Lenore (1981) ‘Why Computer Projects Fail’, Museum News, 59 (4): 40-49. Sarasan, Lenore (1987) ‘What to Look for in an Automated Collections Management System’, Museum

Studies Journal, 3: 82-93. Sarasan, Lenore (1988) ‘Standards: How Do We Get There from Here?‘, Museum News, 66 (6): 36. Schoener, Allon (1968) ‘The Electronic Museum and Information Distribution’, in Computers and

Their Potential Applications in Museums, pp. 359-366. New York: Arno Press. Stam, Deirdre (1987a) ‘Choosing Our Words: Reflections on Authority Control in Art Information

Systems’, in K. Muller (ed.) Authority Control Symposium, Occasional Papers No. 6, pp. 55-67. Tucson, AZ: Art Libraries Society of North America.

Stam, Deirdre (1987b) ‘Factors Affecting Authority Work in Art Historical Information Systems: A Report of Findings from a Study Undertaken for the Comite International d’Histoire de 1’Art (CIHA) Project: Thesaurus Artis Universalis (TAU)‘, Visual Resources, 4: 25-49.

Stam, Deirdre (1988) ‘A Quest for a Code, or a Brief History of the Computerized Cataloguing of Art Objects’, given at the Rare Books and Manuscripts Preconference of the Association of College and Research Libraries, New Orleans, 6 July. To be published in Art Documentation 8(l), Spring 1989.

Sullivan, Mary L. (1988) ‘From Systems Model to the Marketplace: The Virginia Museum of Fine Arts Systems Planning Project’, Museum Computer Network Annual Conference.

Thompson, Barbara (1987) ‘Resources’, Museum Studies Journal, 3: 94-110. Turner, Judith Axler (1988) ‘Museum Computerization: The Evolution Has Begun’, Museum News, 66

(6): 22-28. Vance, David (1979) ‘Computers and Registration: a Definition of Terms’, in Dorothy H. Dudley and

Irma Bezold Wilkinson, (eds.) Museum Registration Methods, 3rd ed. rev., pp. 311-318. Washington DC: American Association of Museums.

Vance, David (1988a) ‘Computer Notes: The Relational Paradox’. International Journal of Museum Management and Curatorship, 7: 67-69.

Vance, David (1988b) ‘Computer Notes: Eternal Truth’, InternationalJournal of Museum Management and Curatorship, 7: 189-190.

Vance, David (1988~) ‘Computers I: Codes’, International Journal of Museum Management and Curatorship, 7: 287-288.

Varveris, Therese (1979) ‘Computers and Registration: Practical Applications’, in Dorothy H. Dudley and Irma Bezold Wilkinson (eds) Museum Registration Methods, h-d ed. rev., pp. 340-354. Washington DC: American Association of Museums.

Vulpe, Michel (1986) ‘Collections Management Action Support System-CMASS: Statement of the Problem’, International Journal of Museum Management and Curatorship, Is: 349-356.

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Bibliographic Appendix Some Sources on Injbrmation Resources Management (IRM)

While the usual context of IRM is in organizations intended for profit, the following list is useful for non-profit organizations as well. These sources provide some theoretical foundations and practical

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advice and methods for information management. Topics include the identification and examination of information needs, patterns and automation.

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