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DL94: The University of Michigan Digital Library: This Is Not Your Father's Library
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<h1>
The University of Michigan Digital Library: This Is Not Your Father's Library
</h1>
<p>
William P. Birmingham[1], 
Karen M. Drabenstott[2],
Carolyn O. Frost[2],
Amy J. Warner[2],
and Katherine Willis[2]<p>

[1] <em>Advanced Technology Laboratory, College of Engineering, University of Michigan, Ann Arbor, MI 48109-2110, wpb@eecs.umich.edu</em><p>

[2] <em>School of Information and Library Studies, 550 East
University Avenue, Ann Arbor, MI 48109-1092 USA, {karen.drabenstott,
carolyn.frost, amy.warner, kathy.willis}@umich.edu</em><p>
<p>
<p>
<p>
</i><b><p>
Abstract</b><p>
This paper uses the term "digital library" as a generic name for dynamic,
federated structures that provide intellectual and physical access to the
growing world-wide networks of information encoded in multimedia digital
formats and examines research toward the broad goal of personalized harvesting
in the information wilderness organized around agency-based architecture.
Beginning from the perspective of the desktop, the researchers will explore the
creation and evaluation of an architecture consisting of user interface agents,
query processing agents, mediators, ontologies, and collection interface
agents.<p>
Although much of the research will be generic with respect to the information
subject area, the testbed will focus on the subject domain of earth and space
science. User communities for the testbed will include expert researchers,
graduate, undergraduate, and high school students, and the general public. The
research team will build a microcosm of content levels and media types,
including page images, structured documents (SGML), interactive, compound
documents and real-time interaction with real-time scientific data. Economic
and intellectual property issues will also be considered in the design.
Evaluation will be featured on a continuing basis.<p>
<b><p>
Keywords</b>: Agent architectures, Distributed systems, Information retrieval,
Search algorithms<b><p>
<p>
<p>
<p>
1.  Project Overview</b><p>
A multi-disciplinary team at the University of Michigan proposes coordinated
research and development to gain insight into the creation, operation, and use
of large scale, continually evolving digital libraries (see Figure 1). We use
the term "digital libraries" as the generic name for federated structures that
provide humans both intellectual and physical access to the huge and growing
worldwide networks of information encoded in multimedia digital formats.<p>
The fundamental mission and centuries-old tradition of libraries and the
library profession has been to provide intellectual and physical access to and
preservation of the human record. Although this fundamental mission will
continue to be vitally important, the manner in which libraries fulfill it is
being radically altered by the sudden change in the physical basis (electronic,
optical, magnetic) for information representation [3]. This shift to
"de-massified" representation will alter the structure and process by which
humans create, find, use and re-use the information they need and want. In
particular, the digital library has the potential to:<p>
<p>
*	Provide information any time and any place,<p>
*	Provide access to collections of multimedia information built upon the
integration of text, image, graphics, audio, video (and other continuous
media),<b></b><p>
*	Support user-friendly personalization/ customization of information access
and representation, including support for "harvesting" relevant information and
protection from information overload,<p>
*	Be the heart of new technology-mediated structures to radically enhance
collaborative intellectual activities such as research, learning, and design by
reducing barriers of distance (geographic and organizational) and time.<a
href="#fn0">[1]</a>
<p>
<img src="figures/umdl1.gif">
<p>
<i>Figure 1. Constituent Competencies for the UMDL Research Project</i><p>
The realization of these potentials requires fundamental research and
development of user-centered pilot projects to address a complex array of
technical and socioeconomic issues. We have brought together a unique team,
with demonstrated competence in the broad areas of research, system building,
and end-user service necessary to do this. Team participants are faculty,
research staff and students from the Department of Electrical and Computer
Engineering, the School of Information and Library Studies, the Department of
Atmospheric, Ocean and Space Sciences, the University Libraries, the
Computer-Aided Engineering Network, the Information Technology Division, Ann
Arbor Public Schools and Library, the New York Public Library and Stuyvesant
Science High School, Bellcore, McGraw-Hill, UMI, Elsevier, Encyclopedia
Britannica, IBM, Apple, and Kodak.<p>
Although we will build a complete system, we will focus on two primary areas:
(1) at the front-end, we will offer users customized (adaptive) query and
viewer facilities to support intellectual access to information, and (2) at the
back-end, we will explore approaches to rapid federation of diverse information
resources into the digital library. These functions will be brought together in
an agent-based architecture, connecting front-end, back-end, and intermediate
services, such as search, retrieval, and document structuring facilities.<p>
We intend to build an experimental system -- the University of Michigan Digital
Library (UMDL) -- as the basis for operational digital-library systems. We have
obtained significant collections and vendor support for this project. In
addition to relevant research and system-building competency, we possess two
other strengths. First, we have strong bonds between the computer-science and
information-technology communities and the information and library science
academic community. The latter includes various types of libraries (academic,
public, school, special) and several publishers. Second, we have the
opportunity to link this project with support from the Kellogg Foundation. This
linkage will enable us to radically broaden and revise the curriculum in
information and library science/studies (ILS) schools to produce the leadership
that will design, develop, promote, and manage digital libraries.<b><p>
<p>
2.  System Architecture<p>
<p>
2.1.  Introduction</b><p>
The purpose of this paper is to overview the research component of the UMDL. In
pursuing our research, we will be guided by the practical context in which the
library is to be developed and deployed. In particular, we will address issues
arising from the diversity of user groups, computational environments, and
information collections comprising the UMDL. Characteristics of digital
libraries posing special challenges include:<p>
<p>
*	Variance in user needs and sophistication,<p>
*	Diversity in hardware performance,<p>
*	Large, both in size and number, information resources that are physically
distributed,<p>
*	Heterogeneous types of information resources created by a variety of
groups,<p>
*	Multimedia data types,<p>
*	The need for extensibility to add new collections (e.g., a new database
system) as well as new data types (e.g., voice).<p>
<p>
A major challenge of digital libraries is avoiding <i>information overload</i>.
The ever-growing availability of data can reduce the amount of effective
information that users can retrieve from the system in an acceptable amount of
time and with reasonable ease. Our goal is to enable users truly to profit from
the amount of available information by providing them with tools that simplify
the retrieval of meaningful information from this mountain of data.<p>
Several ramifications of these challenges will influence the UMDL's design:<p>
<p>
*	The UMDL will be organized as a distributed system. Information resources
will be managed by computational agents. The network will include agents that
perform on behalf of users (e.g., processing search requests), information
sources (e.g., multicasting their contents), or the network itself (e.g.,
reorganizing ephemeral communication links among agents).<p>
*	The network must be flexible enough to allow information resources to be
placed on or taken off the network without adversely affecting the network. (We
envision literally millions of information resources eventually on the
network.) We will achieve this by enforcing communication protocols among
agents in the network for the <i>dynamic construction </i> of processing
strategies, rather than supporting hard-coded connections. This will allow
individual information sources and user interfaces to be engineered by local
groups as they see fit.<p>
*	The vastness of the amount of information on the network can render
undirected searching impossible. To ensure an efficient search, we must develop
intelligent, well-informed search strategies customized to the true needs of
the user, and we must also exploit the <i>structure</i> of information on the
network. The latter must include two categories of structure. First,
hierarchical, bibliographic structures must be imposed on the collections of
the information sources to indicate which ones may have the information being
sought. Second, individual information sources themselves must be structured to
facilitate an efficient local search.<p>
*	As the network agents are autonomous, they will need to make decisions about
whether to participate in a search, whether to return information being sought,
and so forth. It is critical that these agents base their decisions on some
metric of value that considers both the public good and incentives for
individual participation. Such <i>economic</i> models of decision-making will
be used to coordinate activity in the network.<p>
*	The information sources will contain intellectual property, therefore the
network must provide mechanisms to both protect this property (from
unauthorized copying, for example) and to collect fees for its usage.<p>
*	As the size of the network grows, it will be difficult to enforce standards
of information source architectures. Therefore, we must standardize
communication <i>protocols</i>, and not the architecture of information
sources.<p>
<p>
Our system architecture, described in the remainder of this section, will be
designed primarily to afford flexibility in addressing the diversity of
requirements and resources described above. Our broad goal is to develop a new
paradigm for integration of autonomous, disparate systems that is truly
distributed, yet performs seamlessly. A major challenge is to share information
across the UMDL, while maintaining the autonomy of individual collections. In
particular, consider that individual information-source providers (third
parties to those developing and maintaining the digital library), working
without interaction from other providers, need to be able to place their
information resources in the network without requiring them to necessarily
understand details of the overall library system. The same will apply to third
parties producing user interfaces.<b><p>
<p>
2.2.  Agent-Based Architecture</b><p>
UMDL will be organized as a distributed system consisting of information
sources, user interfaces, and sets of processing agents. Most of the actual
services required from the digital library system will thus be performed by
these information agents. In general terms, these services are concerned with
translating a query or some other expression of a user's need into a delivery
of information meeting that need. More specifically, we can classify the
information agents in our system as responsible for the following tasks:<p>
*	Processing user queries and displaying retrieved information,<p>
*	Searching, filtering, and summarizing large volumes of data,<p>
*	Translating or passing on search requests to databases or other agents,<p>
*	Maintaining metadata about a particular data repository,<p>
*	Monitoring usage patterns and information changes to initiate reorganization
of data and notification of users.<p>
<p>
Figure 2 illustrates, at a very high level, the UM Digital Library, linking
several users through their User-Interface (UI) agents to collections through
Collection-Interface (CI) agents. In a simplistic system, the UI agents and CI
agents could be networked together, allowing UI agents to query collections
directly, either sequentially or in parallel. There are many problems with this
simple solution, such as the duplication of effort in having UI agents
determine the subset of CI agents needed to service a particular request, or
the complexities of terminating the search once a CI agent has successfully
answered a user query.<p>
<p>
<img src="figures/umdl2.gif">
<p>
<i>Figure 2. A federated agent architecture</i><p>
Embedding specialized information agents (besides the UI and CI agents) into
the architecture to act as mediators between users and collections can
alleviate these problems, and provide additional useful services to library
users and contributors of information to the library. Different types of
mediating agents for finding, processing, and delivering information are
distinguished by their specific knowledge and expertise. Some examples of
potential agent capabilities include:<p>
<p>
*	Understanding general requirements, as well as particular requests, of
users,<p>
*	Executing effective search strategies over the network,<p>
*	Possessing effective strategies for processing  searches over the network,<p>
*	Summarizing and displaying information in various ways,<p>
*	Understanding the contents and organization of particular collections,<p>
*	Understanding the relations among collections, data formats, etc.,<p>
*	Understanding the availability, capabilities and usage of network
resources,<p>
*	Gathering usage patterns of particular users or user groups,<p>
*	Possessing alternative methods for summarizing and displaying information,<p>
*	Understanding capabilities and effectiveness of other agents,<p>
*	Understanding the particular domains of inquiry.<p>
<p>
The knowledge and computational resources available to particular information
agents dictate the range of <i>information services</i>  they can provide to
users or other agents. Each individual service offered by an information agent
is a building block for constructing complex information-processing strategies.
Combinations of cooperative agents can collectively implement the more complex
tasks required of the digital-library system, such as information-storage
(e.g., caching and indexing schemes), access-plan strategies  (e.g., browsing
options and traversal paths), and so on. Realizing the benefits of populating
the digital library architecture with a community of diverse information agents
will require the agents to team dynamically to provide a particular information
service on demand

[4]. In the following sections, we describe a representative set of agents that
comprise the digital library and the general mechanisms for coordination and
communication that we will employ.<b><p>
<p>
3.  Agents<p>
<p>
3.1. Introduction</b><p>
Our development of a comprehensive agent-based architecture will focus on the
construction of particular agents and protocols:<p>
<p>
1.	<i>User-interface agents</i>  for both on-demand and continuous modes of
operation, including an interviewing agent to help lead digital library users
to the best information for their needs regardless of the type or genre of the
resource.<p>
2.	Supporting <i>query-processing agents</i>, incorporating linguistic
retrieval, and providing information integration.<p>
3.	<i>Mediators</i>  to support the interactions between users and collections
to assist in fulfilling queries, organizing information, and allocating
resources to satisfy a community of scholars. <i>Economic coordination
mechanisms</i> will provide a framework for dynamically allocating resources
across information-processing activities.<p>
4.	<i>Ontologies</i> <i>and protocols</i> to federate any collection of
independently generated information sources in a common language for describing
contents without detailed information about access mechanisms, organization, or
any other implementation-specific issues.<p>
5.	<i>Collection-interface agents</i> maintaining the links between autonomous
data repositories and the rest of the system.<b> </b>These agents will
translate query requests, map between data types and formats, resolve schema
inconsistencies, etc.<b><p>
<p>
3.2.  User-interface Agents</b><p>
The UMDL's user interface agents will provide search strategies to the user
accessing UMDL. As an example, we will develop a class of user-interface
agents, called an Interviewing Agent (IA), that strives to lead digital library
users to the best information for their needs regardless of the type or genre
of the resource. It will also serve as a helpful companion that users can call
on for guidance and instruction during their navigation through the federated
network or examination of digital resources.<p>
The IA will model the described behavior of information seekers (e.g., high
school, undergraduate, graduate researchers) according to definable
characteristics and styles, as well as discipline-based methodologies. We plan
to interview and study this broad base of users to design the required search
strategies. The IA will query users about various parameters of their search,
(e.g., intended use, time constraints, familiarity with their topics), and pass
this information on to the agents it deems appropriate for further
processing.<b><p>
<p>
3.3. Query-Processing Agents</b><p>
The development of query paradigms that allow users to retrieve the desired
material with ease by processing complex requests in this distributed
environment is a key research problem. Traditionally, query-optimization
techniques determine a fixed execution strategy for a query by evaluating and
comparing all information given in the metadata, e.g., availability of indices,
size of data sets, etc. In the UMDL this will become a much harder problem
because the query optimizer will have to make decisions with incomplete
information (e.g., without studying all possible metadata servers). More
importantly, the query processor will have to incrementally adjust the query
execution plan depending on hit ratios, quality of partial results, etc. In the
UMDL, this sort of information will be distributed among those agents expert in
the various repositories and access techniques, the so-called metadata agents.
We will develop strategies to control the parallel spawning of query requests
to different metadata servers.<p>
Much of the information in the digital library will consist of documents and
representations in natural and controlled language. Problems with this include
not only the intrinsic problems posed by language used in a given database, but
also by both the quantity and heterogeneity of the information that will be
searched and integrated across multiple collections. The identification and
construction of linguistic techniques builds upon prior research in
manipulating the surface structure of documents and queries to build linguistic
capabilities into an information-retrieval system [10, 11, 12]. These methods
make use of the existing surface structure found in documents and queries, as
well as the structure and content available in already existing controlled
vocabularies. In terms of the overall system architecture, query agents will
make use of linguistic techniques to filter and refine large sets of
documents.<b><p>
<p>
3.4. Mediators</b><p>
The purpose of mediators is to support the interactions between users and
collections to assist in fulfilling queries, organizing information, and
allocating resources to satisfy a community of users. For example, mediators in
the network will keep track of published material, maintaining a directory of
information sources (e.g., metadata) as they dynamically evolve, and supplying
information about sources to help. Typically, there will be many such
mediators, hierarchically arranged and with redundant knowledge, to avoid the
contention and single-point-of-failure pitfalls of centralized directory
services. These hierarchies must dynamically reconfigure themselves as hosts
and links fail and as the load on them changes.<p>
Interactions among mediators will resemble a cooperative problem-solving effort
among a diverse set of specialists [5],
where the problems to be solved, the expertise of the specialists, and the
population of specialists can all change over time. To provide this
functionality, we will draw on a variety of techniques for distributed problem
solving, organizational self design, coordination theory, and distributed
artificial intelligence [2]. For example, the process of query decomposition,
subquery allocation, and result synthesis can be cast as a contracting
arrangement among query processors [9]. Implementation of such techniques in
the digital library, however, poses an exciting research challenge because of
its dynamic nature. For example, decisions about how best to decompose queries
must be based on what collections are likely to be available to respond to
queries. Consequently, the decomposition process itself may require
communication among mediators to first determine reasonable decompositions,
followed up by further communication to then allocate subqueries and collect
results.<p>
Directing the activities of mediators is essentially a problem of resource
allocation. The alternative information services offered by mediators are
competing economic activities. Information agents dynamically connect with each
other as opportunities arise for mutually beneficial exchanges. The collections
provide the ultimate "raw materials" in this process, whereas the end users are
the ultimate consumers of the "finished goods." The mediator agents bridge the
gap by bringing to bear knowledge, processing, storage, or other computational
resources to improve in some way the expected value of the information as it
passes along the chain from agent to agent. Our implementation of virtual
markets in information services will be based on the idea of "smart auctions"
proposed for smooth allocation of bandwidth on the Internet [7]. The mechanisms
for managing multiple, interacting markets will be based on our previously
developed "market-oriented programming" system [13].<b><p>
<p>
3.5. Ontologies and Protocols</b><p>
Central to federating any collection of independently-generated information
sources, or databases, is a common language for describing contents without
detailed information about access mechanisms, organization, or any other
implementation-specific issues. The description of the content, in a sense, is
a declaration of <i>what is</i>; this is commonly called an ontology. The
ontology, because it must be communicated, is described in some (semi) formal
language, facilitating concise and thorough statement of the contents [6, 8].<p>
The <i>ontological</i>  approach, therefore, concentrates on defining the
following:<p>
<p>
*	<i>Content-description language</i>: The terms and data must be precisely
described in a commonly accepted definition: this is the ontology. The ontology
is similar to a data dictionary in database systems, except that it describes
the meaning of terms in general, not their representation within this
particular DBMS.<p>
*	<i>Interchange protocols</i>: As an ontology is a description of what exists
in a domain or database, it does not perform any actions <i>per se</i>. Rather,
actions occur through protocols. The protocols we will develop as part of UMDL
will have the same philosophical basis as ontologies: they will describe
services without specifying how they are to be done. Furthermore, these
protocols will operate on top of network protocols that describe how to move
bits through wires (e.g., TCP/IP) or how to form and interpret blocks of data
(e.g.,<i> </i>Z39.50).<u><p>
</u><p>
Interchange protocols will define the full range of activities that can be
performed in the UMDL and will apply primarily to mediators and collection
agents. By insulating information sources and interfaces from the details of
the operation of the network, they are easier to construct and to maintain.
Furthermore, we can control their actions, adding security to the
network.<u></u><b><p>
<p>
3.6.  Collection-interface Agents</b><p>
In our distributed-agent paradigm, queries will eventually be submitted to
local information repositories to execute elementary requests on the actual
information sources. In order for an information source to participate
effectively  in the network, it will be assigned a dedicated Collection
Interface (CI) agent, responsible for maintaining a link between the repository
and the rest of the system. These agents will be capable of translating query
requests, mapping between data types and formats, resolving schema
inconsistencies, etc. Collection types to be explored include page images,
structured documents (SGML), general image collections, and some audio and
video.<p>
We focus here on two particular capabilities that CI agents will possess in a
digital library. The first capability is to use knowledge supplied by document
and domain specialists about the structure of the documents or other
information sources, or both, to characterize formats and contents to support
queries and browsing. In general, this amounts to expertly guided structuring
and organization of the documents and other information resources. The second
capability is a more dynamic structuring activity, based on usage patterns,
into (possibly transient) virtual collections.<p>
One important task will be to organize image and text data so content in
different collections and formats can be intelligently located, quickly
retrieved, and easily reused in unanticipated and arbitrary ways. For large,
complex collections, conventional retrieval terms will need to be supplemented
by some form of knowledge representation, which will be used to segment the
search space so agents need apply brute force techniques only in areas where
probability of success is high [1].<p>
One simple way of capturing knowledge representation in a digital-library
collection will be to associate abstracts and reviews of works with items,
separated from content. In addition to information about structure that the
information source will provide to its CI agent, we must also investigate what
metadata each source should make available, as well as which modeling
techniques should best be used to describe this metadata. Metadata will include
a description of the content of the database (schema), available index
strategies and access methods, the integrity mechanisms enforced, and other
information for administrative purposes. A metadata agent will then be in
charge of posting a comprehensive description of the collection to the digital
library system, representing a wrapper between the local information source and
the rest of the system.<b><p>
<p>
3.7.  Design and Construction of a Testbed</b><p>
UMDL will be focused and grounded by the goal to design, construct, deploy, and
evaluate a testbed. Although much of the research will be generic with respect
to the information subject area, our testbed will focus on the subject domain
of earth and space science (ESS). The choice of ESS was motivated by the
following considerations: (1) significant expertise and level of activity in
this area at the University (Atmospheric, Oceanic, and Space Sciences, and
university-wide global change and environmental studies activity); (2)
availability of rich, multimedia special collections (real-time and archival)
on campus and through government sources (e.g. NASA) sites; (3) the broad,
general appeal of this area and its fit to existing research activities in
learner-centered high school science education; and (4) linkage with the Upper
Atmospheric Research Collaboratory Project (UARC).<p>
As part of this proposal, the University of Michigan plans a comprehensive
deployment activity on- and off-campus. Partnerships have been established with
publishers and users that will allow us to undertake testing and evaluation of
the research proposed under realistic user conditions with a large,
representative collection. The fact that we have these relationships
established, combined with the existing development of an image-based
digital-library system (DIRECT) already in place at the University, will allow
us to begin initial deployment of the testbed immediately.<p>
We will start deployment of the testbed with a significant advantage: a small
software-development project at Michigan, DIRECT (Desktop Information Resources
and Collaboration Technology), has produced a prototype digital-library system
for image-based documents. Funding for DIRECT has come from Digital Equipment
Corporation and internal University funds. The initial deployment of DIRECT has
been undertaken with a journal set provided by Elsevier Science Publishers
under its TULIP (the University Licensing Program) initiative.<b> <p>
<p>
4.  Deployment, Use and Evaluation</b><p>
Testbed users will include expert researchers, graduate, undergraduate, and
high school students, and the general public. We will build a microcosm of
content levels and media types ranging from page images to interactive,
compound documents and real-time interaction with real-time scientific data,
replays of its collaborative sessions, and human expertise. We will also
address issues about how users add content to the UMDL.<p>
Usage will be monitored both for any billing needs and anonymously for usage
studies and research. Usage statistics will be fed back to the developers and
user-studies groups, who will in turn suggest changes, improvements, and new
features for UMDL, which, in turn, will require further testing. By using this
iterative process throughout the project, UMDL will evolve to both incorporate
new research results and to meet the changing needs of the user community.<p>
The UMDL will enable students to explore questions in ways that would be
exceedingly difficult, if not impossible, with current resources. For example,
students will have access to the same data as the researchers, as well as some
access to the scientists themselves. No longer must students rely on minimalist
summaries in outdated textbooks. Taken together, the UMDL will provide an
information infrastructure that should enable students to develop inquiries
into timely, proactive, and authentic -- and hence, motivating -- scientific
questions.<p>
Critical to the exploitation of these resources will be ongoing programs of
training, user assistance, and outreach to promote use of the digital library.
Closely associated with user support will be the ongoing development of the
collection of information resources through continued partnerships with
information providers, including commercial, governmental, or academic sources.
User-support structures envisioned for this project will bring together these
themes of technical assistance, user skill development, and responsiveness to
user needs both in terms of tapping existing information resources and the
development of future resources.<b><p>
<p>
5.  Summary</b><p>
The primary characteristics of a digital library are that it should provide
physical and intellectual access to a highly distributed, heterogeneous
collection of information resources. Access should be independent of time and
distance, and should be flexible and personalized to the individual.
Ultimately, it should facilitate new, collaborative ways of learning, gathering
information, and doing research. The University of Michigan Digital Library
Project is investigating methods of achieving these goals through a
distributed, federated architecture, using agents that embody knowledge about
collections, users, and query processing methods, as well as mediation
procedures to coordinate interactions among them. Our goal is to efficiently
guide the user's search toward the best available resources, and avoid the
problem of overwhelming the user with too much information. We will pursue this
goal in the context of an operational system, continuously evaluated with real
users.<p>
In order to carry out this research program, the University of Michigan has
assembled a large, multi-disciplinary research team consisting of software
engineers, computer and information scientists, economists, librarians, subject
specialists, and corporate and academic sponsors. We believe that this approach
will enable us to tackle key problems -- technical, organizational and economic
-- of the digital library.<b><p>
<p>
<p>
Acknowledgments</b><p>
Members of the UMDL Project Team are: Ken Alexander, James E. Alloway, Daniel
E. Atkins, William P. Birmingham, David C. Blair, Colin Day, Karen M.
Drabenstott, Edmund H. Durfee, Joan C. Durrance, Randall L.  Frank, Carolyn O.
Frost, Kathleen Garland, Joseph W. Janes, Michael E. Lesk, Wendy P. Lougee,
Gregory R. Peters, David L. Rodgers, Elke A. Rundensteiner, Elliot Soloway, Hal
R.Varian, Amy J. Warner, Michael P. Wellman, and Katherine P. Willis.<b><p>
<p>
<p>
References</b><p>
[1]	Blair, D. C. 1990. <i>Language Representation in Information Retrieval</i>.
Amsterdam: Elsevier Science Publishers.<p>
<p>
[2]	Bond, A. H., and Gasser, L. 1988. <i>Readings in Distributed Artificial
Intelligence</i>. Morgan Kaufmann Publishers, San Mateo, CA.<p>
<p>
[3]	Drabenstott, K. M. 1994. <i>Analytical Review of the Library of the
Future</i>. Council on Library Resources, Washington, DC.<p>
<p>
[4]	Darr, T. P., and Birmingham, W. P. 1993. <i>Automated Design for Concurrent
Engineering</i>  University of Michigan, Technical Report No. CSE-TR-174-93,
Ann Arbor, MI.<p>
<p>
[5]	Durfee, E. H., Lesser, V. R., and Corkill, D. D.. 1989. Coordination of
Distributed Problem Solvers. In <i>Handbook of Artificial Intelligence</i>, A.
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83-137.<p>
<p>
[6]	Gruber, T. R. 1993. A Translation Approach to Portable Ontology
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<hr>
<a name="fn0">[1]</a>The digital library, appropriately generalized, is
strongly related to the concept of a "collaboratory." As part of a
collaboratory, the digital library supports the usual library functions of
informing and diffusing intellectual work. In addition, however, it offers the
potential for capturing not only the end products of intellectual work, but
also the process and rationale, both formal and informal, by which they are
created. <p>

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