D-Lib Magazine, June 1996
A full-fledged, end-to-end digital library project must include a target collection whose contents are to be preserved and maintained over time, a user test bed, intermediaries that help determine the layout and organization of the materials, and finally technologies to support these activities. PARC is participating as an industrial partner in several of the NSF/DARPA/NASA-sponsored digital library projects, working most closely with those of Stanford and UC Berkeley. These projects provide an opportunity for the exploration and demonstration of how support technologies can be used in the digital library context.
This article presents a sample of PARC digital library technologies and
introduces a new PARC project,
Much of the technical research at PARC centers around the interface between paper and electronic documents. Since its invention thousands of years ago, paper has served as one of our primary communications media. Its inherent physical properties make it easy to use, transport, and store, and cheap to manufacture. However, much research is still needed for building bridges between paper and the digital world. The final report for a recent digital library workshop [Lynch and Garcia-Molina] begins by noting that ``Digital libraries will, for the foreseeable future need to span both print and digital materials.''
The problem of capturing and converting scanned paper materials has received considerable attention at PARC, from a number of perspectives. We will illustrate the range of activities with three examples:
and the corresponding SQL code for a relational database entry:
INSERT INTO dams (
dam_name,dwr_num,owner,county,
stream,loc_section,loc_township,loc_range,loc_base_mer,
national_id,dam_type,stor_capacity,drainage_area,reserv_area,
parapet_code,parapet_ht,crest_elev,crest_len,height,
total_frbd,oper_frbd,crest_width,volume,year_comp,
lat,long
)
VALUES
('FOLSOM','9000-148','U S BUREAU OF RECLAMATION',
'SACRAMENTO','AMERICAN RIVER',24,'10N','7E','MD',
'CA10148','GRAV',(1010000,1245834),(1885.0,4882.15),
(11450,4634),NULL,(NULL,NULL),(480.5,146.5),(26670,8129),
(275,84),(62.5,19.1),(5.1,1.6),(36,11),(13970000,10680763),
'1956-01-01',(38.0,42.5),(121.0,9.4));
It is clear that the names of the database record fields and the
representations of the fields in the image are highly specific to this
particular document. A body of information about fish species, for example
would have a completely different logical and typographic structure.
The motivation for creating the type of semantic markup illustrated above,
which goes beyond simple document structure tags such
as
The DID approach to creating document-specific tags is to support the automatic generation of custom recognizers from declarative specifications, in a manner analogous to the way LEX and YACC generate character string parsers from language grammars. The overall vision is summarized in this figure:
The input to a decoder generator is a document model that describes aspects of the document content and appearance relevant to extracting the desired information. Typical elements of this model include specifications of the language, information structure, layout, character shape and degradation processes. The decoder generator converts the model into a specialized document recognition procedure that implements maximum a posteriori (MAP) image decoding with respect to the model. In the current implementation, the specialized decoders are in-line C programs that are compiled and linked with a support library.
The DID project is actively involved
with the UC Berkeley Environmental
Digital Library Project and has been developing specialized decoders
for documents in the project testbed. These advanced structured document
examples include a table of
California Dams and descriptions of Delta Fish
Species . Additional information about the application of DID to the
digital library can be found in [Kopec].
Document Image Summarization
The Document Image Summarization (DIMSUM) activity is developing methods
for creating summaries of scanned documents without performing optical
character recognition (OCR). DIMSUM is motivated by the observation
that performing OCR is often much more computationally demanding that
preparing a summary using the recognized text,
The DIMSUM strategy is to directly extract images of sentences and phrases
that together communicate a sense of the document. To identify a set of
summarizing excerpts, word boxes are extracted from the images and then
word-box equivalence classes are formed. Based on word proximity and
statistics on word frequency within the document, a set of summarizing
excerpts is constructed. The following is an example of a five sentence summary of a three page article on
rocket engine development created using DIMSUM:
One application of DIMSUM is in generation of
single-page summary sheets that can be used later for retrieval of the
full document. Additional information can be found in [Chen and
Bloomberg].
Paper User Interface and Protofoil
The Paper User Interface and Protofoil
are two approaches to providing interfaces that
bridge the paper and digital worlds. Paper User
Interface ([Johnson et al.]), moves the
user interface beyond the workstation and onto paper itself. This
technology uses paper forms, often placed as cover sheets in
front of paper documents, to invoke electronic behavior or to control
how documents are processed during and after scanning. Because paper
forms eliminate the necessity of using a workstation interface for
many tasks, users can perform a wide range of operations remotely,
often in a manner that decouples their time from the system's
activity. For example, a user can fill out forms for processing
documents on a plane trip, fax the stack of documents (separated by
forms) to his paper server at home for storage and/or distribution to
others.
To support the exploration of the use of paper user interface, a paper infrastructure was developed that provides mechanisms for defining and managing forms, and for processing incoming streams of digital images from scanners and faxes, and for invoking document services provided in the electronic world.
The second interface for linking paper and digital documents is
Protofoil [Rao et al. 94], a system for
storing, retrieving, and manipulating scanned paper documents using an
electronic filing cabinet metaphor. Protofoil is intended to support
the filing needs of the individual information worker and has been
deployed and evaluated at a lawyer's office as part of an extensive
ethnographically-motivated design study. [See D-Lib Magazine,
May, 1996 for more information about PARC work practices research
related to digital libraries.] Protofoil allows users to store and
retrieve document images and to invoke various document services on
the stored documents. The system consists of three major components:
(i) software for scanning documents and interpreting paper user
interface forms as instructions (see below), (ii) a database for
storing and archiving the document images and associated descriptions
or auxiliary renderings, and (iii) a graphical user interface for
retrieving and manipulating stored documents. Protofoil integrates
components from a number of other PARC projects including the Text
Database (TDB) [Cutting et al. 91]
statistical content analysis engine.
Information Access and Visualization
The emergence of digital libraries promises to provide massive amounts
of diverse types of digital information. This brings to the forefront
the necessity of building new, more powerful, user workspaces for
finding and using information in this increasingly rich and varied
world.
Researchers at PARC have developed a variety of theoretical and computational tools for search over and retrieval from large collections of online documents (usually natural language texts, but increasing multimedia), as well as for helping the user understand and navigate the contents of the collections.
Some of the work in this area has recently been discussed in a digital library context in another publication [Rao et al. 95]. The discussion below focuses on a somewhat different subset of this work, and at different levels of detail. The main areas are:
If a user of an information access system issues a query that retrieves a very large number of documents, that user cannot be expected to have the time and patience to read through a large set of titles. Instead, the information access system should provide the user with tools to facilitate the assimilation of the results. One possibility is to help the user reformulate the query by suggesting alternative terms. Another possibility, explored in the examples below, is to provide tools to aid the user in the navigation of the retrieval results.
Scatter/Gather uses the metaphor of a dynamic table-of-contents to help the user navigate a large collection of documents. Initially the system uses document clustering to automatically scatter the collection into a small number of coherent document groups, and presents short summaries of the groups to the user. Based on these summaries, the user selects one or more of the groups for further study. The selected groups are gathered, or unioned, together to form a subcollection. The system then reapplies clustering to scatter the new subcollection into a new set of document groups, and these in turn are presented to the user. With each successive iteration the groups become smaller, and therefore more detailed.
The document clustering algorithm is optimized for speed, to encourage interaction, rather than to guarantee accuracy. The current system uses a linear-time clustering algorithm for ad hoc document collections and a constant-time algorithm for stable, preprocessed collections. The linear-time algorithm can organize 5000 short documents in under one minute on a SPARC20 workstation.
The cluster summaries are designed to impart general topical information. Clusters are summarized by presenting their size, a set of topical terms , and a set of typical titles. The topical terms are extracted from the document profiles , or weighted bag-of-words representations, of the documents included in the cluster and are intended to reflect the terms of greatest importance in that cluster. The typical titles are the titles of documents closest to the cluster centroid.
Here we demonstrate the use of Scatter/Gather on the TIPSTER collection of over 1 million newswire, newspaper, magazine and government articles, dating mainly from the late 1980's. We also make use of one of the TREC queries and its associated relevance judgments. For this query, the task is to find all documents that discuss the following abbreviated version of Topic 87: Criminal Actions Against Officers of Failed Financial Institutions.
We formulated a query containing the terms bank financial institution failed criminal officer indictment and instructed the system to retrieve the 500 top-ranked documents according to a standard weighting algorithm, which are then gathered into five clusters; below the resulting sizes and topical terms are shown.
Cluster 4 stands out for the purposes of the query in that it contains terms pertaining to fraud, investigation, lawyers, and courts. Since we know the system has retrieved documents that pertain to financial institutions, we can assume that the legal terms occur in the context of financial documents. It turns out that out of these 500 retrieved documents, only 21 had been judged relevant to the query by the TREC judges and 15 of these relevant documents appear in Cluster 4. The user can now select this cluster (or several clusters) and re-scatter it to see its contents in more detail, or access the documents directly by clicking on their titles. See [Hearst and Pedersen], [Cutting et al. 92b] and [Cutting et al. 93] for more for more information.
The TileBars for the most relevant looking cluster (from the results of a Scatter/Gather) are shown. The ranking reflects criteria specific to this interface: the documents are ranked first by overlap: how many segments have hits for all termsets, second by total number of hits, and third by the ranking from a similarity search. The number shown is the original similarity search ranking.
Each large rectangle indicates a document, and each square within the document represents a coherent text segment. The darker the segment, the more frequent the term (white indicates 0, black indicates 8 or more hits, the frequencies of all the terms within a term set are added together). The top row of each rectangle correspond to the hits for Term Set 1, the middle row to hits of Term Set 2, and the bottom row to hits of Term Set 3. The first column of each rectangle corresponds to the first segment of the document, the second column to the second segment, and so on.
In this example we can see at a glance that all three topics are discussed in at least one segment in the first 16 documents, but that the last four documents discussion only Xerox and research, with no discussion of business or technical transfer. We can also see the relative lengths of the documents and how strongly the three topics overlap within the documents. The score next to the title shows what a standard ranking algorithm would produce.
A version of TileBars has been implemented in Java as part of the UC Berkeley Digital Library project and can be experimented with at http://elib.cs.berkeley.edu/tilebars.html.
For example, in answer to the question What New York City borough was the setting for Saturday Night Fever? the system responds as follows:
Article: Travolta, John
Article: Brooklyn
Evidence is knitted together from noun phrases taken from two different articles. Brooklyn was suggested as the answer because it appears in conjunction with the phrase Saturday Night Fever in the Travolta article, and with borough and New York City in the Brooklyn article.
Question answering of this type should play an increasingly important
role as more and more information becomes available electronically.
The Information Visualization project has for many years
been exploring the application of interactive graphics and
animation technology to the problem of visualizing and making sense of
larger information sets. This work is based on the premise that many
complex information tasks can be simplified by offloading complex
cognitive tasks onto the human perceptual system.
The Information Visualizer (IV) [Robertson
et al.] is based on a 3D Rooms metaphor to establish a
large workspace containing multiple task areas. In addition, other
novel building blocks were developed to support a new user interface
paradigm.
The IV architecture has enabled the development of a set of animated
information visualizations for hierarchical information, including the
Cone-Tree , the Perspective Wall and the Table
Lens. The figure below shows examples of a cone-tree
and a perspective wall.
Many of these techniques use the display uniformly,
assigning a large number of pixels to a focus area, and retaining
contextual cues in less detail. These techniques allow the display of
larger number of items than could previously be put on the screen.
For example, the top 600 nodes of the Xerox organization chart could
be seen all at the same time even though it otherwise requires an
80-page paper document.
An application of IV that is of particularly relevance to digital
libraries is Butterfly , an Information Visualizer application
for collections of scholarly papers, which have rich patterns for
visualization including people, time, place, and citation
relationships [Mackinlay et al]. Butterfly
allows the user to quickly navigate citation relationships among
scholarly papers (available from DIALOG's Science Citation databases)
by interacting with virtual 3D objects representing papers and their
citation relationships. Network information often involves slow
access that conflicts with the use of highly-interactive information
visualization. Butterfly addresses this problem, integrating search,
browsing, and access management via four techniques:
There are currently three thrusts. First is the characterization
of accessible information in terms of its cost structure [Card and Pirolli]. Information retrieval can be
thought of as just the rearrangement of this cost structure. Second,
is the application of concepts from the literature of optimal foraging
theory from biology to information access. Based on cost and benefit
parameters, this allows us to understand the ecology of various
information strategies, such as direct retrieval vs automatic
dissemination [Pirolli et al.]. Third is the
development of a theory of sensemaking
[Russell et al.], which articulates the methods by which raw
information is combined to produce new information products and
insights. All three of these components are being explored in the
context of the World Wide Web and information access.
Middleware refers to software and systems architecture that helps knit
together the various pieces of a distributed information delivery
system, including information repositories, search and retrieval
tools, and client-side workspace tools such as visualizations.
Important emerging issues are the need to develop a network-oriented
object-oriented mechanism for system interoperability, and interfaces
that make use of this mechanism to expose the capabilities of the
underlying sub-systems.
PARC work in interface and middleware development for digital library
integration has focused on three components:
There are currently two primary distributed object-oriented
programming paradigms available as open standards in the commercial
market, Microsoft's Distributed Component Object Model (DCOM) and OMG's Common Object Request Broker
Architecture (CORBA). While
there are many differences between the two, and debates about their
relative merits are intense, there is no question that both are
powerful enough to serve as the infrastructure on which to build
digital library systems. The Inter-Language Unification System
(ILU) is an implementation of the CORBA standard that was
developed at PARC and is distributed freely over the Internet. (See
ftp://ftp.parc.xerox.com/pub/ilu/ilu.html.)
ILU is a multi-language object interface system designed to provide
interconnection between components of a distributed system. The object
interfaces provided by ILU hide implementation distinctions between
different languages, between different address spaces, and between
operating systems. For example, ILU allows modules
written in Common Lisp, C++, and Python to be combined.
It also automatically provides networking to interconnect parts of the
system running on different machines, thereby relieving application
programmers of the need to write networking code. Finally, it can be
used to define and document interfaces between the modules of
non-distributed and distributed programs using ILU's Interface
Specification Language. Currently several of the NSF-sponsored
Digital Library Initiative projects are making use of ILU.
Xerox joined with Novell in May 1994 to propose a standard framework
for distributed document repositories called Document Enabled
Networking (DEN). This
standard was both competitive and complementary with the standard
proposed by the Shamrock Document Management Coalition, so in April
1995 they were merged to produce the Document Management Alliance
(DMA), a standards group
under the auspices of the Association for Information and Image
Management (AIIM). The proposed DMA
standard specifies an object system and interfaces for
repository-based document management, including storage and retrieval
of documents of various types, version management services, catalog
information and search services, and integration of services over
multiple repositories. All objects in DMA are self-describing using
mechanisms built into the standard.
The DMA standard is currently in draft form, with a version 1 release
expected by third quarter of 1996. PARC and other Xerox
researchers are actively involved with DMA standards and development
activities. In particular, the 1996 AIIM trade show in Chicago
featured a demonstration of DMA-based interoperability between a
number of client and repository systems, one of which was developed by
Xerox researchers in Webster, New York. In addition, Xerox research
in El Segundo, California, has been involved in porting the XSoft DMA
middleware (available free to DMA members) from Win32 to Unix, and is
currently working on extending the middleware to support distributed
repositories.
A DMA-related effort at PARC is the Metro research project,
which provides ILU-based interfaces and middleware that allow the
integration of multiple search services over DMA-style repositories.
The integrated services may provide quite different analyses of the
underlying repository documents (e.g., image vs. text retrieval);
Metro allows each of the services to be developed independently and
then integrates their operation and search interfaces.
The Metro implementation
allows for arbitrary distribution of the service and repository system
elements, as well as for optimizations in cases where they are
co-resident. In future, Metro functionality is intended to include
query persistence (result set updates as repository contents change).
Currently when books are published, a large number of them are printed
all at once and distributed to bookstores and other merchants, with
the remainder stored in warehouses. If publishers greatly
overestimate the number of books desired they must absorb the expense
of unsold books. On the other hand, print runs using standard
printing equipment are expensive unless done in bulk.
The UPrint1 project is exploring whether it is practical to
print books one at a time, at the time the customer wishes to purchase
them [Bruce et al.]. (This assumes that the
trend toward digitizing printed material will not make books obsolete,
but rather will make bookstores obsolete. Printed books will
stay around because paper has high contrast and resolution and books
don't require batteries or power cords.) This may be more practical
today than in the past due to the recent availability of high-end,
high-volume publishing systems such as the Xerox DocuTech Network
Publisher. If this effort does prove to be practical, it may
dramatically change the book publishing industry. For instance, books
would not need to go out-of-print, and could be customized when
printed to have large type, use a special kind of paper, and so on.
As another example, small-run, specialized books, such as academic
monographs, should become less expensive to produce.
The UPrint1 project makes use of an online, or virtual, bookstore.
After making a selection at the virtual bookstore, one copy is printed
for the customer, either at home if an appropriate printing device is
available, or at a print shop.
Some advantages of a virtual over a physical bookstore are: it's
contents are searchable, browsing can be done in multiple ways instead
of the static shelf arrangement of a physical bookstore, a larger
selection of books can be available, the bookstore is accessible
anytime from anywhere, and it can provide auto-recommendation from an
appropriate community of experts. On the other hand, a physical
bookstore provides a place for people to meet and talk, allows for the
reading and browsing of physical copies of the books, and often has a
coffee shop next door.
A virtual bookstore without a UPrint1 service is no different from
existing web bookstores in which users find what they want and
publishers fill their orders from a warehouse and ship the physical
books. Thus books that are out of print, or that are temporarily sold
out are unavailable without a mechanism like UPrint1. Futhermore,
UPrint1 avoid the lag time between ordering and receipt of the book.
There are many aspects to making UPrint1 a reality. Currently the
project is focusing on the question of how to entice people to visit
an online or virtual bookstore that has no physical books. One idea
is to give the visitor to a virtual bookstore a recommendation service
they can't get at a physical bookstore. As a sample scenario, imagine
you visit the bookstore and search for books on the Java programming
language. You will get many hits: how do you know which book you
should buy? If you have previously indicated some of your favorite
computer books, the system can match you with readers of similar
taste, and suggest a Java book that these readers found helpful.
Work on this aspect of the project is currently ongoing.
[Bruce et al.] R. Bruce, J. Foote,
D. Goldberg, J. Pedersen, K. Petersen, ``UPrint1,'' Xerox PARC
Internal Report 1996.
[Card and Pirolli] S. K. Card and P. Pirolli.
``The Cost-of-Knowledge Characteristic Function: Display Evaluation for
Direct-Walk Dynamic Information Visualizations,'' Proceedings of the
ACM SIGCHI Conference on Human Factors in Computing Systems, April
1994.
[Chen and Bloomberg]
F. Chen and D. Bloomberg,
``Extraction of Thematically Relevant Text from Images,''
Fifth Annual Symposium on Document Analysis and Information Retrieval,
April 15 - 17, 1996, Las Vegas, Nevada.
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and P.-K. Halvorsen.
``An Object-Oriented Architecture for Text Retrieval,'' Proceedings
of RIAO'91.
[Cutting et al. 92] D. Cutting, J. Kupiec,
J. Pedersen, and P. Sibun.
``A Practical Part-of-Speech Tagger,'' Proceedings of Applied
Natural Language Processing, Trento, Italy, 1992.
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J. Pedersen, and J.W. Tukey. ``Scatter/Gather: A Cluster-based Approach
to Browsing Large Document Collections,'' Proceedings of the 15th
Annual International ACM/SIGIR Conference, 1992.
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J. Pedersen. ``Constant Interaction-Time Scatter/Gather Browsing of
Large Document Collections,'' Proceedings of 16th Annual
International ACM/SIGIR Conference, Pittsburgh, PA, 1993.
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``Regular Models of Phonological Rule Systems,''
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``Visualization of Term Distribution Information in Full Text
Information Access,'' Proceedings of the ACM SIGCHI Conference
on Human Factors in Computing Systems, Denver, CO, ACM, May 1995.
http://www.acm.org/sigchi/chi95/Electronic/documnts/papers/mah_bdy.htm
[Hearst and Pedersen] M. A. Hearst and J.O. Pedersen
``Re-examining the Cluster Hypothesis:
Scatter/Gather on Retrieval Results,'' Proceedings of the
19th Annual International ACM/SIGIR Conference, Zurich, 1996.
[Johnson et al]
W. Johnson, S. K. Card, H.D. Jellinek, L. Klotz, R. Rao,
``Bridging the Paper and Electronic Worlds: The Paper User Interface,''
Proceedings of INTERCHI, ACM, April 1993. pp. 507-512.
[Kopec]
G. Kopec, ``Document image decoding in the Berkeley digital
library project,'' in Document Recognition III, L. Vincent and J. Hull,
editors, Proc. SPIE vol. 2660, pp. 2--13, 1996.
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Linguistic Approach For Question-Answering Using An On-Line
Encyclopedia,'' Proceedings of 16th Annual International ACM/SIGIR Conference,
Pittsburgh, PA, 1993.
[Kupiec] J. Kupiec, J. Pedersen, F. Chen,
``A Trainable Document Summarizer,'' Proceedings of 18th Annual
International ACM/SIGIR Conference, Pittsburgh, PA, 1995.
[Lynch and Garcia-Molina]
C. Lynch and H. Garcia-Molina,
Interoperability, Scaling, and the Digital Libraries A Report on the
May 18-19, 1995 IITA Digital Libraries Workshop Reston, VA,
August 22, 1995.
http://www-diglib.stanford.edu/diglib/pub/reports/iita-dlw/main.html
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R. Rao and S. K. Card. ``An Organic User Interface For
Searching Citation Links,'' Proceedings of the ACM SIGCHI Conference
on Human Factors in Computing Systems, Denver, CO, May 1995.
http://www.acm.org/sigchi/chi95/Electronic/documnts/papers/jdm_bdy.htm
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``Information Foraging in Information Access Environments,''
Proceedings of the ACM SIGCHI Conference
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http://www.acm.org/sigchi/chi95/Electronic/documnts/papers/ppp_bdy.htm
[Rao et al. 94] R. Rao, S. K. Card,
W. Johnson, L. Klotz, and R. Trigg, ``Protofoil: Storing and Finding
the Information Worker's Paper Documents in an Electronic File
Cabinet,'' Proceedings of the ACM SIGCHI Conference on Human
Factors in Computing Systems, April 1994.
[Rao et al. 95]
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the Digital Library,'' Communications of the ACM, 38
(4), 29-39, April 1995.
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G. G. Robertson, S. K. Card, J. D. Mackinlay.
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Cost Structure of Sensemaking,'' Proceedings of ACM InterCHI '93.
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[Schütze] H. Schütze,
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pages 787-796, Minneapolis MN, 1992.
[Schütze et al.]
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of Classifiers and Document Representations for the Routing Problem,''
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Conference, pages 229-237, 1995.
ftp://parcftp.xerox.com/pub/qca/sigir95.abs.html
hdl://cnri.dlib/june96-hearst
Information Visualization
The Butterfly Citation Browser
Experience with the Butterfly implementation has allowed the proposal
of a general information access approach, called Organic User
Interfaces for Information Access, in which a virtual landscape grows
under user control as information is accessed automatically.
Analytical and Empirical Characterization of
Information-Intensive Work
Information retrieval has often been studied as if it were a
self-contained problem (e.g., library automation). Yet from the
user's point of view, information retrieval is almost always part of
some larger process of information use. Researchers at PARC are
engaged in a set of empirical and theoretical studies to characterize
information-access-intensive work in a way that leads to the design
and evaluation of digital library and related systems.
The Inter-Language Unification System (ILU)
The Document Management Alliance (DMA)
UPrint1
Summary
This article has surveyed some of the recent activities at PARC related to
digital libraries, focussing on document capture, information access and
visualization, and middleware. The set of specific projects described here
is representative of the range of ongoing activities, but is by no means an
exhaustive list of all relevant PARC projects. Missing, for example, are
significant activities in web-based authoring, high-resolution displays,
AAA (authentication, authorization, accounting), multilingual technology,
and electronic commerce-based document services. Information about some of
these can be found via the PARC home
page.
Acknowledgements
Bill Janssen, Ramana Rao, and Hinrich Schütze contributed
material to this article. Kris Halvorsen and Larry Masinter read and
commented on early drafts.
References
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