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<H1>Galloway, Edward A. and Gabrielle V. Michalek. "The Heinz Electronic =
Library=20
Interactive On-line System (HELIOS): An Update." <I>The Public-Access =
Computer=20
Systems Review</I> 9, no. 1 (1998).</H1>
<HR>

<H2>1.0 Introduction</H2>
<P>In February 1994 Carnegie Mellon University (CMU) Libraries embarked =
on an=20
ambitious project to convert approximately one million pages of the=20
congressional papers of Pennsylvania Senator John Heinz into digital =
format. <A=20
name=3Dcite1></A><A=20
href=3D"http://epress.lib.uh.edu/pr/v9/n1/gall9n1.html#cite1n">[1]</A> =
Innovative=20
image-management and text-retrieval software created at CMU provides the =
ability=20
to search and retrieve these papers. Named in memory of the late =
Senator, the=20
Heinz Electronic Library Interactive On-line System (HELIOS) currently =
allows=20
researchers to browse, search, view, and print over 434,000 digital =
images from=20
the collection. Accessible through the campus network and the Internet, =
HELIOS=20
dramatically increases depth of indexing and quality of retrieval beyond =
that=20
which archiving resources have traditionally allowed. Since January =
1998, HELIOS=20
can be accessed on the Internet at &lt;URL:<A=20
href=3D"http://heinz1.library.cmu.edu/HELIOS">http://heinz1.library.cmu.e=
du/HELIOS</A>&gt;.=20

<P>In order to stimulate the exploration and use of the Heinz papers by =
a much=20
broader community of users than is expected with a paper-based archive, =
the=20
University Libraries proposed to digitize the congressional papers. Over =
one=20
million dollars was donated by the Heinz Family Foundation, Heinz =
Company=20
Foundation, and the Heinz Endowments to support the establishment of the =
H. John=20
Heinz III Archives and the digitization project. In addition to the =
Heinz gift,=20
CMU and the CLARITECH Corporation contributed over $700,000 in =
resources,=20
including permanent full-time staff salaries, archival equipment, and =
office=20
rental space for a processing facility. Heinz assistance has made it =
possible to=20
advance the techniques of digital preservation and access for archival=20
collections.=20
<P>Our goal has been to develop a digital archive to serve as a model =
for the=20
archival profession and research community. Traditionally, archives have =
faced=20
several challenges, including: 1. the creation of good finding aids and =
indexes=20
for large archival collections; 2. the provision of effective retrieval =
of=20
information from paper archives in spite of the inherent diversity and =
size of=20
these unique materials; and 3. the difficulty of offering broad public =
access to=20
archives since they represent resources that the researcher must visit =
in order=20
to use effectively.=20
<H2>2.0 H. John Heinz III Congressional Collection</H2>
<P>Shortly after the tragic death of Senator Heinz in 1991, the family =
placed=20
his congressional papers at Carnegie Mellon University to serve as the =
research=20
centerpiece for the H. John Heinz III School of Public Policy and =
Management.=20
After a rented archival facility near campus was prepared, the =
collection was=20
transferred from its storage facility in Harmarville, Pennsylvania to =
the rental=20
facility.=20
<P>The collection was completely processed by October 1996. It consisted =
of the=20
Heinz House of Representatives Papers (54.9 linear feet) and the Heinz =
Senate=20
Papers (670.6 linear feet). The Heinz Archives staff followed =
conventional=20
processing methods to arrange and describe the papers while applying =
fundamental=20
preservation techniques to the original material to ensure its =
longevity. In=20
addition to providing access to the physical documents, the Heinz =
Archives=20
provide electronic access to the most important series and subseries in =
the=20
record groups.=20
<P>In addition to documenting Heinz's tenure as a three-term member of =
the U.S.=20
House of Representatives (1971-1976), the papers focus on his =
fifteen-year=20
Senate career (1977-1991). Senator Heinz earned a national reputation =
based on=20
his work on retirement and aging issues, international trade and =
finance, and=20
environmental issues. The Heinz papers present a rich and valuable =
source of=20
information about the professional life of John Heinz in the U.S. =
Congress and=20
the social and political concerns of the nation during the senator's =
tenure. The=20
Heinz Archives will aid scholars in understanding the senator's =
contributions to=20
national policy and allow current public-policy makers to build upon his =

accomplishments and unfinished work.=20
<H2>3.0 HELIOS Team Members</H2>
<P>The HELIOS project is composed of three umbrella units representing =
several=20
disciplines. Each unit brings its own expertise to the project, =
resulting in=20
major contributions to the design, creation, and implementation of =
HELIOS.=20
<H3>3.1 Laboratory For Computational Linguistics</H3>
<P>Regarded as one of the world's premier laboratories for advanced work =
in the=20
field, CMU's Laboratory for Computational Linguistics (LCL) focuses its =
research=20
efforts on information management and retrieval issues. LCL researchers =
have=20
developed efficient methods to analyze and extract language using =
computers, and=20
this natural language processing (NLP) research is the basis of the =
CLARIT=20
software.=20
<H3>3.2 CLARITECH Corporation</H3>
<P>The CLARITECH Corporation, a CMU spin-off company recently purchased =
by=20
JustSystem of Japan, has improved and marketed LCL's NLP technology, =
dubbing it=20
CLARIT. CLARITECH's primary contribution to the HELIOS project is system =

architecture and interface design. It is responsible for incorporating =
elements=20
of the CLARIT system designed in the LCL into HELIOS and for creating =
four=20
graphical user interfaces for the system.=20
<H3>3.3 Carnegie Mellon University Libraries</H3>
<P>Three different units within the Carnegie Mellon University Libraries =
play a=20
major role in the interdisciplinary functioning of the project. The =
Library=20
administration is responsible for providing the leadership function for =
HELIOS=20
as well as the fiscal management of the project. The Department of =
Library=20
Information Technology is responsible for supporting and maintaining the =
HELIOS=20
client/server system. The University Archives facilitates the =
interdisciplinary=20
teamwork of the project. The Heinz Archives, a unit within the =
University=20
Archives, is responsible for establishing control over the collection,=20
appraising and processing the original Heinz papers, creating a finding =
aid to=20
the collection, providing reference service, disseminating and =
cataloging the=20
collection via OCLC, and preserving the original collection in =
perpetuity.=20
<P>Working together, the University and Heinz Archives are responsible =
for=20
developing four interface specifications, testing the interfaces before =
release,=20
scanning the original material into electronic format, verifying the =
quality of=20
the images, performing additional organizational tasks, creating =
annotations and=20
links to other parts of the electronic collection, conducting user =
protocol=20
testing, and training other library staff to use the system.=20
<P>CMU archivists were principally involved in creating system =
specifications.=20
Working diligently and closely with software designers was an important =
role=20
necessary to guarantee that archival specifications were understood and =
clearly=20
communicated. Moreover, we incorporated preservation issues into our =
plan,=20
design, system architecture, and resource allocation to ensure the =
portability=20
and interoperability of the source files.=20
<H2>4.0 HELIOS Processing</H2>
<P>To create the growing HELIOS database, processed documents are =
scanned,=20
converted to ASCII form via OCR (Optical Character Recognition) =
software,=20
verified and annotated, and then indexed using the CLARIT natural =
language=20
processing software. The project has developed four graphical user =
interfaces: a=20
scanning interface (HelioScan), a verification interface =
(HeliosArchivist), a=20
Windows-based user interface (CLARIT Retrieval for Windows), and a =
Web-based=20
user interface (CLARITweb). (See Figure 1.)=20
<HR>
Figure 1. Helios Project Flowchart=20
<HR>
<IMG border=3D0 alt=3D"Figure 1"=20
src=3D"http://epress.lib.uh.edu/pr/v9/n1/figure1.gif">=20
<HR>
The original paper documents were processed based on the typical =
arrangement=20
scheme of a congressional collection. During the last year of document=20
processing, we began the digital conversion process, taking entire =
folder=20
contents from completed series and subseries and digitizing them at 400 =
dots per=20
inch (dpi). We converted the image files to ASCII text on a nightly =
basis using=20
the TextBridge OCR software package. After the images and text were =
verified,=20
with additional notes and organization added, the text was indexed by =
CLARIT,=20
resulting in the searchable Heinz Senate Papers database.=20
<H3>4.1 Scanning</H3>
<P>After one year of initial testing and development, we commenced the=20
full-scale scanning of material in January 1996. By this time almost the =
entire=20
Senate collection was processed, so the Heinz Archivist selected several =
series=20
indicated by survey results as being of interest to local researchers. =
Since we=20
are attempting to digitize the record of Senator Heinz's congressional =
life and=20
activities, we are scanning the complete contents of the folders within =
a series=20
and subseries.=20
<P>With the use of two 586 Dell PCs running Windows for Workgroups =
3.1.1, 20"=20
color monitors (1600 x 1200 pixels), and two high-end Fujitsu scanners, =
we are=20
creating 400 dpi bitonal TIFF (Tagged Image File Format) images. The =
images are=20
compressed using CCITT Group IV, an international compression standard, =
and=20
backed up on 4 mm digital data storage tapes on a nightly basis. The =
scanning=20
workstations are networked to our Sun Sparcstation server (UNIX) where =
the data=20
is stored.=20
<P>Our choice to use 400 dpi resolution coupled with bitonal scanning =
was driven=20
by three factors: 1. 400 dpi was the highest true resolution offered =
when we=20
began scanning; 2. the material in the archives consists almost =
exclusively of=20
typical documents with black ink on white paper; and 3. a higher =
resolution=20
yields better OCR performance. As far as digital preservation goes, the=20
faithfulness of our image to the original document is directly =
proportional to=20
the scanning resolution. Unlike compression algorithms for gray scale or =
color=20
scanning, compression algorithms for binary images do not lead to the =
loss of=20
any data and can thus be used to reduce the storage size of our images =
without=20
compromising their faithfulness to the original.=20
<P>Because the scanning procedure represents the most crucial aspect of =
the=20
project, we designed a scanning interface, dubbed HelioScan, to =
facilitate the=20
rapid scanning of documents while capturing essential contextual =
information=20
(metadata) for the user and archives staff. <A name=3Dcite2></A><A=20
href=3D"http://epress.lib.uh.edu/pr/v9/n1/gall9n1.html#cite2n">[2]</A> =
On average,=20
the scanning operators scan approximately 1,200 pages per day. As of May =
1,=20
1998, we have scanned over 560,000 pages from the Heinz Senate Papers.=20
<P>HelioScan is structured to imitate a standard archival collection =
arrangement=20
scheme, organizing documents into subgroups, series, subseries, and =
smaller=20
units. (See Figure 2.) The scanning operator selects the appropriate =
level using=20
drop-down menus. The operator then enters the box and folder number as =
well as=20
the folder title and date. HelioScan was also designed to capture =
"bundles";=20
that is, groups of documents within folders originally fastened together =
by=20
paper clips, staples, or rubber bands. These bundles, which often =
reflect=20
inherent meaning, are more difficult to depict to an online user; =
however, doing=20
so is important because it gives the user the same context as if he or =
she were=20
physically examining the material.=20
<HR>
Figure 2. HelioScan v2.0=20
<HR>
<IMG border=3D0 alt=3D"Figure 2"=20
src=3D"http://epress.lib.uh.edu/pr/v9/n1/figure2.gif">=20
<HR>
The document feature allows the operator to choose from a prepared list =
of=20
document types, such as correspondence, memoranda, speeches, and notes, =
and to=20
assign a corresponding date. There are two reasons for doing this. =
First,=20
tagging this kind of data will enable a user to restrict a search to a =
specified=20
document type. Second, most archival documents do not have distinct =
titles. To=20
overcome this problem and to generate a useful description of the =
retrieved=20
document for the user, the document type and date can be offered as the =
title.=20
Providing this kind of "fielded" information is vital for access to the =
material=20
and to maintain contextual accuracy.=20
<P>In addition to capturing the contextual information or metadata, this =

interface was developed to take into account the unique characteristics =
of=20
archival documents. Prior to scanning a document, the operator must =
specify page=20
size; brightness and contrast levels; whether the document is single- or =

double-sided; orientation of the page; and the scanner source (flatbed =
or=20
automatic document feeder). When a page is scanned, it appears in an =
image=20
viewer adjacent to the scanning interface, allowing the operator to =
determine=20
the success of the scan and to rescan if necessary. Each scanning =
session is=20
logged to monitor quality control and record scanning performance.=20
<H3>4.2 Optical Character Recognition</H3>
<P>In order for the system to provide innovative searching capabilities, =
the=20
images must be converted to machine-readable format. This text =
recognition=20
process, commonly referred to as optical character recognition, produces =
a=20
standard ASCII text file. An off-the-shelf package called TextBridge, a =
Xerox=20
Imaging Systems product, is used for OCR conversion. We run the OCR =
program in=20
batch mode at night to economize staff time and computer usage.=20
<H3>4.3 Verification</H3>
<P>Once a complete series or subseries has been digitized and text files =
have=20
been produced, members of the archives staff utilize a verification =
interface,=20
dubbed HeliosArchivist, that supports image and text verification, =
annotation,=20
and organization. We are using three Dell 586 PCs running Windows NT 4.0 =
with=20
20" color monitors (1280 x 1024 pixels) to perform the verification =
tasks. Using=20
a client/server system, the PCs are networked to the server.=20
<P>Since December 1996, graduate students and the Heinz Archivist have =
performed=20
the majority of the verification tasks. As of May 1, 1998, we have =
verified over=20
495,000 images.=20
<P>HeliosArchivist provides the ability to browse the hierarchical =
contents of=20
the archives as well as move through the contents of a folder page by =
page,=20
document by document. HeliosArchivist displays each page image and its=20
associated ASCII text to the verifier, and it enables the verifier to:=20
<UL>
  <LI>Verify the quality of the page image against the original page =
itself.=20
  <LI>Schedule pages for rescanning.=20
  <LI>Check and correct the attributes associated with each page (e.g., =
document=20
  type).=20
  <LI>Evaluate the quality of the OCR conversion for each page.=20
  <LI>Perform minimal editing of the converted ASCII text, perhaps =
keying in=20
  sections that were not converted by the OCR process, such as =
handwritten=20
  notes.=20
  <LI>Mark pages with serious OCR conversion problems so that they can =
be=20
  keyboarded by a typist at a later date.=20
  <LI>Add notations at the folder and/or document level.=20
  <LI>Perform other organizational tasks, including the reordering of =
pages,=20
  documents, or folders. (See Figures 3 and 4.) </LI></UL>
<HR>
Figure 3. HeliosArchivist v2.0--Browser Window=20
<HR>
<IMG border=3D0 alt=3D"Figure 3"=20
src=3D"http://epress.lib.uh.edu/pr/v9/n1/figure3.gif">=20
<HR>
Every page of a primary source (e.g., memos, speeches, correspondence) =
is=20
verified; only the first page of a secondary source is reviewed (e.g., =
reports,=20
articles). The verifiers are assigned a complete series or subseries to =
verify.=20
For documents not scanned in their entirety, such as government =
publications,=20
the verifiers note the availability of the complete report in a regional =

repository or alert the user to see the actual folder. Each document and =

corresponding image is rated as "Good," "Fair," or "Poor." We can also =
indicate=20
that the original document possessed one or more of the following=20
characteristics: it was stained, crooked, and/or had poor contrast.=20
<HR>
Figure 4. HeliosArchivist v2.0--Image Window and Document Report Card=20
<HR>
<IMG border=3D0 alt=3D"Figure 4"=20
src=3D"http://epress.lib.uh.edu/pr/v9/n1/figure4.gif">=20
<HR>

<H2>5.0 HELIOS Server</H2>
<P>Running Solaris 2.4, the Sun Sparcstation server (UNIX) is housed in =
CMU's=20
Computer Center, a strictly climate-controlled environment not =
susceptible to=20
damage from high humidity, rapid and extreme temperature fluctuations,=20
contamination from airborne particulate matter, or power outages. In =
addition to=20
storing the images and text, the server also stores the verification=20
application, the CLARIT Retrieval for Windows application, the CLARIT =
index=20
software, and the CLARIT server and CLARITweb applications.=20
<P>To accommodate our rapidly growing database, we continue to add =
external=20
drives to the Sparcstation; currently we have nine nine-gigabyte Seagate =
drives.=20
To manage the external drives, we employ a virtual volume manager =
(Solstice Disk=20
Suite). The source files that are indexed for the CLARIT server =
application=20
comprise slightly more than the sum of the ASCII text files.=20
<H2>6.0 Searching HELIOS</H2>
<P>Digital technology offers effective and innovative methods of =
providing=20
access to and managing large bodies of heterogeneous material. However,=20
converting material to digital format only for preservation purposes ". =
. . will=20
add little value to the research process if it serves only as an =
alternative=20
form of storage from which analog replicas are produced for use with=20
conventional analytical methods." <A name=3Dcite3></A><A=20
href=3D"http://epress.lib.uh.edu/pr/v9/n1/gall9n1.html#cite3n">[3]</A> =
Indeed,=20
scholars will come to expect the coupling of digital research sources =
with the=20
tools necessary to analyze them. Therefore, we wanted to equip =
researchers with=20
traditional methods of searching and browsing an archive while adding =
new and=20
robust electronic capabilities not available in the analog world.=20
<H3>6.1 NLP Search Engine</H3>
<P>As previously mentioned, the HELIOS search engine (CLARIT) utilizes =
natural=20
language processing technology. NLP stems from work done in the fields =
of=20
computer science, artificial intelligence, and linguistics. Natural =
language is=20
simply common, everyday language we use to speak and write. Natural =
language=20
processing allows users to interact with a computer system, describing =
topics of=20
interest using their own language as opposed to reacting to menus and =
prompts or=20
using keyword and Boolean searching techniques. Consequently, they can =
make=20
better use of the database with only a general knowledge of its =
contents.=20
<P>As the HELIOS search engine, CLARIT supports more accurate, =
sensitive, and=20
robust content-based indexing and retrieval than is possible with =
traditional=20
"word-based" information retrieval technologies. Its indexing and =
retrieval=20
capabilities are not based on locating individual words, but rather on=20
extracting concepts that accurately characterize the content of =
documents.=20
Combined with specialized statistical methods, CLARIT analyzes a query=20
linguistically, comparing it with a similar linguistic analysis of the =
actual=20
documents in the database. We have applied CLARIT to the problem of =
managing=20
compound documents (text and images) and the special requirements of =
archival=20
material.=20
<P>Why use NLP? Concrete disciplines, such as the medical and legal =
professions,=20
often communicate and express ideas in rigorous terminology. But =
historians and=20
other scholars, who use archives and historical material, approach their =

discipline with more imprecise language. This is why NLP technology has =
such=20
promise for robust retrieval of archival material.=20
<P>The Text Retrieval Conference (TREC) studies sponsored by the =
National=20
Institute of Science and Technology (NIST) and the Department of =
Defense's=20
Advanced Research Projects Agency (ARPA) have now demonstrated that =
CLARIT has a=20
compelling advantage over traditional keyword and Boolean searching and=20
retrieval. <A name=3Dcite4></A><A=20
href=3D"http://epress.lib.uh.edu/pr/v9/n1/gall9n1.html#cite4n">[4]</A> =
Studies of=20
keyword and Boolean retrieval systems have shown that they sometimes =
provide=20
good precision and sometimes good recall, but never both together, and =
often=20
neither. <A name=3Dcite5></A><A=20
href=3D"http://epress.lib.uh.edu/pr/v9/n1/gall9n1.html#cite5n">[5]</A> =
The=20
non-expert searcher (i.e., the average library user) has even less =
success. In=20
addition, Boolean logic operators or special devices like adjacency and =
nesting=20
are usually ignored by the general user who opts for single-term =
searches in=20
hopes of getting the greatest number of retrieved items. They know from=20
experience that they will do better by manually sifting the results and=20
selecting relevant documents.=20
<P>Efforts to enhance online records have improved recall at the expense =
of=20
precision. Unless we find new tools, moving to full-text electronic =
access will=20
only make matters worse. CMU believes that CLARIT is the "better =
mousetrap"--one=20
that will be especially useful for accessing archival material.=20
<H3>6.2 CLARITweb and CLARIT Retrieval for Windows</H3>
<P>The majority of users can access HELIOS on the Internet at &lt;URL:<A =

href=3D"http://heinz1.library.cmu.edu/HELIOS">http://heinz1.library.cmu.e=
du/HELIOS</A>&gt;.=20
In addition to offering the ability to search portions of the =
collection, the=20
site includes Web pages entitled: About the HELIOS Project; Frequently =
Asked=20
Questions; CLARITweb User's Guide; and Restrictions on Using HELIOS.=20
<P>Campus users can use a more robust searching interface called CLARIT=20
Retrieval for Windows. It adds more powerful functions for constraining=20
searches, displaying retrieved documents, editing queries, and more.=20
<P>Either interface allows the user to select a database, submit a=20
natural-language query (e.g., the global loss of biodiversity associated =
with=20
the destruction of tropical rainforests and global warming), and review =
a list=20
of retrieved documents ranked in order of their estimated relevance to =
the=20
query. The "title" for each retrieved document is generated by several =
metadata=20
fields: Document Type; Document Date; Subject; Folder Title; Folder =
Date. Once=20
the image is displayed, the user can move through the list of retrieved=20
documents or move forward or backward through any level of the =
collection (e.g.,=20
move to the next or previous page of the document or the next or =
previous=20
document in the folder).=20
<P>Each interface offers tools to improve query results. The "enhance =
query"=20
feature extracts related terminology from selected documents; these =
terms are=20
generated "on the fly" by CLARIT. This feature allows the documents to =
describe=20
themselves and eliminates the need for pre-existing indices. A second =
feature=20
allows the researcher to edit the query by adjusting the weight of each =
search=20
term. Another feature allows the researcher to use an existing page as =
an=20
example query to locate more documents like it.=20
<P>The user can limit or constrain a search to particular fields in the=20
database. However, CLARITweb only allows specification of the following =
fields=20
in a search: Document Type, Document Date, or Principal Persona (e.g.,=20
affiliation with John Heinz).=20
<P>Unless otherwise specified, CLARIT searches the entire collection; =
therefore=20
it is crucial for the user to be able to see the context in which the =
retrieved=20
documents were created. Each HELIOS interface features a context button =
("Where=20
am I?") that creates a hierarchical view of the archives structure, =
placing the=20
displayed document in its proper context. It presents the name and date =
of the=20
folder from which a retrieved page originated, including the name of its =

subgroup, series, or smaller unit. It also allows the user to browse the =

inventory of any series as well as read the series descriptions. In this =
way the=20
user interfaces incorporate the traditional methods of performing =
archival=20
research that maintain the context in which documents were created.=20
<P>Either interface allows the user to examine the metadata, archivist =
notes,=20
quality assessments, and ASCII text. Captured for each image, the =
metadata=20
display contextual information which includes Title, Document Type, =
Document=20
Date, Bundle Number, Folder Number, Subject (if applicable), Folder =
Title,=20
Folder Date, Box Number, Subgroup name, Series name, Subseries name, and =
more.=20
In addition, the metadata show the assessment of the original document, =
the=20
transcriptions of selected handwritten notes or failed OCR results, the=20
archivist's notes at the folder and/or document level, the raw OCR =
output, and=20
the indication of the availability of the complete document elsewhere.=20
<P>
<H3>6.3 Focus Groups and Protocol Testing</H3>
<P>Shortly after the release of HELIOS on the World Wide Web, CMU =
Libraries=20
would like to begin conducting formal user protocol testing to provide =
concrete=20
data about how researchers actually approach and use the Web-based =
interface and=20
to make changes as needed. In focus groups, users will often describe =
what they=20
think they need, but protocol testing will show that they actually want=20
something else.=20
<H2>7.0 Potential HELIOS Benefits</H2>
<P>The HELIOS project team anticipates that the system will have a =
number of=20
potential benefits:=20
<UL>
  <LI>It will allow users to find archival information quickly and =
efficiently.=20
  Because of the overwhelming amount of material that is often present =
in=20
  congressional archives, research is often a result of an extremely=20
  time-consuming manual "hit or miss" research method. Using HELIOS, =
users will=20
  eliminate the need to wade through pages and pages of less significant =

  material in search of those "golden nuggets." Scholars will be able to =
focus=20
  their efforts more on exploring new ideas, comparing and contrasting =
new=20
  relationships, and drawing conclusions, rather than on performing =
endless=20
  hours of manual research.=20
  <LI>It will provide uniform and consistent access to the collection in =
a way=20
  that is superior to the access provided by traditional finding aids.=20
  <LI>It will provide subject access across the entire record group, =
series,=20
  subseries, and folders, making the collection accessible in a variety =
of ways.=20

  <LI>New series, which in the past received little research attention =
due to=20
  unmanageable bulk or perceived irrelevance of folder titles, will be =
easily=20
  accessible.=20
  <LI>Many archives users simply do not have the time or money to travel =
to=20
  distant repositories to conduct research. Remote users will be able to =
access=20
  both HELIOS and a finding aid via the Internet using World Wide Web =
browsers=20
  such as Netscape. Consequently, the archives' location and operating =
hours=20
  will no longer be a concern.=20
  <LI>Many potential users of archives avoid them because of poor =
finding aids,=20
  excessive bulk, and time constraints, turning instead to secondary =
sources of=20
  information. HELIOS will encourage these traditional users to conduct =
more=20
  archival research, and it will attract new types of users. </LI></UL>
<H2>8.0 Conclusion</H2>
<P>By effectively utilizing imaging, OCR, and natural language =
processing=20
technologies, the HELIOS project promises to dramatically transform the =
Heinz=20
Archives' services by providing researchers with state-of-the-art =
electronic=20
access to archival source materials. The HELIOS project is building a =
prototype=20
of the digital archive of the future. It is to be hoped that it will be =
one of=20
many similar projects that will make archival information instantly =
available to=20
users across the globe, offering them advanced information retrieval=20
capabilities that significantly enhance their research activities.=20
<H2>Notes</H2>
<P><A name=3Dcite1n></A><A=20
href=3D"http://epress.lib.uh.edu/pr/v9/n1/gall9n1.html#cite1">1.</A> =
This article=20
is a revised version of "The Heinz Electronic Library Interactive Online =
System=20
(HELIOS): Building a Digital Archive Using Imaging, OCR, and Natural =
Language"=20
&lt;URL:<A=20
href=3D"http://info.lib.uh.edu/pr/v6/n4/gall6n4.html">http://info.lib.uh.=
edu/pr/v6/n4/gall6n4.html</A>&gt;,=20
published in <I>Public-Access Computer Systems Review</I>, volume 6, =
number 4,=20
1995.=20
<P><A name=3Dcite2n></A><A=20
href=3D"http://epress.lib.uh.edu/pr/v9/n1/gall9n1.html#cite2">2.</A> =
Metadata is=20
data about data. The term refers to any data used to aid the =
identification,=20
description, and location of networked electronic resources. Many =
different=20
metadata formats exist, some quite simple in their description, others =
quite=20
complex and rich.=20
<P><A name=3Dcite3n></A><A=20
href=3D"http://epress.lib.uh.edu/pr/v9/n1/gall9n1.html#cite3">3.</A> =
Margaret=20
Hedstrom, <I>Digital Preservation: a Time Bomb for Digital =
Libraries.</I> See=20
&lt;URL:<A=20
href=3D"http://www.uky.edu/~kiernan/DL/hedstrom.html">http://www.uky.edu/=
~kiernan/DL/hedstrom.html</A>&gt;.=20

<P><A name=3Dcite4n></A><A=20
href=3D"http://epress.lib.uh.edu/pr/v9/n1/gall9n1.html#cite4">4.</A> =
Donna Harmon,=20
ed., <I>The Second Text REtrieval Conference (TREC-2)</I> (Washington, =
DC:=20
Government Printing Office, 1994).=20
<P><A name=3Dcite5n></A><A=20
href=3D"http://epress.lib.uh.edu/pr/v9/n1/gall9n1.html#cite5">5.</A> =
D.C. Blair=20
and M.E. Maron, "An Evaluation of Retrieval Effectiveness for a =
Full-Text=20
Document-Retrieval System," <I>Communications of the ACM</I> 28 (March =
1985):=20
289-299.=20
<H2>About the Authors</H2>
<P>Edward A. Galloway, Heinz Archivist, H. John Heinz III Archives, =
Carnegie=20
Mellon University, 5000 Forbes Avenue, Hamburg Hall, Room 2504B, =
Pittsburgh, PA=20
15213-3890. Internet: <A=20
href=3D"mailto:eg2d@andrew.cmu.edu">eg2d@andrew.cmu.edu</A>.=20
<P>Gabrielle V. Michalek, University Archivist, University Libraries, =
Carnegie=20
Mellon University, 5000 Forbes Avenue, Hunt Library - University =
Archives,=20
Pittsburgh, PA 15213-3890. Internet: <A=20
href=3D"mailto:gm1l@andrew.cmu.edu">gm1l@andrew.cmu.edu</A>.=20
<H2>About the Journal</H2>
<P>The World Wide Web home page for <I>The Public-Access Computer =
Systems=20
Review</I> provides detailed information about the journal and access to =
all=20
article files: &lt;URL:<A=20
href=3D"http://info.lib.uh.edu/pacsrev.html">http://info.lib.uh.edu/pacsr=
ev.html</A>&gt;.=20

<H2>Copyright</H2>
<P>This article is Copyright =C2=A9 1998 by Edward A. Galloway and =
Gabrielle V.=20
Michalek. All Rights Reserved.=20
<P><I>The Public-Access Computer Systems Review</I> is Copyright =C2=A9 =
1998 by the=20
University Libraries, University of Houston. All Rights Reserved.=20
<P>Copying is permitted for noncommercial, educational use by academic =
computer=20
centers, individual scholars, and libraries. This message must appear on =
all=20
copied material. All commercial use requires permission. =
</P></BODY></HTML>

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------=_NextPart_000_0000_01CA0C5E.DA462650--

