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&lt;A name=1&gt;&lt;/a&gt;&lt;b&gt;Applications for Bibliometric Research&lt;/b&gt;&lt;br&gt;


&lt;b&gt;in the Emerging Digital Libraries&lt;/b&gt;&lt;br&gt;


Sally Jo Cunningham&lt;br&gt;


Department of Computer Science&lt;br&gt;


University of Waikato&lt;br&gt;


Hamilton, New Zealand&lt;br&gt;


email:  [email protected]&lt;br&gt;


&lt;b&gt;Abstract:&lt;/b&gt;  Large numbers of research documents have recently become available on&lt;br&gt;


the Internet through  “digital libraries”, and these collections are seeing high levels of&lt;br&gt;


use  by  their  related  research  communities.  A  secondary    use  for  these  document&lt;br&gt;


repositories and indexes is as a platform for bibliometric research.  We examine the&lt;br&gt;


extent to which the new digital libraries support conventional bibliometric analysis, and&lt;br&gt;


discuss  shortcomings  in  their  current  forms.    Interestingly,  these  electronic  text&lt;br&gt;


archives also provide opportunities for new types of studies:  generally the full text of&lt;br&gt;


documents are available for analysis, giving a finer grain of insight than abstract-only&lt;br&gt;


online databases;  these repositories often contain technical reports or pre-prints, the&lt;br&gt;


“grey  literature”  that  has  been  previously  unavailable  for  analysis;  and  document&lt;br&gt;


“usage”  can  be  measured  directly  by  recording  user  accesses,  rather  than  studied&lt;br&gt;


indirectly through document references.&lt;br&gt;


&lt;b&gt;1.  Introduction&lt;/b&gt;&lt;br&gt;


In recent years a number of &amp;quot;digital libraries&amp;quot; have become available through the&lt;br&gt;


Internet.  While the technology promises in the future to support large, heterogenous&lt;br&gt;


collections, at present the most widely used of the academically-focussed digital&lt;br&gt;


libraries are generally repositories of one or two types of document (typically technical&lt;br&gt;


reports, journal articles, pre-prints, or conference proceedings), grouped by discipline.&lt;br&gt;


&lt;hr&gt;


&lt;A name=2&gt;&lt;/a&gt;A distinguishing characteristic of these digital libraries is that the full text of documents&lt;br&gt;


are often available for retrieval, as well as bibliographic records.The sciences are&lt;br&gt;


represented much more heavily in the present crop of digital libraries than the social&lt;br&gt;


sciences, arts, or humanities. They are maintained by professional societies,&lt;br&gt;


universities, research laboratories, and even private individuals.  Access is generally&lt;br&gt;


free, both to search and to download documents.&lt;br&gt;


The emergence of these subject-specific digital libraries is particularly important&lt;br&gt;


given the pattern of access to materials presently employed by research scientists.&lt;br&gt;


Informal exchanges of preprints, reprints, and photocopies of papers passed on by&lt;br&gt;


colleagues currently are major venues for the transmission of scientific information&lt;br&gt;


between researchers in the sciences.  In one study, the dependence on these sources&lt;br&gt;


ranges from 12% (for chemistry)  to 39% (for mathematics) of all papers cited in&lt;br&gt;


researchers' own publications [11]. A qualitative study of study of how computer&lt;br&gt;


scientists locate and retrieve documents (computing is one of the domains considered&lt;br&gt;


later in this paper) indicates that for that field, technical reports and research documents&lt;br&gt;


found in various locations on the Internet are a preferred source of information [6].&lt;br&gt;


Many of the digital library systems discussed in this paper are repositories for just this&lt;br&gt;


type of literature.  The documents tend to be of high quality:  primarily  technical&lt;br&gt;


reports or working papers from research institutions (both academic and commercial),&lt;br&gt;


as well as advance copies of work accepted for publication in conventional paper&lt;br&gt;


journals. Moreover, these digital libraries are also coming to include refereed work&lt;br&gt;


published digitally (in electronic journals).  Anecdotal evidence suggests that in their&lt;br&gt;


fields, these digital libraries are coming to be the resource of choice for locating cutting&lt;br&gt;


edge work.&lt;br&gt;


For specialized subjects such as high energy physics, this dependence on&lt;br&gt;


informal or extra-library dissemination can be much higher. Ginsparg ([9], [10])&lt;br&gt;


reports that fields in physics have traditionally relied heavily on preprint exchanges, and&lt;br&gt;


the digital repositories of physics preprints begun in 1991 (the PHYSICS E-PRINT&lt;br&gt;


ARCHIVES) have to a large extent supplanted conventional publishing and physical&lt;br&gt;


&lt;hr&gt;


&lt;A name=3&gt;&lt;/a&gt;paper mailing of technical reports.  By providing ready access to information sources&lt;br&gt;


that are already preferentially utilized by scientists, the digital libraries show potential to&lt;br&gt;


increase access to information that until recently was expensive or difficult to acquire in&lt;br&gt;


paper form.  Indeed, in some fields (most notably physics) this process has already&lt;br&gt;


begun, as researchers in less developed countries report access to ongoing research&lt;br&gt;


through the Internet repositories that their local libraries could not afford to acquire&lt;br&gt;


through conventional journal subscriptions ([9], [10]).&lt;br&gt;


The primary use for new bibliographic resources is, of course, for the contents&lt;br&gt;


of the documents involved.  A secondary use for emerging resources is as a basis for&lt;br&gt;


bibliometric analysis of the subject field.  With the conventionally published scientific&lt;br&gt;


literature, the sheer difficulty of accumulating statistics discouraged bibliometric&lt;br&gt;


research until the advent of large bibliographic databases in the 1960's. Computerized&lt;br&gt;


bibliographic databases sparked a significant increase in the number of large-scale&lt;br&gt;


bibliographic studies, as significant portions of the collection and analysis of data could&lt;br&gt;


be automated ([12], [13]).  The availability of CD-ROM versions of bibliographic&lt;br&gt;


databases has been of particular importance, since they provide a cheaper alternative to&lt;br&gt;


the online commercial databases [3].&lt;br&gt;


These computerized bibliographic resources have drawbacks, however.  The&lt;br&gt;


greatest is that the full text of documents are rarely available, and even abstracts are not&lt;br&gt;


always present.  This obviously limits the types of bibliometric research that can be&lt;br&gt;


conducted &lt;i&gt;solely&lt;/i&gt; through these databases.  In addition, these databases are generally&lt;br&gt;


limited to formally published documents (those appearing in selected books, journals,&lt;br&gt;


and conference proceedings).  The &amp;quot;grey literature&amp;quot; of technical reports, pre-prints, and&lt;br&gt;


other works not formally published are largely ignored, and it is this absence of easy&lt;br&gt;


access to these documents that has hampered the analysis of these important forms of&lt;br&gt;


scientific communication.&lt;br&gt;


The digital libraries currently in existence complement the online and CD-ROM&lt;br&gt;


bibliographic databases.  They are best suited for examinations of the &amp;quot;physical&amp;quot;&lt;br&gt;


characteristics of documents (for example, document length), analysis based on&lt;br&gt;


&lt;hr&gt;


&lt;A name=4&gt;&lt;/a&gt;bibliographic information that can be automatically extracted from the document text or&lt;br&gt;


the sometimes unevenly formatted bibliographic records (such as obsolescence&lt;br&gt;


studies),  and usage studies (geographic or institutional origin of users, date/time of&lt;br&gt;


access, individual patterns of document retrieval, etc.).  Because  references are present&lt;br&gt;


in the document file but not identified by field, co-citation and bibliographic coupling&lt;br&gt;


research is not well-supported, and conducting these studies requires considerable&lt;br&gt;


effort on the part of the researcher.&lt;br&gt;


The variety of bibliographic repositories in the available digital libraries in itself&lt;br&gt;


has great potential in conducting bibliometric research.  Sigogneau et al [15] present a&lt;br&gt;


case study illustrating the ways in which the strengths of different databases can be&lt;br&gt;


played off each other; they conduct a fine-grained analysis of the emergence of research&lt;br&gt;


fronts in molecular and cellular biology, and demonstrate that the observations gleaned&lt;br&gt;


from two complementary bibliographic databases provide greater insight into their&lt;br&gt;


problem. Similarly, it appears that  the types of bibliographic data that can be gleaned&lt;br&gt;


from the relatively unstructured digital libraries can be profitably combined with data&lt;br&gt;


from online databases, CD-ROMS, and other more conventional bibliographic&lt;br&gt;


resources.&lt;br&gt;


This paper is organized as follows:  Section 2 discusses the types of indexing&lt;br&gt;


and searching available with current digital libraries; Section 3 gives examples of&lt;br&gt;


conventional bibliometric techniques applied to Internet-accessible archives; Section 4&lt;br&gt;


discusses opportunities to directly measure usage of documents and to detect&lt;br&gt;


information-seeking patterns in researchers; and Section 5 presents our conclusions.&lt;br&gt;


&lt;b&gt;2.  Indexing and searching in current digital libraries&lt;/b&gt;&lt;br&gt;


At present, the types of indexing fields for most academically-oriented digital&lt;br&gt;


library systems are limited.  Many schemes index on user-supplied document&lt;br&gt;


descriptions, abstracts, or similar document surrogates (for example, the PHYSICS E-&lt;br&gt;


PRINT ARCHIVE [10], a collection of physics pre-prints and technical reports). As will&lt;br&gt;


&lt;hr&gt;


&lt;A name=5&gt;&lt;/a&gt;be discussed below, the quality of this user-provided data can be highly variable, and&lt;br&gt;


may unfavorably impact the usefulness of the index for searching. Alternatively, a&lt;br&gt;


designated site librarian may maintain a catalog (eg, the WATERS [14] system, now&lt;br&gt;


subsumed by NCSTRL (http://www.ncstrl.org/), both primarily collections of&lt;br&gt;


computer science technical reports);  in this case the quality of the bibliographic&lt;br&gt;


information may be expedited to be higher, but fewer sites will be likely to support&lt;br&gt;


such a librarian and therefore fewer documents are likely to be included in the digital&lt;br&gt;


library. In a “harvesting” system such as the computer science technical report&lt;br&gt;


collections supported by HARVEST  [2] or the NEW ZEALAND DIGITAL LIBRARY&lt;br&gt;


computer science technical report collection ([16], [17]), documents are indexed from&lt;br&gt;


passive repositories (that may not even be aware that their documents are being&lt;br&gt;


included in the digital library). Harvesting systems therefore cannot rely on the&lt;br&gt;


presence of bibliographic data of any sort.&lt;br&gt;


Because of the relative paucity of high-quality bibliographic data available to&lt;br&gt;


many of the current academically- or research-focussed digital library collections, their&lt;br&gt;


search interfaces tend to be more primitive than those ordinarily found in online&lt;br&gt;


bibliographic databases or library catalogs.  Systems such as NCSTRL can support&lt;br&gt;


author, title, and subject searching, but  this more sophisticated search functionality&lt;br&gt;


comes at the expense of requiring participating repositories to use specific software.  As&lt;br&gt;


a consequence, these latter systems may provide access to a small number of sites than&lt;br&gt;


harvesting systems. Harvesters may access a broader range of providers, but at the&lt;br&gt;


penalty of being limited to unfielded, keyword searches over the raw text of the&lt;br&gt;


document or document surrogate.&lt;br&gt;


Specifically, the indexing in existing digital libraries has a variety of shortcomings for&lt;br&gt;


bibliometric applications:&lt;br&gt;


•&lt;br&gt;


&lt;i&gt;lack of fielded indexing:&lt;/i&gt;   As noted above, some large and widely used digital&lt;br&gt;


libraries (such as the computer science technical report collection of the  NEW&lt;br&gt;


ZEALAND DIGITAL LIBRARY) may lack formal cataloging entirely, and rely on&lt;br&gt;


&lt;hr&gt;


&lt;A name=6&gt;&lt;/a&gt;keyword searching over the raw document text. Obviously this  makes  field-&lt;br&gt;


dependent analysis more difficult (for example, locating documents produced by&lt;br&gt;


specific authors), and in the worst case my require a manual examination of all&lt;br&gt;


files in the collection in order to reliably identify a desired document subset.&lt;br&gt;


However, keyword search techniques that approximate fielded searching results&lt;br&gt;


may suffice:  for example in the  NEW ZEALAND DIGITAL LIBRARY computer&lt;br&gt;


science technical report collection,  limiting the keyword search for “Johnson”&lt;br&gt;


to a search of first pages only is likely to retrieve documents written by Johnson&lt;br&gt;


(since for the  majority  of  computer  science  technical  reports,  the  first  page&lt;br&gt;


contains little more than author, title, date, and institution details).&lt;br&gt;


A more principled  approach to extracting bibliographic information is embodied&lt;br&gt;


in  the  CiteSeer  tool  [1].  This  software  parses  raw,  unfielded  academic&lt;br&gt;


documents and attempts to identify such indexing information as author, title,&lt;br&gt;


reference list, etc. Obviously such a tool cannot attain 100% accuracy over a&lt;br&gt;


heterogenous document collection, but in practice it appears useful in that it can&lt;br&gt;


make a good first pass in processing a set of documents, providing an initial set&lt;br&gt;


of parsed documents for analysis. The remaining (presumably much smaller) set&lt;br&gt;


of unparsable documents can then be dealt with manually.&lt;br&gt;


•&lt;br&gt;


&lt;i&gt;lack of consistency in field formatting:&lt;/i&gt;  Current digital libraries usually acquire&lt;br&gt;


bibliographic  information  from  either  the  authors  of  submitted  articles  or&lt;br&gt;


automatic extraction routines (retrieving bibliographic details from catalog files&lt;br&gt;


that may or may not be in a given document site, and that may or may not be in&lt;br&gt;


an  easily  parsable  form).  Neither  of  these  methods  produce  records  with&lt;br&gt;


standard  formatting,  which  causes  problems  with  automated  bibliometric&lt;br&gt;


analysis.   Consider the following examples selected from entries in the hep-th&lt;br&gt;


(high energy physics) collection of the PHYSICS E-PRINT ARCHIVES:&lt;br&gt;


&lt;hr&gt;


&lt;A name=7&gt;&lt;/a&gt;(i)&lt;br&gt;


Authors: A. Yu. Alekseev, V. Schomerus&lt;br&gt;


(ii)&lt;br&gt;


Authors: Adel Bilal and Ian. I. Kogan&lt;br&gt;


(iii)&lt;br&gt;


Authors: Paul S. Aspinwall and David R. Morrison (with an appendix &lt;br&gt;


by Mark Gross)&lt;br&gt;


(iv)&lt;br&gt;


Authors: A. H. Chamseddine and Herbi Dreiner (ETH-Zurich)&lt;br&gt;


In this case, typical for existing digital libraries, there is no standardized format&lt;br&gt;


for authors' names (here, appearing with full names, initials plus last name, and&lt;br&gt;


a mixture of  the  two);  no  standard  convention  for  separating  author  names&lt;br&gt;


(here, either a comma or &amp;quot;and&amp;quot; are  used);  and  parenthetical  information  can&lt;br&gt;


include a variety of information such as the name of an associate author or the&lt;br&gt;


institutional affiliations of an author.  Manual processing or specially  crafted&lt;br&gt;


software would be required to reformat these fields for analysis.&lt;br&gt;


•&lt;br&gt;


&lt;i&gt;duplicate entries: &lt;/i&gt; Digital libraries that draw documents from a variety of sources&lt;br&gt;


may  inadvertently  contain  duplicate  items.    Unfortunately,  the  irregular&lt;br&gt;


formatting of the bibliographic information makes it difficult to  automatically&lt;br&gt;


detect these duplicates.&lt;br&gt;


•&lt;br&gt;


&lt;i&gt;implicit field tagging:&lt;/i&gt;  In some repositories, items are not explicitly tagged with&lt;br&gt;


certain  types  of  information  –  most  commonly  the  document's  date  of&lt;br&gt;


publication or production.  Instead, the date is implicit in the document's title&lt;br&gt;


(eg, its numeration in a technical report series) or in the location of the document&lt;br&gt;


in the file structure of the repository  (eg,  separate  directories  exist  for  each&lt;br&gt;


year).  A second common piece of  implicit  data  is  the  authors’  institutional&lt;br&gt;


affiliations.  This may be contained in the document itself (typically on a cover&lt;br&gt;


page),  or  may  be  implicit  in  the  document’s  location  (for  example,  a&lt;br&gt;


corporation’s technical reports are stored in its ftp repository).  Again, in these&lt;br&gt;


&lt;hr&gt;


&lt;A name=8&gt;&lt;/a&gt;cases  special  processing  is  required  to  append  this  field  information  to  a&lt;br&gt;


document record for bibliometric analysis.  &lt;br&gt;


•&lt;br&gt;


&lt;i&gt;extraction of document text:&lt;/i&gt;  Few of  the  documents  stored  in  the  research-&lt;br&gt;


oriented digital libraries discussed in this paper are straight ascii text; instead,&lt;br&gt;


documents may appear in a variety of file formats, such as LaTeX, PostScript,&lt;br&gt;


PDF, etc.  If the contents of the documents are to be automatically processed&lt;br&gt;


(for  example,  to  count  the  words  in  a  document,  or  to  extract  reference&lt;br&gt;


publication dates for an obsolescence study), then the text must be extracted.&lt;br&gt;


Utilities are available to convert most common document formats to ascii.&lt;br&gt;


It is likely that many of these problems will be addressed as the Internet-based&lt;br&gt;


document indexing systems mature.  Even minor changes can greatly increase the&lt;br&gt;


useability of a bibliographic database for bibliometric research.  For example, the&lt;br&gt;


addition of an explicit date tag to many online databases in 1975 sparked new&lt;br&gt;


applications in time series research [3].&lt;br&gt;


&lt;b&gt;3.  Opportunities for applications of bibliometric techniques&lt;/b&gt;&lt;br&gt;


One type of bibliometric research concentrates on quantifying fundamental,&lt;br&gt;


structural details about a subject literature:  how many items are published, how many&lt;br&gt;


authors are publishing, over what time period documents are likely to be used, etc.&lt;br&gt;


More complex studies analyze the relationships between documents, such as how&lt;br&gt;


documents cluster into subjects.  The following examples give a flavour of the&lt;br&gt;


bibliometric research that is possible using the emerging digital libraries:&lt;br&gt;


&lt;i&gt;examining the “physical” characteristics of archived documents&lt;/i&gt;&lt;br&gt;


One relatively straightforward type of bibliometric study characterizes the&lt;br&gt;


formats of different literatures.   For example, Figure 1 presents a the range of the size&lt;br&gt;


&lt;hr&gt;


&lt;A name=9&gt;&lt;/a&gt;of computer science technical reports as measured by their length in pages.   Of the&lt;br&gt;


45,720 documents in the CSTR collection as of April 1998, nearly 1600 did not contain&lt;br&gt;


page divisions in their files (and hence are excluded from analysis). Note that the&lt;br&gt;


number of pages in the shorter documents (&amp;lt;50 pages) falls into an approximately&lt;br&gt;


normal distribution (slightly skewed to the left), while presumably the longer&lt;br&gt;


documents represent Masters’ and Doctoral theses. A surprising number of documents&lt;br&gt;


are very short (between one and 5 pages); these may represent the type of condensed&lt;br&gt;


results frequently found in the “technical notes”, “short papers”, and “poster sessions”&lt;br&gt;


of computing conferences and journals. The average number of pages per document,&lt;br&gt;


27.5, appears to be slightly longer than the common upper bound for a computing&lt;br&gt;


journal article, although this observation must be confirmed by a similar study of the&lt;br&gt;


lengths of formally published computing articles.&lt;br&gt;


This type of analysis is of particular interest for technical reports, since they&lt;br&gt;


have not been studied in the same detail as formally published papers.  A comparison of&lt;br&gt;


the physical characteristics of the formal and informal literature could provide&lt;br&gt;


supporting evidence for common beliefs about the relationship between the two types&lt;br&gt;


of documents. For example,  do publishing constraints force journal and proceedings&lt;br&gt;


articles to be shorter than technical reports, and therefore presumably omit technical&lt;br&gt;


details of findings?  Do technical reports contain more/less extensive reference sections?&lt;br&gt;


If reference sections of technical reports are longer than those of published articles, then&lt;br&gt;


citation links are being ommitted in published works; if technical reports contain fewer&lt;br&gt;


references, then this may confirm earlier indications that computer scientists tend to&lt;br&gt;


“research first” and do literature surveys later [6].&lt;br&gt;


Figure 1.  Range of sizes of CS technical reports, measured by number of pages&lt;br&gt;


&lt;i&gt;obsolescence studies.&lt;/i&gt;&lt;br&gt;


A document is considered obsolete when it is no longer referenced by the&lt;br&gt;


current literature. Typically, documents receive their greatest number and frequency of&lt;br&gt;


&lt;hr&gt;


&lt;A name=10&gt;&lt;/a&gt;citations immediately after publication, and the frequency of citation falls rapidly as time&lt;br&gt;


passes. One technique for estimating the obsolescence rate of a body of  literature– the&lt;br&gt;


&lt;i&gt;synchronous&lt;/i&gt; method –  is to find the median date in the references of the documents.&lt;br&gt;


This median date is subtracted from the year of publication for the documents, yielding&lt;br&gt;


the &lt;i&gt;median citation age&lt;/i&gt;.  As would be expected, this median varies between the&lt;br&gt;


disciplines.  Typically the social sciences and arts have a higher median citation age&lt;br&gt;


than the “hard” sciences and engineering, indicating that documents obsolesce more&lt;br&gt;


quickly for the latter fields.&lt;br&gt;


As noted in Section 2, references are not generally explicitly tagged in existing&lt;br&gt;


digital repositories.  However, reference dates can usually be extracted from the&lt;br&gt;


document text by first locating the reference section (usually delimited by a &amp;quot;references&amp;quot;&lt;br&gt;


or &amp;quot;bibliography&amp;quot; section heading), and then extracting all numbers in the appropriate&lt;br&gt;


ranges for dates  for the field under study.&lt;br&gt;


To illustrate this process, 188 technical reports were sampled from Internet-&lt;br&gt;


accessible repositories1 and used as source documents for a synchronous obsolescence&lt;br&gt;


study.  Conveniently, the repositories chosen organize technical reports into sub-&lt;br&gt;


directories by their date of publication.  The reference dates for each technical report&lt;br&gt;


were automatically extracted by software that scanned the document’s file for numbers&lt;br&gt;


of the form 19XX, since previous studies indicate that few if any computing reports&lt;br&gt;


reference documents published in previous centuries [5].  Table 1 presents the median&lt;br&gt;


citation age calculated for these documents, broken down by repository and the year of&lt;br&gt;


publication for the source documents from which the reference dates were extracted:&lt;br&gt;


Table 1.  Median citation ages for technical report repositories&lt;br&gt;


The median citation age ranges between 2 and 4 years, which is consistent with&lt;br&gt;


previous examinations of computing and information systems literature ([5], [4]).&lt;br&gt;


When graphed, the distribution of reference dates show the exponential curve typically&lt;br&gt;


found in obsolescence studies, including the final droop due to an “immediacy effect”&lt;br&gt;


&lt;hr&gt;


&lt;A name=11&gt;&lt;/a&gt;as fewer very new documents are available for citation [7].  These types of results&lt;br&gt;


provide confirmation that references used in computer science technical reports (the pre-&lt;br&gt;


eminent “grey literature” of  the computing field) conforms to the same patterns as&lt;br&gt;


references found in the formally published literature.&lt;br&gt;


&lt;i&gt;co-citation and bibliographic coupling studies&lt;/i&gt;&lt;br&gt;


The rate at which documents cite each other (co-citation) or cite the same&lt;br&gt;


documents (bibliographic coupling) can be used to produce &amp;quot;maps&amp;quot; of a subject&lt;br&gt;


literature.  These techniques rely on analysis of the references of documents, and these&lt;br&gt;


references must be in a common format.  While digital libraries contain full text of&lt;br&gt;


documents, their references are not standardized, and indeed are not  even tagged as&lt;br&gt;


such.  To perform these studies the references must be manually extracted and&lt;br&gt;


processed–a tedious process that is only worthwhile for documents (such as technical&lt;br&gt;


reports) that are not included in existing citation databases such as the Science Citation&lt;br&gt;


Index and Social Science Citation Index.&lt;br&gt;


&lt;i&gt;detecting cycles or regularities in the rate of production of research&lt;/i&gt;&lt;br&gt;


Analysis of trends in the production of technical reports can give indications&lt;br&gt;


about working conditions that affect research; for example, is more research produced&lt;br&gt;


over the summer, when the teaching load is lighter?  or is research steadily produced&lt;br&gt;


throughout the year?&lt;br&gt;


Figure 2.  Distribution of the number of documents submitted to hep-th, 1992-1994&lt;br&gt;


Figures 2 and 3 present statistics on document accumulation in the hep-th (high&lt;br&gt;


energy physics) e-print server, a part of the PHYSICS E-PRINT ARCHIVE.  This system&lt;br&gt;


is one of the oldest formal pre-print archives, and has become the primary means for&lt;br&gt;


information dissemination in its field.  Examination of these figures reveals several&lt;br&gt;


trends.  Clearly the absolute number of documents deposited in the repository has&lt;br&gt;


&lt;hr&gt;


&lt;A name=12&gt;&lt;/a&gt;tended to increase over the time period.  For all three years, research production has its&lt;br&gt;


lowest point in January and February, increases through May and June, then decreases&lt;br&gt;


until August and September.  At that point the rate of production steps up, reaching a&lt;br&gt;


yearly peak in November and December.  This pattern is less clear for 1992, which&lt;br&gt;


might be expected as the archive was established in mid-1991.&lt;br&gt;


Figure 3.  Distribution of the percentage of documents submitted to hep-th, 1992-1994&lt;br&gt;


&lt;b&gt;4.  Analysis of usage data&lt;/b&gt;&lt;br&gt;


The emerging Internet-based digital libraries will permit research on scientific&lt;br&gt;


information collection and use at a much finer grain than is possible with current paper&lt;br&gt;


libraries or online bibliographic databases.  Current bibliometric or scientometric&lt;br&gt;


research of this type must measure information use indirectly – for example,  through&lt;br&gt;


examination of the list of references appended to published articles.  However, it is well&lt;br&gt;


known that authors do not necessarily include in the reference list all documents that&lt;br&gt;


could have been cited, and conversely that not all references listed may have been&lt;br&gt;


actually “used” in performing the research; citation behavior can be affected by a&lt;br&gt;


number of motivating factors (Garfield lists &lt;i&gt;15&lt;/i&gt; possible reasons in [8]).&lt;br&gt;


Digital library transaction logs provide a powerful tool for direct analysis of&lt;br&gt;


document “usage”: since  digital libraries contain the actual document (rather than only a&lt;br&gt;


document surrogate), the relative amount of “use” that a digital library’s clients make of&lt;br&gt;


a given document sees can be estimated from the number of times the document file is&lt;br&gt;


downloaded (and, presumably, the document is read). Note that file downloading is a&lt;br&gt;


much stronger statement on the part of the user than, for example, having a&lt;br&gt;


bibliographic record appear in the query result set for a conventional bibliographic&lt;br&gt;


system; the user downloads only &lt;i&gt;after&lt;/i&gt; the document has been found potentially relevant&lt;br&gt;


through examination of its document surrogate. Additionally,  downloading is&lt;br&gt;


frequently time-consuming  and sometimes costly (depending on local pricing for&lt;br&gt;


&lt;hr&gt;


&lt;A name=13&gt;&lt;/a&gt;Internet access). Downloaded documents are therefore highly likely at least to be&lt;br&gt;


scanned, if not read closely.  The transaction logs for a digital library can provide a&lt;br&gt;


global picture of the use of documents in the collection, since all user interactions with&lt;br&gt;


the library can be automatically logged  for analysis. By contrast, it is of course&lt;br&gt;


impossible to track usage of print bibliographies, and very difficult to monitor usage of&lt;br&gt;


bibliographic data available on CD-ROM across more than one or two sites.&lt;br&gt;


Furthermore, analysis of search requests by geographic location, institution,&lt;br&gt;


and sometimes even individual user are also possible.  As an example, Table 2 presents&lt;br&gt;


a portion of the summary of usage statistics (broken down by domain code) for queries&lt;br&gt;


to the computer science technical collection of the NEW ZEALAND DIGITAL LIBRARY.&lt;br&gt;


Examination of the data indicates that the heaviest use of the collection comes from&lt;br&gt;


North America, Europe (particularly Germany and Finland), as well as the local New&lt;br&gt;


Zealand community and nearby Australia.  As expected for such a collection, a large&lt;br&gt;


proportion of users are from educational (.edu) institutions; surprisingly, however, a&lt;br&gt;


similar number of queries come from commercial (.com) organizations, indicating&lt;br&gt;


perhaps that the documents are seeing use in commercial research and development&lt;br&gt;


units.&lt;br&gt;


Table 2. Accesses to the NEW ZEALAND DIGITAL LIBRARY CS collection  by Domain&lt;br&gt;Code&lt;br&gt;


Of course, usage levels can also be further broken down by IP number&lt;br&gt;


(indicating  institutions), and systems requiring users to register may also be able to&lt;br&gt;


analyze usage on an individual basis. Since the query strings themselves are also&lt;br&gt;


recorded in the transaction logs, this domain/institution/individual activity could also be&lt;br&gt;


linked to specific subjects through the query terms.  Summaries of this type could be&lt;br&gt;


invaluable for studies of geographic diffusion and distribution of research topics.&lt;br&gt;


Transaction log analysis can also indicate time-related  patterns in the&lt;br&gt;


information seeking behavior of digital library users.   As a sample of this type of&lt;br&gt;


analysis,  Paul Ginsparg notes a seven day periodicity in the number of search requests&lt;br&gt;


&lt;hr&gt;


&lt;A name=14&gt;&lt;/a&gt;made to the PHYSICS E-PRINT archives (Figure 4, reproduced from [9]).  From this he&lt;br&gt;


adduces that many physicists do not yet have weekend access to the Internet (an&lt;br&gt;


alternative, slightly more cynical hypothesis is that even high energy theoretical&lt;br&gt;


physicists take the weekend off).&lt;br&gt;


Figure 4.  Summary of search requests to the physics pre-print archives&lt;br&gt;


&lt;b&gt;5.  Conclusion&lt;/b&gt;&lt;br&gt;


This study suggests opportunities for conducting bibliometric research on the&lt;br&gt;


evolving digital libraries.  These repositories are suitable platforms for conventional&lt;br&gt;


bibliometric techniques (such as obsolescence studies, quantification of physical&lt;br&gt;


characteristics of documents comprising a subject literature, time analysis, etc.).  The&lt;br&gt;


ability to directly monitor access to documents in digital libraries also enables&lt;br&gt;


researchers to explicitly quantify document usage, as well as to implicitly measure&lt;br&gt;


usage through citations.  Additional facilities could aid in the performance of&lt;br&gt;


bibliographic experiments, such as: improved tagging of document fields; provision of&lt;br&gt;


utilities to strip out titles, authors, etc. from common document formats; and the ability&lt;br&gt;


to easily eliminate duplicate entries from downloaded library subsets.  Unfortunately,&lt;br&gt;


the most useful of these additional facilities – those associated with a higher degree of&lt;br&gt;


cataloging – run counter to the underlying philosophy of many digital libraries:  to&lt;br&gt;


avoid, if possible,  manual processing and formal cataloging of documents.   While&lt;br&gt;


adherence to this principle can limit the accuracy of fielded searching (or indeed,&lt;br&gt;


preclude it altogether), it can also avoid the cataloging bottleneck and permit digital&lt;br&gt;


libraries to provide access to larger numbers of documents.&lt;br&gt;


The digital libraries complement the information currently available through&lt;br&gt;


paper, online, and CD-ROM bibliographic resources.  While these latter databases&lt;br&gt;


generally have the advantage of standardized formatting of bibliographic fields, the&lt;br&gt;


digital libraries are freely accessible, often contain &amp;quot;grey literature&amp;quot; that is otherwise&lt;br&gt;


&lt;hr&gt;


&lt;A name=15&gt;&lt;/a&gt;unavailable for analysis, and generally make the full text of documents available.  The&lt;br&gt;


insights gained from analysis of digital libraries will add to the store of &amp;quot;information&lt;br&gt;


about information&amp;quot; that we have gained from older types of bibliographic repositories.&lt;br&gt;


&lt;b&gt;References&lt;/b&gt;&lt;br&gt;


[1] Bollacker, K.D., S. Lawrence, and C.L.Giles, CiteSeer: An Autonomous Web&lt;br&gt;


Agent for Automatic  Retrieval  and  Identification  of  Interesting  Publications,&lt;br&gt;


&lt;i&gt;Proceedings of the Second International Conference  on  Autonomous  Agents&lt;/i&gt;&lt;br&gt;


(Minneapolis/St. Paul, May 9-13), 1998.&lt;br&gt;


[2] Bowman, C.M., P.B. Danzig, U. Manber,  and M.F. Schwartz,  Scalable Internet&lt;br&gt;


resource discovery:  Research problems and approaches,  &lt;i&gt;Communications of&lt;/i&gt;&lt;br&gt;


&lt;i&gt;the ACM 37(8)&lt;/i&gt;  (1994)  98-107.&lt;br&gt;


[3] Burton, Hilary D. , Use of a virtual information system for bibliometric analysis,&lt;br&gt;


&lt;i&gt;Informaton Processing &amp;amp; Management 24(1)&lt;/i&gt;  (1988) 39-44.&lt;br&gt;


[4] Cunningham, S.J., An empirical investigation of the obsolescence rate for&lt;br&gt;


information systems literature, &lt;i&gt;Library and Information Science&lt;/i&gt;&lt;br&gt;


&lt;i&gt;Research&lt;/i&gt;., 1996, http://library.fgcu.edu/iclc/lisrissu.htm&lt;br&gt;


 [5]  Cunningham,  S.J.,  and  D.  Bocock,    Obsolescence  of  computing  literature.&lt;br&gt;


&lt;i&gt;Scientometrics&lt;/i&gt;  &lt;i&gt;34(2) &lt;/i&gt; (1995), pp. 255-262.&lt;br&gt;


 [6] Cunningham, S.J. and Lynn Silipigni Connaway, Information searching&lt;br&gt;


preferences and practices of computer science researchers, &lt;i&gt;Proceedings of&lt;/i&gt;&lt;br&gt;


&lt;i&gt;OZCHI '96&lt;/i&gt; (1996)  294-299.&lt;br&gt;


[7] de Solla Price, D.J.,  Citation measures of hard science, soft science, technology,&lt;br&gt;


and nonscience.  In: C.E. Nelson  and  D.K.  Pollock  (eds),  &lt;i&gt;Communication&lt;/i&gt;&lt;br&gt;


&lt;i&gt;among scientists and engineers&lt;/i&gt;  (Heath Lexington, 1970).&lt;br&gt;


[8]  Garfield, E., &lt;i&gt;Citation Indexing:  Its theory and application in Science, Technology&lt;/i&gt;&lt;br&gt;


&lt;i&gt;and Humanities (&lt;/i&gt;Wiley, 1979).&lt;br&gt;


&lt;hr&gt;


&lt;A name=16&gt;&lt;/a&gt;[9]  Ginsparg, P.  After dinner remarks:  14 Oct ‘94 APS meeting at LANL, 1994&lt;br&gt;


(&amp;lt;URL: http://xxx.lanl.gov/blurb&amp;gt; ).&lt;br&gt;


[10] Ginsparg, P., First steps towards electronic research communication, &lt;i&gt;Computers&lt;/i&gt;&lt;br&gt;


&lt;i&gt;in Physics 8(4)&lt;/i&gt; (1994)  390-401.  &lt;br&gt;


[11] Hallmark,  J., Scientists' access and retrieval of references cited in their recent&lt;br&gt;


journal articles, &lt;i&gt; College and Research Libraries 55(3)&lt;/i&gt;  (1994) 199-210.&lt;br&gt;


[12] Hawkins, D.T. , Unconventional uses of on-line information retrieval systems:&lt;br&gt;


on-line bibliometric studies,  &lt;i&gt;Journal of the American Society for Information&lt;/i&gt;&lt;br&gt;


&lt;i&gt;Science 28&lt;/i&gt;  (1977)  13-18.&lt;br&gt;


[13] McGhee, P.E. , P.R. Skinner, K. Roberto,  N.J. Ridenour,  and S.M. Larson,&lt;br&gt;


Using online databases to study current research trends:  an online bibliometric&lt;br&gt;


study, &lt;i&gt;Library and Information Science Research 9&lt;/i&gt;  (1987)   285-291.&lt;br&gt;


[14] Maly, K., E.A. Fox,  J.C. French,  and A.L. Selman,  Wide area technical report&lt;br&gt;


server    (&lt;i&gt;Technical    Report  ,  &lt;/i&gt;  Dept.  of  Computer  Science,  Old  Dominion&lt;br&gt;


University, &lt;br&gt;


1994. &lt;br&gt;


Also &lt;br&gt;


available &lt;br&gt;


at &lt;br&gt;


 &lt;br&gt;


 &lt;br&gt;


&amp;lt;URL:&lt;br&gt;


http://www.cs.odu.edu/WATERS/WATERS-paper.ps&amp;gt; ).&lt;br&gt;


[15] Sigogneau, M.J. , S. Bain, J.P. Courtial, and H. Feillet,  Scientific innovation in&lt;br&gt;


bibliographical databases:  a comparative study of the Science Citation Index&lt;br&gt;


and the Pascal database,  &lt;i&gt;Scientometrics 22(1)&lt;/i&gt;   (1991)  65-82.&lt;br&gt;


[16] Witten, I.H., S.J. Cunningham, M. Vallabh,  and T.C. Bell,  A New Zealand&lt;br&gt;


digital library for computer science research,  &lt;i&gt;Proceedings of Digital Libraries&lt;/i&gt;&lt;br&gt;


&lt;i&gt;'95&lt;/i&gt; (1995) 25-30.&lt;br&gt;


[17]  Witten, I.H., C. Nevill-Manning, and S.J. Cunningham, A public library based&lt;br&gt;


on full-text retrieval, &lt;i&gt;Communications of the ACM&lt;/i&gt; 41(4), 1998, p. 71&lt;br&gt;


&lt;hr&gt;


&lt;A name=17&gt;&lt;/a&gt;                                    &lt;br&gt;


1Documents were randomly sampled from the DEC&lt;br&gt;


(ftp://crl.dec.com/pub/DEC/CRL/tech-reports/), Sony&lt;br&gt;


(ftp://ftp.csl.sony.co.jp/CSL/CSL-Papers), and Ohio (ftp://archive.cis.ohio-&lt;br&gt;


state.edu/pub/tech-report/) technical report repositories&lt;br&gt;


&lt;hr&gt;








</Content>
</Section>
</Archive>