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53 | <A name=1></a><b>Applications for Bibliometric Research</b><br>
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54 | <b>in the Emerging Digital Libraries</b><br>
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55 | Sally Jo Cunningham<br>
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56 | Department of Computer Science<br>
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57 | University of Waikato<br>
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58 | Hamilton, New Zealand<br>
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59 | email: [email protected]<br>
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60 | <b>Abstract:</b> Large numbers of research documents have recently become available on<br>
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61 | the Internet through âdigital librariesâ, and these collections are seeing high levels of<br>
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62 | use by their related research communities. A secondary use for these document<br>
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63 | repositories and indexes is as a platform for bibliometric research. We examine the<br>
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64 | extent to which the new digital libraries support conventional bibliometric analysis, and<br>
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65 | discuss shortcomings in their current forms. Interestingly, these electronic text<br>
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66 | archives also provide opportunities for new types of studies: generally the full text of<br>
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67 | documents are available for analysis, giving a finer grain of insight than abstract-only<br>
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68 | online databases; these repositories often contain technical reports or pre-prints, the<br>
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69 | âgrey literatureâ that has been previously unavailable for analysis; and document<br>
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70 | âusageâ can be measured directly by recording user accesses, rather than studied<br>
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71 | indirectly through document references.<br>
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72 | <b>1. Introduction</b><br>
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73 | In recent years a number of &quot;digital libraries&quot; have become available through the<br>
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74 | Internet. While the technology promises in the future to support large, heterogenous<br>
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75 | collections, at present the most widely used of the academically-focussed digital<br>
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76 | libraries are generally repositories of one or two types of document (typically technical<br>
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77 | reports, journal articles, pre-prints, or conference proceedings), grouped by discipline.<br>
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78 | <hr>
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79 | <A name=2></a>A distinguishing characteristic of these digital libraries is that the full text of documents<br>
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80 | are often available for retrieval, as well as bibliographic records.The sciences are<br>
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81 | represented much more heavily in the present crop of digital libraries than the social<br>
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82 | sciences, arts, or humanities. They are maintained by professional societies,<br>
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83 | universities, research laboratories, and even private individuals. Access is generally<br>
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84 | free, both to search and to download documents.<br>
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85 | The emergence of these subject-specific digital libraries is particularly important<br>
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86 | given the pattern of access to materials presently employed by research scientists.<br>
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87 | Informal exchanges of preprints, reprints, and photocopies of papers passed on by<br>
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88 | colleagues currently are major venues for the transmission of scientific information<br>
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89 | between researchers in the sciences. In one study, the dependence on these sources<br>
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90 | ranges from 12% (for chemistry) to 39% (for mathematics) of all papers cited in<br>
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91 | researchers' own publications [11]. A qualitative study of study of how computer<br>
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92 | scientists locate and retrieve documents (computing is one of the domains considered<br>
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93 | later in this paper) indicates that for that field, technical reports and research documents<br>
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94 | found in various locations on the Internet are a preferred source of information [6].<br>
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95 | Many of the digital library systems discussed in this paper are repositories for just this<br>
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96 | type of literature. The documents tend to be of high quality: primarily technical<br>
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97 | reports or working papers from research institutions (both academic and commercial),<br>
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98 | as well as advance copies of work accepted for publication in conventional paper<br>
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99 | journals. Moreover, these digital libraries are also coming to include refereed work<br>
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100 | published digitally (in electronic journals). Anecdotal evidence suggests that in their<br>
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101 | fields, these digital libraries are coming to be the resource of choice for locating cutting<br>
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102 | edge work.<br>
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103 | For specialized subjects such as high energy physics, this dependence on<br>
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104 | informal or extra-library dissemination can be much higher. Ginsparg ([9], [10])<br>
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105 | reports that fields in physics have traditionally relied heavily on preprint exchanges, and<br>
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106 | the digital repositories of physics preprints begun in 1991 (the PHYSICS E-PRINT<br>
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107 | ARCHIVES) have to a large extent supplanted conventional publishing and physical<br>
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108 | <hr>
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109 | <A name=3></a>paper mailing of technical reports. By providing ready access to information sources<br>
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110 | that are already preferentially utilized by scientists, the digital libraries show potential to<br>
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111 | increase access to information that until recently was expensive or difficult to acquire in<br>
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112 | paper form. Indeed, in some fields (most notably physics) this process has already<br>
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113 | begun, as researchers in less developed countries report access to ongoing research<br>
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114 | through the Internet repositories that their local libraries could not afford to acquire<br>
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115 | through conventional journal subscriptions ([9], [10]).<br>
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116 | The primary use for new bibliographic resources is, of course, for the contents<br>
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117 | of the documents involved. A secondary use for emerging resources is as a basis for<br>
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118 | bibliometric analysis of the subject field. With the conventionally published scientific<br>
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119 | literature, the sheer difficulty of accumulating statistics discouraged bibliometric<br>
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120 | research until the advent of large bibliographic databases in the 1960's. Computerized<br>
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121 | bibliographic databases sparked a significant increase in the number of large-scale<br>
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122 | bibliographic studies, as significant portions of the collection and analysis of data could<br>
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123 | be automated ([12], [13]). The availability of CD-ROM versions of bibliographic<br>
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124 | databases has been of particular importance, since they provide a cheaper alternative to<br>
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125 | the online commercial databases [3].<br>
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126 | These computerized bibliographic resources have drawbacks, however. The<br>
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127 | greatest is that the full text of documents are rarely available, and even abstracts are not<br>
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128 | always present. This obviously limits the types of bibliometric research that can be<br>
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129 | conducted <i>solely</i> through these databases. In addition, these databases are generally<br>
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130 | limited to formally published documents (those appearing in selected books, journals,<br>
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131 | and conference proceedings). The &quot;grey literature&quot; of technical reports, pre-prints, and<br>
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132 | other works not formally published are largely ignored, and it is this absence of easy<br>
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133 | access to these documents that has hampered the analysis of these important forms of<br>
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134 | scientific communication.<br>
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135 | The digital libraries currently in existence complement the online and CD-ROM<br>
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136 | bibliographic databases. They are best suited for examinations of the &quot;physical&quot;<br>
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137 | characteristics of documents (for example, document length), analysis based on<br>
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138 | <hr>
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139 | <A name=4></a>bibliographic information that can be automatically extracted from the document text or<br>
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140 | the sometimes unevenly formatted bibliographic records (such as obsolescence<br>
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141 | studies), and usage studies (geographic or institutional origin of users, date/time of<br>
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142 | access, individual patterns of document retrieval, etc.). Because references are present<br>
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143 | in the document file but not identified by field, co-citation and bibliographic coupling<br>
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144 | research is not well-supported, and conducting these studies requires considerable<br>
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145 | effort on the part of the researcher.<br>
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146 | The variety of bibliographic repositories in the available digital libraries in itself<br>
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147 | has great potential in conducting bibliometric research. Sigogneau et al [15] present a<br>
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148 | case study illustrating the ways in which the strengths of different databases can be<br>
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149 | played off each other; they conduct a fine-grained analysis of the emergence of research<br>
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150 | fronts in molecular and cellular biology, and demonstrate that the observations gleaned<br>
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151 | from two complementary bibliographic databases provide greater insight into their<br>
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152 | problem. Similarly, it appears that the types of bibliographic data that can be gleaned<br>
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153 | from the relatively unstructured digital libraries can be profitably combined with data<br>
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154 | from online databases, CD-ROMS, and other more conventional bibliographic<br>
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155 | resources.<br>
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156 | This paper is organized as follows: Section 2 discusses the types of indexing<br>
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157 | and searching available with current digital libraries; Section 3 gives examples of<br>
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158 | conventional bibliometric techniques applied to Internet-accessible archives; Section 4<br>
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159 | discusses opportunities to directly measure usage of documents and to detect<br>
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160 | information-seeking patterns in researchers; and Section 5 presents our conclusions.<br>
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161 | <b>2. Indexing and searching in current digital libraries</b><br>
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162 | At present, the types of indexing fields for most academically-oriented digital<br>
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163 | library systems are limited. Many schemes index on user-supplied document<br>
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164 | descriptions, abstracts, or similar document surrogates (for example, the PHYSICS E-<br>
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165 | PRINT ARCHIVE [10], a collection of physics pre-prints and technical reports). As will<br>
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166 | <hr>
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167 | <A name=5></a>be discussed below, the quality of this user-provided data can be highly variable, and<br>
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168 | may unfavorably impact the usefulness of the index for searching. Alternatively, a<br>
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169 | designated site librarian may maintain a catalog (eg, the WATERS [14] system, now<br>
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170 | subsumed by NCSTRL (http://www.ncstrl.org/), both primarily collections of<br>
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171 | computer science technical reports); in this case the quality of the bibliographic<br>
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172 | information may be expedited to be higher, but fewer sites will be likely to support<br>
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173 | such a librarian and therefore fewer documents are likely to be included in the digital<br>
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174 | library. In a âharvestingâ system such as the computer science technical report<br>
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175 | collections supported by HARVEST [2] or the NEW ZEALAND DIGITAL LIBRARY<br>
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176 | computer science technical report collection ([16], [17]), documents are indexed from<br>
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177 | passive repositories (that may not even be aware that their documents are being<br>
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178 | included in the digital library). Harvesting systems therefore cannot rely on the<br>
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179 | presence of bibliographic data of any sort.<br>
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180 | Because of the relative paucity of high-quality bibliographic data available to<br>
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181 | many of the current academically- or research-focussed digital library collections, their<br>
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182 | search interfaces tend to be more primitive than those ordinarily found in online<br>
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183 | bibliographic databases or library catalogs. Systems such as NCSTRL can support<br>
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184 | author, title, and subject searching, but this more sophisticated search functionality<br>
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185 | comes at the expense of requiring participating repositories to use specific software. As<br>
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186 | a consequence, these latter systems may provide access to a small number of sites than<br>
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187 | harvesting systems. Harvesters may access a broader range of providers, but at the<br>
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188 | penalty of being limited to unfielded, keyword searches over the raw text of the<br>
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189 | document or document surrogate.<br>
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190 | Specifically, the indexing in existing digital libraries has a variety of shortcomings for<br>
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191 | bibliometric applications:<br>
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192 | â¢<br>
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193 | <i>lack of fielded indexing:</i> As noted above, some large and widely used digital<br>
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194 | libraries (such as the computer science technical report collection of the NEW<br>
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195 | ZEALAND DIGITAL LIBRARY) may lack formal cataloging entirely, and rely on<br>
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196 | <hr>
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197 | <A name=6></a>keyword searching over the raw document text. Obviously this makes field-<br>
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198 | dependent analysis more difficult (for example, locating documents produced by<br>
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199 | specific authors), and in the worst case my require a manual examination of all<br>
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200 | files in the collection in order to reliably identify a desired document subset.<br>
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201 | However, keyword search techniques that approximate fielded searching results<br>
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202 | may suffice: for example in the NEW ZEALAND DIGITAL LIBRARY computer<br>
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203 | science technical report collection, limiting the keyword search for âJohnsonâ<br>
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204 | to a search of first pages only is likely to retrieve documents written by Johnson<br>
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205 | (since for the majority of computer science technical reports, the first page<br>
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206 | contains little more than author, title, date, and institution details).<br>
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207 | A more principled approach to extracting bibliographic information is embodied<br>
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208 | in the CiteSeer tool [1]. This software parses raw, unfielded academic<br>
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209 | documents and attempts to identify such indexing information as author, title,<br>
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210 | reference list, etc. Obviously such a tool cannot attain 100% accuracy over a<br>
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211 | heterogenous document collection, but in practice it appears useful in that it can<br>
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212 | make a good first pass in processing a set of documents, providing an initial set<br>
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213 | of parsed documents for analysis. The remaining (presumably much smaller) set<br>
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214 | of unparsable documents can then be dealt with manually.<br>
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215 | â¢<br>
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216 | <i>lack of consistency in field formatting:</i> Current digital libraries usually acquire<br>
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217 | bibliographic information from either the authors of submitted articles or<br>
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218 | automatic extraction routines (retrieving bibliographic details from catalog files<br>
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219 | that may or may not be in a given document site, and that may or may not be in<br>
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220 | an easily parsable form). Neither of these methods produce records with<br>
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221 | standard formatting, which causes problems with automated bibliometric<br>
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222 | analysis. Consider the following examples selected from entries in the hep-th<br>
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223 | (high energy physics) collection of the PHYSICS E-PRINT ARCHIVES:<br>
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224 | <hr>
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225 | <A name=7></a>(i)<br>
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226 | Authors: A. Yu. Alekseev, V. Schomerus<br>
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227 | (ii)<br>
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228 | Authors: Adel Bilal and Ian. I. Kogan<br>
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229 | (iii)<br>
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230 | Authors: Paul S. Aspinwall and David R. Morrison (with an appendix <br>
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231 | by Mark Gross)<br>
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232 | (iv)<br>
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233 | Authors: A. H. Chamseddine and Herbi Dreiner (ETH-Zurich)<br>
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234 | In this case, typical for existing digital libraries, there is no standardized format<br>
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235 | for authors' names (here, appearing with full names, initials plus last name, and<br>
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236 | a mixture of the two); no standard convention for separating author names<br>
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237 | (here, either a comma or &quot;and&quot; are used); and parenthetical information can<br>
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238 | include a variety of information such as the name of an associate author or the<br>
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239 | institutional affiliations of an author. Manual processing or specially crafted<br>
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240 | software would be required to reformat these fields for analysis.<br>
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241 | â¢<br>
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242 | <i>duplicate entries: </i> Digital libraries that draw documents from a variety of sources<br>
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243 | may inadvertently contain duplicate items. Unfortunately, the irregular<br>
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244 | formatting of the bibliographic information makes it difficult to automatically<br>
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245 | detect these duplicates.<br>
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246 | â¢<br>
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247 | <i>implicit field tagging:</i> In some repositories, items are not explicitly tagged with<br>
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248 | certain types of information â most commonly the document's date of<br>
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249 | publication or production. Instead, the date is implicit in the document's title<br>
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250 | (eg, its numeration in a technical report series) or in the location of the document<br>
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251 | in the file structure of the repository (eg, separate directories exist for each<br>
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252 | year). A second common piece of implicit data is the authorsâ institutional<br>
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253 | affiliations. This may be contained in the document itself (typically on a cover<br>
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254 | page), or may be implicit in the documentâs location (for example, a<br>
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255 | corporationâs technical reports are stored in its ftp repository). Again, in these<br>
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256 | <hr>
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257 | <A name=8></a>cases special processing is required to append this field information to a<br>
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258 | document record for bibliometric analysis. <br>
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259 | â¢<br>
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260 | <i>extraction of document text:</i> Few of the documents stored in the research-<br>
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261 | oriented digital libraries discussed in this paper are straight ascii text; instead,<br>
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262 | documents may appear in a variety of file formats, such as LaTeX, PostScript,<br>
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263 | PDF, etc. If the contents of the documents are to be automatically processed<br>
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264 | (for example, to count the words in a document, or to extract reference<br>
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265 | publication dates for an obsolescence study), then the text must be extracted.<br>
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266 | Utilities are available to convert most common document formats to ascii.<br>
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267 | It is likely that many of these problems will be addressed as the Internet-based<br>
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268 | document indexing systems mature. Even minor changes can greatly increase the<br>
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269 | useability of a bibliographic database for bibliometric research. For example, the<br>
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270 | addition of an explicit date tag to many online databases in 1975 sparked new<br>
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271 | applications in time series research [3].<br>
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272 | <b>3. Opportunities for applications of bibliometric techniques</b><br>
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273 | One type of bibliometric research concentrates on quantifying fundamental,<br>
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274 | structural details about a subject literature: how many items are published, how many<br>
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275 | authors are publishing, over what time period documents are likely to be used, etc.<br>
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276 | More complex studies analyze the relationships between documents, such as how<br>
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277 | documents cluster into subjects. The following examples give a flavour of the<br>
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278 | bibliometric research that is possible using the emerging digital libraries:<br>
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279 | <i>examining the âphysicalâ characteristics of archived documents</i><br>
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280 | One relatively straightforward type of bibliometric study characterizes the<br>
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281 | formats of different literatures. For example, Figure 1 presents a the range of the size<br>
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282 | <hr>
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283 | <A name=9></a>of computer science technical reports as measured by their length in pages. Of the<br>
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284 | 45,720 documents in the CSTR collection as of April 1998, nearly 1600 did not contain<br>
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285 | page divisions in their files (and hence are excluded from analysis). Note that the<br>
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286 | number of pages in the shorter documents (&lt;50 pages) falls into an approximately<br>
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287 | normal distribution (slightly skewed to the left), while presumably the longer<br>
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288 | documents represent Mastersâ and Doctoral theses. A surprising number of documents<br>
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289 | are very short (between one and 5 pages); these may represent the type of condensed<br>
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290 | results frequently found in the âtechnical notesâ, âshort papersâ, and âposter sessionsâ<br>
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291 | of computing conferences and journals. The average number of pages per document,<br>
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292 | 27.5, appears to be slightly longer than the common upper bound for a computing<br>
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293 | journal article, although this observation must be confirmed by a similar study of the<br>
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294 | lengths of formally published computing articles.<br>
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295 | This type of analysis is of particular interest for technical reports, since they<br>
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296 | have not been studied in the same detail as formally published papers. A comparison of<br>
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297 | the physical characteristics of the formal and informal literature could provide<br>
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298 | supporting evidence for common beliefs about the relationship between the two types<br>
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299 | of documents. For example, do publishing constraints force journal and proceedings<br>
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300 | articles to be shorter than technical reports, and therefore presumably omit technical<br>
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301 | details of findings? Do technical reports contain more/less extensive reference sections?<br>
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302 | If reference sections of technical reports are longer than those of published articles, then<br>
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303 | citation links are being ommitted in published works; if technical reports contain fewer<br>
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304 | references, then this may confirm earlier indications that computer scientists tend to<br>
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305 | âresearch firstâ and do literature surveys later [6].<br>
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306 | Figure 1. Range of sizes of CS technical reports, measured by number of pages<br>
|
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307 | <i>obsolescence studies.</i><br>
|
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308 | A document is considered obsolete when it is no longer referenced by the<br>
|
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309 | current literature. Typically, documents receive their greatest number and frequency of<br>
|
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310 | <hr>
|
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311 | <A name=10></a>citations immediately after publication, and the frequency of citation falls rapidly as time<br>
|
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312 | passes. One technique for estimating the obsolescence rate of a body of literatureâ the<br>
|
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313 | <i>synchronous</i> method â is to find the median date in the references of the documents.<br>
|
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314 | This median date is subtracted from the year of publication for the documents, yielding<br>
|
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315 | the <i>median citation age</i>. As would be expected, this median varies between the<br>
|
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316 | disciplines. Typically the social sciences and arts have a higher median citation age<br>
|
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317 | than the âhardâ sciences and engineering, indicating that documents obsolesce more<br>
|
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318 | quickly for the latter fields.<br>
|
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319 | As noted in Section 2, references are not generally explicitly tagged in existing<br>
|
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320 | digital repositories. However, reference dates can usually be extracted from the<br>
|
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321 | document text by first locating the reference section (usually delimited by a &quot;references&quot;<br>
|
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322 | or &quot;bibliography&quot; section heading), and then extracting all numbers in the appropriate<br>
|
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323 | ranges for dates for the field under study.<br>
|
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324 | To illustrate this process, 188 technical reports were sampled from Internet-<br>
|
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325 | accessible repositories1 and used as source documents for a synchronous obsolescence<br>
|
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326 | study. Conveniently, the repositories chosen organize technical reports into sub-<br>
|
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327 | directories by their date of publication. The reference dates for each technical report<br>
|
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328 | were automatically extracted by software that scanned the documentâs file for numbers<br>
|
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329 | of the form 19XX, since previous studies indicate that few if any computing reports<br>
|
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330 | reference documents published in previous centuries [5]. Table 1 presents the median<br>
|
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331 | citation age calculated for these documents, broken down by repository and the year of<br>
|
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332 | publication for the source documents from which the reference dates were extracted:<br>
|
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333 | Table 1. Median citation ages for technical report repositories<br>
|
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334 | The median citation age ranges between 2 and 4 years, which is consistent with<br>
|
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335 | previous examinations of computing and information systems literature ([5], [4]).<br>
|
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336 | When graphed, the distribution of reference dates show the exponential curve typically<br>
|
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337 | found in obsolescence studies, including the final droop due to an âimmediacy effectâ<br>
|
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338 | <hr>
|
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339 | <A name=11></a>as fewer very new documents are available for citation [7]. These types of results<br>
|
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340 | provide confirmation that references used in computer science technical reports (the pre-<br>
|
---|
341 | eminent âgrey literatureâ of the computing field) conforms to the same patterns as<br>
|
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342 | references found in the formally published literature.<br>
|
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343 | <i>co-citation and bibliographic coupling studies</i><br>
|
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344 | The rate at which documents cite each other (co-citation) or cite the same<br>
|
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345 | documents (bibliographic coupling) can be used to produce &quot;maps&quot; of a subject<br>
|
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346 | literature. These techniques rely on analysis of the references of documents, and these<br>
|
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347 | references must be in a common format. While digital libraries contain full text of<br>
|
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348 | documents, their references are not standardized, and indeed are not even tagged as<br>
|
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349 | such. To perform these studies the references must be manually extracted and<br>
|
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350 | processedâa tedious process that is only worthwhile for documents (such as technical<br>
|
---|
351 | reports) that are not included in existing citation databases such as the Science Citation<br>
|
---|
352 | Index and Social Science Citation Index.<br>
|
---|
353 | <i>detecting cycles or regularities in the rate of production of research</i><br>
|
---|
354 | Analysis of trends in the production of technical reports can give indications<br>
|
---|
355 | about working conditions that affect research; for example, is more research produced<br>
|
---|
356 | over the summer, when the teaching load is lighter? or is research steadily produced<br>
|
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357 | throughout the year?<br>
|
---|
358 | Figure 2. Distribution of the number of documents submitted to hep-th, 1992-1994<br>
|
---|
359 | Figures 2 and 3 present statistics on document accumulation in the hep-th (high<br>
|
---|
360 | energy physics) e-print server, a part of the PHYSICS E-PRINT ARCHIVE. This system<br>
|
---|
361 | is one of the oldest formal pre-print archives, and has become the primary means for<br>
|
---|
362 | information dissemination in its field. Examination of these figures reveals several<br>
|
---|
363 | trends. Clearly the absolute number of documents deposited in the repository has<br>
|
---|
364 | <hr>
|
---|
365 | <A name=12></a>tended to increase over the time period. For all three years, research production has its<br>
|
---|
366 | lowest point in January and February, increases through May and June, then decreases<br>
|
---|
367 | until August and September. At that point the rate of production steps up, reaching a<br>
|
---|
368 | yearly peak in November and December. This pattern is less clear for 1992, which<br>
|
---|
369 | might be expected as the archive was established in mid-1991.<br>
|
---|
370 | Figure 3. Distribution of the percentage of documents submitted to hep-th, 1992-1994<br>
|
---|
371 | <b>4. Analysis of usage data</b><br>
|
---|
372 | The emerging Internet-based digital libraries will permit research on scientific<br>
|
---|
373 | information collection and use at a much finer grain than is possible with current paper<br>
|
---|
374 | libraries or online bibliographic databases. Current bibliometric or scientometric<br>
|
---|
375 | research of this type must measure information use indirectly â for example, through<br>
|
---|
376 | examination of the list of references appended to published articles. However, it is well<br>
|
---|
377 | known that authors do not necessarily include in the reference list all documents that<br>
|
---|
378 | could have been cited, and conversely that not all references listed may have been<br>
|
---|
379 | actually âusedâ in performing the research; citation behavior can be affected by a<br>
|
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380 | number of motivating factors (Garfield lists <i>15</i> possible reasons in [8]).<br>
|
---|
381 | Digital library transaction logs provide a powerful tool for direct analysis of<br>
|
---|
382 | document âusageâ: since digital libraries contain the actual document (rather than only a<br>
|
---|
383 | document surrogate), the relative amount of âuseâ that a digital libraryâs clients make of<br>
|
---|
384 | a given document sees can be estimated from the number of times the document file is<br>
|
---|
385 | downloaded (and, presumably, the document is read). Note that file downloading is a<br>
|
---|
386 | much stronger statement on the part of the user than, for example, having a<br>
|
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387 | bibliographic record appear in the query result set for a conventional bibliographic<br>
|
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388 | system; the user downloads only <i>after</i> the document has been found potentially relevant<br>
|
---|
389 | through examination of its document surrogate. Additionally, downloading is<br>
|
---|
390 | frequently time-consuming and sometimes costly (depending on local pricing for<br>
|
---|
391 | <hr>
|
---|
392 | <A name=13></a>Internet access). Downloaded documents are therefore highly likely at least to be<br>
|
---|
393 | scanned, if not read closely. The transaction logs for a digital library can provide a<br>
|
---|
394 | global picture of the use of documents in the collection, since all user interactions with<br>
|
---|
395 | the library can be automatically logged for analysis. By contrast, it is of course<br>
|
---|
396 | impossible to track usage of print bibliographies, and very difficult to monitor usage of<br>
|
---|
397 | bibliographic data available on CD-ROM across more than one or two sites.<br>
|
---|
398 | Furthermore, analysis of search requests by geographic location, institution,<br>
|
---|
399 | and sometimes even individual user are also possible. As an example, Table 2 presents<br>
|
---|
400 | a portion of the summary of usage statistics (broken down by domain code) for queries<br>
|
---|
401 | to the computer science technical collection of the NEW ZEALAND DIGITAL LIBRARY.<br>
|
---|
402 | Examination of the data indicates that the heaviest use of the collection comes from<br>
|
---|
403 | North America, Europe (particularly Germany and Finland), as well as the local New<br>
|
---|
404 | Zealand community and nearby Australia. As expected for such a collection, a large<br>
|
---|
405 | proportion of users are from educational (.edu) institutions; surprisingly, however, a<br>
|
---|
406 | similar number of queries come from commercial (.com) organizations, indicating<br>
|
---|
407 | perhaps that the documents are seeing use in commercial research and development<br>
|
---|
408 | units.<br>
|
---|
409 | Table 2. Accesses to the NEW ZEALAND DIGITAL LIBRARY CS collection by Domain<br>Code<br>
|
---|
410 | Of course, usage levels can also be further broken down by IP number<br>
|
---|
411 | (indicating institutions), and systems requiring users to register may also be able to<br>
|
---|
412 | analyze usage on an individual basis. Since the query strings themselves are also<br>
|
---|
413 | recorded in the transaction logs, this domain/institution/individual activity could also be<br>
|
---|
414 | linked to specific subjects through the query terms. Summaries of this type could be<br>
|
---|
415 | invaluable for studies of geographic diffusion and distribution of research topics.<br>
|
---|
416 | Transaction log analysis can also indicate time-related patterns in the<br>
|
---|
417 | information seeking behavior of digital library users. As a sample of this type of<br>
|
---|
418 | analysis, Paul Ginsparg notes a seven day periodicity in the number of search requests<br>
|
---|
419 | <hr>
|
---|
420 | <A name=14></a>made to the PHYSICS E-PRINT archives (Figure 4, reproduced from [9]). From this he<br>
|
---|
421 | adduces that many physicists do not yet have weekend access to the Internet (an<br>
|
---|
422 | alternative, slightly more cynical hypothesis is that even high energy theoretical<br>
|
---|
423 | physicists take the weekend off).<br>
|
---|
424 | Figure 4. Summary of search requests to the physics pre-print archives<br>
|
---|
425 | <b>5. Conclusion</b><br>
|
---|
426 | This study suggests opportunities for conducting bibliometric research on the<br>
|
---|
427 | evolving digital libraries. These repositories are suitable platforms for conventional<br>
|
---|
428 | bibliometric techniques (such as obsolescence studies, quantification of physical<br>
|
---|
429 | characteristics of documents comprising a subject literature, time analysis, etc.). The<br>
|
---|
430 | ability to directly monitor access to documents in digital libraries also enables<br>
|
---|
431 | researchers to explicitly quantify document usage, as well as to implicitly measure<br>
|
---|
432 | usage through citations. Additional facilities could aid in the performance of<br>
|
---|
433 | bibliographic experiments, such as: improved tagging of document fields; provision of<br>
|
---|
434 | utilities to strip out titles, authors, etc. from common document formats; and the ability<br>
|
---|
435 | to easily eliminate duplicate entries from downloaded library subsets. Unfortunately,<br>
|
---|
436 | the most useful of these additional facilities â those associated with a higher degree of<br>
|
---|
437 | cataloging â run counter to the underlying philosophy of many digital libraries: to<br>
|
---|
438 | avoid, if possible, manual processing and formal cataloging of documents. While<br>
|
---|
439 | adherence to this principle can limit the accuracy of fielded searching (or indeed,<br>
|
---|
440 | preclude it altogether), it can also avoid the cataloging bottleneck and permit digital<br>
|
---|
441 | libraries to provide access to larger numbers of documents.<br>
|
---|
442 | The digital libraries complement the information currently available through<br>
|
---|
443 | paper, online, and CD-ROM bibliographic resources. While these latter databases<br>
|
---|
444 | generally have the advantage of standardized formatting of bibliographic fields, the<br>
|
---|
445 | digital libraries are freely accessible, often contain &quot;grey literature&quot; that is otherwise<br>
|
---|
446 | <hr>
|
---|
447 | <A name=15></a>unavailable for analysis, and generally make the full text of documents available. The<br>
|
---|
448 | insights gained from analysis of digital libraries will add to the store of &quot;information<br>
|
---|
449 | about information&quot; that we have gained from older types of bibliographic repositories.<br>
|
---|
450 | <b>References</b><br>
|
---|
451 | [1] Bollacker, K.D., S. Lawrence, and C.L.Giles, CiteSeer: An Autonomous Web<br>
|
---|
452 | Agent for Automatic Retrieval and Identification of Interesting Publications,<br>
|
---|
453 | <i>Proceedings of the Second International Conference on Autonomous Agents</i><br>
|
---|
454 | (Minneapolis/St. Paul, May 9-13), 1998.<br>
|
---|
455 | [2] Bowman, C.M., P.B. Danzig, U. Manber, and M.F. Schwartz, Scalable Internet<br>
|
---|
456 | resource discovery: Research problems and approaches, <i>Communications of</i><br>
|
---|
457 | <i>the ACM 37(8)</i> (1994) 98-107.<br>
|
---|
458 | [3] Burton, Hilary D. , Use of a virtual information system for bibliometric analysis,<br>
|
---|
459 | <i>Informaton Processing &amp; Management 24(1)</i> (1988) 39-44.<br>
|
---|
460 | [4] Cunningham, S.J., An empirical investigation of the obsolescence rate for<br>
|
---|
461 | information systems literature, <i>Library and Information Science</i><br>
|
---|
462 | <i>Research</i>., 1996, http://library.fgcu.edu/iclc/lisrissu.htm<br>
|
---|
463 | [5] Cunningham, S.J., and D. Bocock, Obsolescence of computing literature.<br>
|
---|
464 | <i>Scientometrics</i> <i>34(2) </i> (1995), pp. 255-262.<br>
|
---|
465 | [6] Cunningham, S.J. and Lynn Silipigni Connaway, Information searching<br>
|
---|
466 | preferences and practices of computer science researchers, <i>Proceedings of</i><br>
|
---|
467 | <i>OZCHI '96</i> (1996) 294-299.<br>
|
---|
468 | [7] de Solla Price, D.J., Citation measures of hard science, soft science, technology,<br>
|
---|
469 | and nonscience. In: C.E. Nelson and D.K. Pollock (eds), <i>Communication</i><br>
|
---|
470 | <i>among scientists and engineers</i> (Heath Lexington, 1970).<br>
|
---|
471 | [8] Garfield, E., <i>Citation Indexing: Its theory and application in Science, Technology</i><br>
|
---|
472 | <i>and Humanities (</i>Wiley, 1979).<br>
|
---|
473 | <hr>
|
---|
474 | <A name=16></a>[9] Ginsparg, P. After dinner remarks: 14 Oct â94 APS meeting at LANL, 1994<br>
|
---|
475 | (&lt;URL: http://xxx.lanl.gov/blurb&gt; ).<br>
|
---|
476 | [10] Ginsparg, P., First steps towards electronic research communication, <i>Computers</i><br>
|
---|
477 | <i>in Physics 8(4)</i> (1994) 390-401. <br>
|
---|
478 | [11] Hallmark, J., Scientists' access and retrieval of references cited in their recent<br>
|
---|
479 | journal articles, <i> College and Research Libraries 55(3)</i> (1994) 199-210.<br>
|
---|
480 | [12] Hawkins, D.T. , Unconventional uses of on-line information retrieval systems:<br>
|
---|
481 | on-line bibliometric studies, <i>Journal of the American Society for Information</i><br>
|
---|
482 | <i>Science 28</i> (1977) 13-18.<br>
|
---|
483 | [13] McGhee, P.E. , P.R. Skinner, K. Roberto, N.J. Ridenour, and S.M. Larson,<br>
|
---|
484 | Using online databases to study current research trends: an online bibliometric<br>
|
---|
485 | study, <i>Library and Information Science Research 9</i> (1987) 285-291.<br>
|
---|
486 | [14] Maly, K., E.A. Fox, J.C. French, and A.L. Selman, Wide area technical report<br>
|
---|
487 | server (<i>Technical Report , </i> Dept. of Computer Science, Old Dominion<br>
|
---|
488 | University, <br>
|
---|
489 | 1994. <br>
|
---|
490 | Also <br>
|
---|
491 | available <br>
|
---|
492 | at <br>
|
---|
493 | <br>
|
---|
494 | <br>
|
---|
495 | &lt;URL:<br>
|
---|
496 | http://www.cs.odu.edu/WATERS/WATERS-paper.ps&gt; ).<br>
|
---|
497 | [15] Sigogneau, M.J. , S. Bain, J.P. Courtial, and H. Feillet, Scientific innovation in<br>
|
---|
498 | bibliographical databases: a comparative study of the Science Citation Index<br>
|
---|
499 | and the Pascal database, <i>Scientometrics 22(1)</i> (1991) 65-82.<br>
|
---|
500 | [16] Witten, I.H., S.J. Cunningham, M. Vallabh, and T.C. Bell, A New Zealand<br>
|
---|
501 | digital library for computer science research, <i>Proceedings of Digital Libraries</i><br>
|
---|
502 | <i>'95</i> (1995) 25-30.<br>
|
---|
503 | [17] Witten, I.H., C. Nevill-Manning, and S.J. Cunningham, A public library based<br>
|
---|
504 | on full-text retrieval, <i>Communications of the ACM</i> 41(4), 1998, p. 71<br>
|
---|
505 | <hr>
|
---|
506 | <A name=17></a> <br>
|
---|
507 | 1Documents were randomly sampled from the DEC<br>
|
---|
508 | (ftp://crl.dec.com/pub/DEC/CRL/tech-reports/), Sony<br>
|
---|
509 | (ftp://ftp.csl.sony.co.jp/CSL/CSL-Papers), and Ohio (ftp://archive.cis.ohio-<br>
|
---|
510 | state.edu/pub/tech-report/) technical report repositories<br>
|
---|
511 | <hr>
|
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512 |
|
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513 |
|
---|
514 | </Content>
|
---|
515 | </Section>
|
---|
516 | </Archive>
|
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