Review
Defrosting the Digital Library: Bibliographic Tools for the
Next Generation Web
Duncan Hull
1,2
*, Steve R. Pettifer
2,3
, Douglas B. Kell
1,2
1 School of Chemistry, The University of Manchester, Manchester, United Kingdom, 2 The Manchester Interdisciplinary Biocentre, The University of Manchester,
Manchester, United Kingdom, 3 School of Computer Science, The University of Manchester, Manchester, United Kingdom
Abstract: Many scientists now manage the bulk of their
bibliographic information electronically, thereby organiz-
ing their publications and citation material from digital
libraries. However, a library has been described as
‘‘thought in cold storage,’’ and unfortunately many digital
libraries can be cold, impersonal, isolated, and inaccessi-
ble places. In this Review, we discuss the current chilly
state of digital libraries for the computational biologist,
including PubMed, IEEE Xplore, the ACM digital library, ISI
Web of Knowledge, Scopus, Citeseer, arXiv, DBLP, and
Google Scholar. We illustrate the current process of using
these libraries with a typical workflow, and highlight
problems with managing data and metadata using URIs.
We then examine a range of new applications such as
Zotero, Mendeley, Mekentosj Papers, MyNCBI, CiteULike,
Connotea, and HubMed that exploit the Web to make
these digital libraries more personal, sociable, integrated,
and accessible places. We conclude with how these
applications may begin to help achieve a digital defrost,
and discuss some of the issues that will help or hinder this
in terms of making libraries on the Web warmer places in
the future, becoming resources that are considerably
more useful to both humans and machines.
‘‘The apathy of the academic, scientific, and information communities
coupled with the indifference or even active hostility…of many
publishers renders literature-data-driven science still inaccessible.’’ –
Peter Murray-Rust [1]
Introduction
The term digital library [2–4] denotes a collection of literature
and its attendant metadata (data about data) stored electronically.
According to Herbert Samuel, a library is ‘‘thought in cold
storage’’ [5], and unfortunately digital libraries can be cold,
isolated, impersonal places that are inaccessible to both machines
and people. Many scientists now organize their knowledge of the
literature using some kind of computerized reference management
system (BibTeX, EndNote, Reference Manager, RefWorks, etc.),
and store their own digital libraries of full publications as PDF files.
However, getting hold of both the data (the actual publication) and
the metadata for any given publication can be problematic
because they are often frozen in the isolated and icy deposits of
scientific publishing. Because each library and publisher has
different ways of identifying and describing their metadata, using
digital libraries (either manually or automatically) is much more
complicated than it needs to be [6], and with papers in the life
sciences alone (at Medline) being published at the rate of
approximately two per minute [7], only computerized analyses
can hope to be reasonably comprehensive. What then, are these
digital libraries, and what services do they provide?
As far as computational Biologists are concerned, and for the
purposes of this Review, we shall define a digital library more
broadly as a database of scientific and technical articles,
conference publications, and books that can be searched and
browsed using a Web browser. As of early 2008, there is a wide
range of these digital libraries, but no single source covering all
information (in part because of the cost, given that there are some
25,000 peer-reviewed journals publishing some 2.5 million articles
per year [8]). Each library is isolated, balkanized, and has only
partial coverage of the entire literature. This contrasts with the
historically pre-eminent library of Alexandria whose great strength
was that it brought together all the useful literature then available
to a single location. Like Alexandria, most digital libraries are
currently read-only, allowing users to search and browse informa-
tion, but not to write new information nor add personal knowledge.
Other digital libraries are in danger of becoming write-only ‘‘data-
tombs’’ [9], where data are deposited but will probably never be
accessed again. Indeed, the literature itself is now so vast that most
scientists choose to access only a fraction of it [10], at potentially
considerable intellectual loss [11] (see also [12]).
Digital libraries provide electronic access to documents,
sometimes just to their abstracts and sometimes to the full text
of the publication. Presently, the number of abstracts considerably
exceeds the number of full-text papers, but with the emergence of
Open Access initiatives (e.g., [13–16]), Institutional Repositories
(e.g., [17–20]), and the like, this is set to change considerably. This
is very important, as much additional information exists in full
papers that is not seen in abstracts, and, in addition, full papers
that are available electronically are likely to be much more widely
read and cited [21–23]. The format of the full text of such
documents can vary significantly among publishers. Such formats
can be described using a Document Type Definition (DTD), e.g.,
that provided by the (U.S.) National Library of Medicine [16,24],
and, since not all publishers (especially those of non-biomedical
material) conform to the NLM DTD, this can considerably affect
the types of analysis that can be done on such documents.
Citation: Hull D, Pettifer SR, Kell DB (2008) Defrosting the Digital Library:
Bibliographic Tools for the Next Generation Web. PLoS Comput Biol 4(10):
e1000204. doi:10.1371/journal.pcbi.1000204
Published October 31, 2008
Copyright:
2008 Hull et al. This is an open-access article distributed under
the terms of the Creative Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in any medium, provided the
original author and source are credited.
Funding: Biotechnology and Biological Sciences Research Council (BBSRC): grant
code BB/E004431/1.
Competing Interests: The authors have declared that no competing interests
exist.
* E-mail: duncan.hull@cs.man.ac.uk
Editor: Johanna McEntyre, National Center for Biotechnology Information (NCBI),
United States of America
PLoS Computational Biology | www.ploscompbiol.org 1 October 2008 | Volume 4 | Issue 10 | e1000204

In a similar vein, there is not yet a recognized (universal) standard
for describing the metadata (see Table 1), although some (discussed
below) such as the Dublin Core are becoming widely used.
Since all of these libraries are available on the Web, increasing
numbers of tools for managing digital libraries are also Web-based.
They rely on Uniform Resource Identifiers (URIs [25] or ‘‘links’’) to
identify, name, and locate resources such as publications and their
authors. By using simple URIs, standard Web browser technology,
and the emerging methods of the next generation Web or ‘‘Web 2.0’’
[26], it has become possible for digital libraries to become not just read-
only or write-only, but both read–write. These applications allow users to
add personal metadata, notes, and keywords (simple labels or ‘‘tags’’
[27,28]) to help manage, navigate, and share their personal collections.
This small but significant change is helping to improve digital libraries
in three main ways: personalization, socialization, and integration.
The focus of this Review is largely about searching and
organizing literature data together with their metadata. For
reasons of space, we do not consider in any detail issues
surrounding Open Access (e.g., [13,29]), nor structured digital
abstracts [30,31] (note the recent initiative in FEBS Letters [32–
34] and the RSC’s Project Prospect for whole papers [35–38]).
Neither do we discuss the many sophisticated tools for text mining
and natural language processing (e.g., [39–42]), for joining
disparate concepts [43,44], for literature-based discovery (e.g.,
[45–49], and for studies of bibliometrics [50,51], literature
dynamics [52], knowledge domains [53], detecting republication
[54], and so on, all of which become considerably easier to
implement only when all the necessary data are digitized and
linked together with their relevant metadata.
This Review is structured as follows (see also Figure 1): the
section Digital Libraries, DOIs, and URIs starts by looking at the
range of information in digital libraries, and how resources are
identified using URIs on the Web. In the section Problems with
Digital Libraries, we consider a fairly standard workflow that
serves to highlight some problems with using these libraries. The
following section, Some Tools for Defrosting Libraries, examines
what Web-based tools are currently available to defrost the digital
library and how they are making libraries more personal, sociable,
and integrated places. Finally, the section A Future with Warmer
Libraries looks at the obstacles to future progress, recommends
some best practices for digital publishing, and draws conclusions.
Digital Libraries, DOIs, and URIs
Because computational biology is an interdisciplinary science, it
draws on many different sources of data, information, and
knowledge. Consequently, there exists a range of digital libraries
on the Web identified by URIs [25] and/or DOIs [55,56] that a
typical user requires, each with its own speciality, classification,
and culture, from computer science through to biomedical science.
DOIs are a specific type of URI and similar to the International
Standard Book Numbers (ISBN), allowing persistent and unique
identification of a publication (or indeed part of a publication),
independently of its location. The range of libraries currently
available on the Web is described below, starting with those that
focus on specific disciplines (such as ACM, IEEE, and PubMed)
through to libraries covering a broader range of scientific disciplines,
such as ISI WOK and Google Scholar. For each library, we describe
Table 1. A summary of some of the digital libraries described in this Review.
Name Domain Size Style of Metadata
Persistent
Inbound Links?
Persistent
Outbound
Links? Full Text? Access
ACM Digital Library
http://portal.acm.org
Computer science .54,000
articles
BibTeX,
EndNote
Yes, see ACM
section in text
Not applicable For subscribers Metadata and abstract
free, full paper for
subscribers only
IEEE Xplore http://
ieeexplore.ieee.org
Computer science Unknown EndNote,
Procite,
Refman
Yes, see Xplore
section in text
Not applicable For subscribers Metadata and abstract
free, full paper for
subscribers only
DBLPDBLP http://dblp.
uni-trier.de
Mostly computer
science
.900,000
articles
BibTeX Yes, see dblp
section in text
Various,
including DOIs
Links to
publisher DOIs
Metadata free
Pubmed http://pubmed.
gov
Life sciences and
biomedicine
.17,000,000
articles
XML, NLM, DTD Yes, see
PubMed
section in text
LinkOut and
links to
publisher sites
Links to
publisher DOIs
Metadata and abstract
free
PubmedCentral http://
pubmedcentral.gov
Life sciences and
biomedicine
.750,000 XML, Dublin
Core, RDF
Yes, see text Not applicable Yes Free access to data and
metadata
Web of Knowledge http://
apps.isiknowledge.com
Broad scientific
coverage
.15,000,000 BibTeX, EndNote,
Refman, Procite
No, see WoK
section in text
Links to
publisher sites
Links to
publisher DOIs
Subscription only
Scopus http://www.
scopus.com
Broad scientific
coverage
.33,000,000 RefWorks, EndNote,
Refman, Procite
Yes, see Scopus
section in text
Links to
publisher sites
Links to
publisher DOIs
Subscription only
Citeseer http://citeseer.ist.
psu.edu
Broad coverage .760,000 BibTeX Yes, see
Citeseer section
in text
Local cache and
links to self-
archived papers
Yes Free access
Google Scholar http://
scholar.google.com
Broad coverage Not published Nothing very
exportable,
html only
Yes, see Google
Scholar section
in text
Direct links to
publishers and
self-archived
grey literature
Yes (includes
grey literature
and self-archived)
Free access
arXiv http://www.arxiv.
org/
Mainly physical
sciences
.44,000 BibTeX, Yes, see section
on arXiv in text
Links to self-
archived material
in some PDFs
Yes Free access
Note that this table summary does not cover all the minutiae of licensing issues.
doi:10.1371/journal.pcbi.1000204.t001
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the size, coverage, and style of metadata used (summarized in Table 1
and Figure 2). Where available, DOIs can be used to retrieve
metadata for a given publication using a DOI resolver such as
CrossRef [57], a linking system developed by a consortium of
publishers. We illustrate with specific examples how URIs and DOIs
are used by each library to identify, name, and locate resources,
particularly individual publications and their author(s). We often take
URIs for granted, but these humble strings are fundamental to the
way the Web works [58] and how libraries can exploit it, so they are
a crucial part of the cyberinfrastructure [59] required for e-science
on the Web. It is easy to underestimate the value of simple URIs,
which can be cited in publications, bookmarked, cut-and-pasted, e-
mailed, posted in blogs, added to Web pages and wikis [60–62], and
indexed by search engines. Simple URIs are a key part of the current
Web (version 1.0) and one of the reasons for the Web’s phenomenal
success since appearing in 1990 [63]. As we shall demonstrate with
examples, each digital library has its own style of URI for being
linked to (inbound links) and alternative styles of URI for linking out
(outbound links) to publisher sites. Some of these links are simple,
others more complex, and this has important consequences for both
human and programmatic access to the resources these URIs
identify.
The ACM Digital Library. The Association for Computing
Machinery (ACM), probably best known for the Turing award,
makes their digital library available on the Web [64]. The library
currently contains more than 54,000 articles from 30 journals and
900 conference proceedings dating back to 1947, focusing
primarily on computer science. Like many other large
publishers, the ACM uses Digital Object Identifiers (DOI) to
identify publications. So, for example, a publication on scientific
workflows [65] from the 16th International World Wide Web
Conference (WWW2007) is identified by the Digital Object
Figure 1. A mind map [207] summarizing the contents of this article in a convenient manner.
doi:10.1371/journal.pcbi.1000204.g001
Figure 2. The approximate relative coverage and size of
selected digital libraries described in the section Digital
Libraries, DOIs, and URIs, and summarised in Table 1. Of all
the libraries described, Google Scholar probably has the widest
coverage. However, it is currently not clear exactly how much
information Google indexes, what the criteria are for inclusion in the
index, and whether it subsumes other digital libraries in the way shown
in the figure. Note: the size of sets (circles) in this diagram is NOT
proportional to their size, and DBLP, Scopus, and arXiv are shown as a
single set for clarity rather than correctness.
doi:10.1371/journal.pcbi.1000204.g002
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Identifier DOI:10.1145/1242572.1242705. The last part of the
DOI can be used in ACM-style URIs as follows: http://portal.
acm.org/citation.cfm?doid = 1242572.1242705. Metadata for
publications in the ACM digital library are available from URIs
in the style above as EndNote [66] and BibTeX formats; the latter
is used in the LaTeX document preparation system [67].
IEEE Xplore. The Institute of Electrical and Electronics
Engineers (IEEE) provides access to its technical literature in
electrical engineering, computer science, and electronics, through a
service called Xplore [68]. The exact size of the Xplore archive is not
currently described anywhere on the IEEE Web site. Xplore
identifies publications using Digital Object Identifiers that are
supplemented with a proprietary IEEE scheme for identifying
publications. So, for example, a publication on text-mining [69] in
IEEE/ACM Transactions on Computational Biology and Bioinformatics is
identified by both the Digital Object Identifier DOI:10.1109/
TBME.2007.906494 and an internal IEEE identifier 1416852.
These identifiers can be used in URIs as follows: http://dx.doi.
org/10.1109/TBME.2007.906494 and http://ieeexplore.ieee.org/
search/wrapper.jsp?arnumber = 1416852. Metadata for publications
in IEEE Xplore are available from URIs in the style above in
EndNote, Procite, and Refman. Alternatively, publication metadata
are available by using a DOI resolver such as CrossRef. Currently,
the IEEE offers limited facilities for its registered members to build a
personal library and to share this with other users.
DBLP. The Digital Bibliography and Library Project (DBLP)
[70,71], created by Michael Ley, provides an index of peer-
reviewed publications in computer science. Recently, DBLP has
started to index many popular journals with significant
computational biology content such as Bioinformatics and Nucleic
Acids Research, and currently indexes about 900,000 articles, with
links out to full text, labeled EE for electronic edition. Thus an
article by Russ Altman on building biological databases [72] is
identified by the URI http://dblp.uni-trier.de/rec/bibtex/
journals/bib/Altman04. Metadata for publications in DBLP are
available in BibTeX format only. Unlike some libraries that we
describe later, DBLP is built largely by hand [71], rather than by
bots and crawlers indexing Web pages without human intervention.
One of the consequences of this is that authors are disambiguated
more accurately [73], e.g., where an author’s middle initial(s) is not
used or alternative first names appear in metadata. This kind of
author disambiguation is particularly relevant to the naming
conventions in some countries [74].
PubMed.gov and PubMed Central. PubMed [75] is a
service provided by the National Center for Biotechnology
Information (NCBI). The PubMed database includes more than
17 million citations from more than 19,600 life science journals
[76,77]. The primary mechanism for identifying publications in
PubMed is the PubMed identifier (PMID); so, for example, an
article describing NCBI resources [77] is identified by the URI
http://pubmed.gov/18045790. Publication metadata for articles
in PubMed are available in a wide variety of formats including
MEDLINE flat-file format and XML, conforming to the NCBI
Document Type Definition [77], a template for creating
XML documents. PubMed can be personalized using the
MyNCBI application, described later in the section Some Tools
for Defrosting Libraries. PubMed Central [78], a subset of
PubMed, provides free full-text of articles, but has lower coverage
as shown in Figure 2. Related sites are also emerging in other
countries, such as that in the UK [79]. A URI identifying the
NCBI resources article [77] in the US PubMed Central is: http://
www.pubmedcentral.nih.gov/articlerender.fcgi?artid = 1781113.
Metadata are available from URIs in PubMed Central as either
XML, Dublin Core, and/or RDF [80] by using the Open
Archives Initiative (OAI) [81] Protocol for Metadata Harvesting
(PMH), a standard protocol for harvesting metadata. For
example, embedded in the page identified by the URI above,
there are Dublin Core terms such as DC.Contributor, DC.Date,
and DC.title, which are standard predefined terms for describing
publication metadata. In addition to such standard metadata,
PubMed papers are tagged or indexed according to their MeSH
(Medical Subject Heading) terms, curated manually.
ISI Web of Knowledge (WoK). ISI WoK [82] is The
Institute for Scientific Information’s Web of Knowledge, a service
provided by The Thomson Reuters Corporation, covering a broad
range of scientific disciplines (not just computer science or
biomedical science). The size of the library is somewhere in the
region of 15,000,000 ‘‘objects’’ according to the footer displayed in
pages of search results. Unfortunately, ISI WoK does not currently
provide short, simple links to its content; so, for example, the URI
for an NCBI publication [77] in ISI WoK is hidden behind a script
interface called cgi [83]; this is usually displayed in the address bar
of a Web browser, regardless of which publication is being viewed,
as in this example: http://isiknowledge.com. It is possible to
extract individual URIs for publications, but regrettably they are
usually too long and complicated and contain ‘‘session identifiers,’’
which make them expire after a set period of time (usually
24 hours). Temporary and long URIs of this kind cannot be easily
used by humans, and prevent inbound links to the content. ISI
WoK also provides various citation tracking and analytical
features such as Journal Citation Reports, which measures the
impact factor [84,85] of individual journals [86]. Metadata for
publications in ISI WoK are provided in BibTeX, Procite,
Refman, and EndNote. WoK provides citation tracking features,
particularly calculating the H-index [87] for a given author, as well
as ‘‘citation alerts’’ that can automatically send e-mail when a
given paper is newly cited.
Scopus.com. Scopus [88] is a service provided by Reed
Elsevier and seems to be the Digital Library with individually the
most comprehensive coverage, claiming (June 2008) .33,000,000
records (leaving aside Web pages). As far as linking is concerned,
Scopus allows links to its content using OpenURL [89], which
provides a standard syntax for creating URIs. For example, the URI
http://www.scopus.com/scopus/openurl/document.url?issn =
03029743&volume = 3298&spage = 350 identifes a publication [90]
from the Semantic Web conference, with the ISSN, volume, and
page as part of the URI. The Scopus OpenURL link shown above is
the simplest kind that can exist; many get much more complicated as
more information is included in the URI, doubling the length of the
one shown. The longer and more complicated URIs become, the less
likely they are to be useful for humans. Scopus also links out to
content using OpenURL and provides citation tracking. Metadata
can be exported in RefWorks [91], RIS format (EndNote, ProCite,
RefMan), and plain text, etc.
Citeseer. Citeseer [92] is a service currently funded by
Microsoft Research, NASA, and the National Science Foundation
(NSF), covering a broad range of scientific disciplines and more
than 760,000 documents, according to Citeseer. The URI http://
citeseer.ist.psu.edu/apweiler04uniprot.html identifies a paper
about UniProt [93]. Publication metadata are available from
Citeseer in BibTeX format, and citation tracking is performed
annually in the Most Cited Authors feature [94].
Google Scholar. Google Scholar [95] (e.g., [96–99]) is a
service provided by Google (see also [100]), which indexes
traditional scientific literature, as well as preprints and ‘‘grey’’
self-archived publications [19] from selected institutional Web
sites. A typical page from Google Scholar is shown in Figure 3.
The size and coverage of Google Scholar does not seem to have
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been published, and the exact method for finding and ranking
citations has not yet been made completely public [101].
In contrast to some other digital libraries, Google Scholar
provides simple URIs that link to different resources. For example,
http://scholar.google.com/scholar?cites = 9856542662207029505
identifies citations of a publication [102] by Tom Oinn.
At the time of writing, Google Scholar does not currently offer
any specific facilities for creating a personal collection of
documents or sharing these collections with other users, other
than using simple links such as the one above. Publication
metadata can be obtained from Google Scholar where OpenURL
links are found in its search results; otherwise, metadata can be
obtained by clicking through the links to their original sources.
arXiv.org. arXiv [103] provides open access to more than
44,000 e-prints in physics, mathematics, computer science,
quantitative biology, and statistics, and was created by Paul
Ginsparg [104]. It is a leading example of what can be done,
although it is presently little used by biologists. The arXiv has a
different publishing model from that of the other digital libraries
described in this paper, because publications are peer-reviewed
after publication in the arXiv, rather than before publication. (A
related but non-identical strategy is pursued with PLoS ONE,
where papers are peer reviewed before being made accessible, but
if they do not pass peer review they do not appear.) The arXiv is
owned, operated, and funded by Cornell University and is also
partially funded by the National Science Foundation. arXiv uses
simple URIs to identify publications that incorporate the arXiv
identifier. Because arXiv acts as a preprint server, some of its
content eventually becomes available elsewhere in more
traditional peer-reviewed journals. For example, an article on
social networks published in Science [105] is also available from
http://arxiv.org/abs/cond-mat/0205383. Metadata for
publications in arXiv are available in BibTeX format, with
various citation-tracking features provided by the experimental
citebase project [106,107]. This alternative approach to manual
citation counts works by calculating the number of times an
individual paper has been downloaded, as with the Highly-
accessed feature on BioMedCentral journals.
…and the rest. In a short review such as this one, it is not
possible to describe every single library a computational biologist
might use, because there are so many. Also, it is surprisingly hard
to define exactly what a specific digital library is because the
distinction between publishers, libraries, and professional societies
is not always a clean one. Thus, we have not described the digital
libraries provided by Highwire [108], WorldCat [109], JSTOR,
the British Library, the Association for the Advancement of
Artificial Intelligence (AAAI), the Physical Review Online Archive
(PROLA), and the American Chemical Society (ACS) (e.g.,
SciFinder). Neither do we discuss commercial publisher-only
sites such as SpringerLink, Oxford University Press,
ScienceDirect, Wiley-Blackwell, Academic Press, and so on here,
since most of this content is accessible, typically via abstracts, via
the other libraries and databases described in the section on digital
libraries with links out to the publishers’ sites.
Summary of libraries. Although they differ in size and
coverage, all of these digital libraries provide similar basic facilities
for searching and browsing publications. These features are well-
documented elsewhere, so we will not describe them in detail here.
With the exception of arXiv and PubMed Central, which provide
full free access to entire articles, all other libraries described here
Figure 3. Google Scholar search results, identified by http://scholar.google.com/scholar?q = mygrid. Google Scholar links out to
external content using a number of methods including OpenURL [89], shown here by the ‘‘Find it via JRUL’’ (JRUL is a local library) links. Unlike, e.g.,
WoK, it is relatively easy to create inbound links to individual authors and publications in Google Scholar; see text for details.
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provide free access to metadata (author, year, title, journal,
abstract, etc.) and link to data (the full-text of a given article),
which the user may or may not be licensed to view. The
approximate relationship between the different libraries, as far as
coverage is concerned, is shown in Figure 2.
Where these libraries differ is in the subscription, personaliza-
tion, and citation-tracking features. So, for example, ISI WoK is a
subscription-only service, not freely accessible, but which offers
more extensive citation tracking features (such as ranking papers
by citation counts, the impact factor [85,86], and h-index [87])
than other libraries. Other services, such as the NCBI, are
available freely, and provide additional features using custom tools
to freely registered users. Other services such as Google Scholar
and Citeseer are free, but currently offer no personalized view.
Both ISI and Google Scholar provide services for counting and
tracking citations of a given paper, which are not provided by most
other libraries.
These libraries also differ considerably in the nature and power
of their indexing by which users can search them on specific topics
of metadata. Most permit Boolean searches on the basis of
authors, keywords, words in a title or abstract, and so on, though
none does this in real-time, and comparatively few allow
sophisticated combinations.
All of this reflects the fact that these libraries and the means of
searching them evolved independently and largely in isolation.
Consequently, it is generally difficult for a user to build their own
personalized view of all the digital libraries combined into one
place, although tools described in the section Some Tools for
Defrosting Libraries are now beginning to make this more feasible.
Before we describe these further, we shall look at some of the
current issues with using these digital libraries, as it is exactly these
kinds of problems that have motivated the development of new
tools. These tools, and the digital libraries they are built on, have
to manage two inescapable facts: 1) redundancy: any given
publication or author can be identified by many different URIs; 2)
representing metadata: there are many different ways of
identifying and describing metadata (and see Table 1). We
describe some of the consequences of this in the next section.
Problems Using Digital Libraries
The digital libraries outlined in the previous section all differ in
their coverage, access, and features, but the abstract process of
using them is more standard. Figure 4 shows an abstract workflow
for using any given digital library. We do not propose this as a
universal model, which every user will follow, but provide it to
illustrate some of the problems with managing data and metadata
in the libraries described in the previous section on digital libraries.
To begin with, a user selects a paper, which will have come
proximately from one of four sources: 1) searching some digital
library, ‘‘SEARCH’’ in Figure 4; 2) browsing some digital library
(‘‘BROWSE’’); 3) a personal recommendation, word-of-mouth from
colleague, etc., (‘‘RECOMMEND’’); 4) referred to by reading
another paper, and thus cited in its reference list (‘‘READ’’). Once a
paper of interest is selected, the user: 1) retrieves the abstract and
then the paper (i.e., the actual paper itself as a file), ‘‘GET’’ in
Figure 4; 2) they save the paper, for example by bookmarking it,
storing on a hard-drive, printing off, etc., (‘‘SAVE’’). Saving often
involves getting the metadata, too, (‘‘GET METADATA’’). By
metadata, we again mean the basic metadata about a publication,
such as the author, date, journal, volume, page number, publisher,
etc. In practice, this means any information typically found in an
EndNote or BibTeX entry; 3) they read the paper, ‘‘READ’’ in
Figure 4; 4) they may annotate the paper, (‘‘ANNOTATE’’); 5)
finally, they may cite the paper (‘‘CITE’’). Citing requires retrieving
the metadata, if these have not been retrieved already.
This abstract workflow is idealized, but highlights some
problems with using current digital libraries, for both humans
and machines. In particular, see the following list.
1.Identity Crisis. There is no universal method to retrieve a
given paper, because there is no single way of identifying
publications across all digital libraries on the Web. Although
various identification schemes such as the PubMed identifier
(PMID), Digital Object Identifier (DOI), ISBN, and many
others, exist, there is not yet one identity system to ‘‘rule them
all.’’
2.Get Metadata. Publication metadata often gets ‘‘divorced’’
from the data it is about, and this forces users to manage each
independently, a cumbersome and error-prone process. Most
PDF files, for example, do not contain embedded metadata
that can be easily extracted [110]. Likewise, for publications on
the Web there is no universal method to retrieve metadata. For
any given publication, it is not possible for a machine or human
to retrieve metadata using a standard method. Instead there
are many inadequate options to choose from, which add
unnecessary complexity to obtaining accurate metadata.
3.Which metadata? There is no single way of representing
metadata, and without adherence to common standards (which
largely already exist, but in a plurality) there never will be.
EndNote (RIS) and BibTeX are common, but again, neither
format is used universally across all libraries.
We describe each of these issues more fully in the following
sections.
Identity crisis. We are suffering from an acute identity crisis
in the life sciences [111]. Just as sequence databases have trouble
managing the multiple identities of sequences [112], digital
libraries also suffer from being unable to identify individual
publications and their authors [113]. These are essential pieces of
information that make libraries easy to use, and also help to track
citations, but in the present implementation they create
considerable barriers to users and machines. Any single
publication or author is identified by numerous different URIs.
An important task for managing these disparate collections
involves reconciling and normalizing these different identity
schemes, that is, calculating if two different URIs identify the
same resource or not. For example, a human can fairly easily
determine (by following the links) that each of these URIs identify
the same publication, but writing a generic program to automate
this for arbitrary URIs is more challenging: http://nar.
oxfordjournals.org/cgi/content/full/36/suppl_1/D13; http://www.
ncbi.nlm.nih.gov/pubmed/18045790; http://www.pubmedcentral.
nih.gov/articlerender.fcgi?artid = 1781113; and http://dx.doi.org/
10.1093/nar/gkm1000.
Where DOIs exist, they are supposed to be the definitive URI.
This kind of automated disambiguation, of publications and
authors, is a common requirement for building better digital
libraries. Unlike the traditional paper library, machines play a
much more important role in managing information. They come
in many forms, typically search-engine bots and spiders such as
Googlebot [114], but also screen-scrapers [115], feed-readers
[116,117], workflows [102,118], programs, Web services [90,119–
122], and ad hoc scripts, as well as semantic Web agents and
reasoners [123]. They are obviously of great importance for text-
mining [39–41,124–126], where computer algorithms plus
immense computing power can outperform human intelligence
on at least some tasks [127]. Publication metadata are essential for
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machines and humans in many tasks, not just the disambiguation
described above. Despite their importance, metadata can be
frustratingly difficult to obtain.
Metadata: You can’t always GET what you want. As well
as the problem of extracting metadata from PDFs [110], getting
metadata for any given URI which identifies a publication is also
problematic. Although the semantic Web has been proposed as a
general solution to this [128–132], it is currently a largely
unrealised vision of the future [133,134]. The Open Archives
Initiative mentioned previously provides a solution to this
problem, though it is not adopted by all publishers. So, given an
arbitrary URI, there are only two guaranteed options for getting
any metadata associated with it. Using http [135], it is possible to
for a human (or machine) to do the following.
1.http GET the URI. Getting any URIs described in the
previous section Digital Libraries, URIs, and DOIs will usually
return the entire HTML representation of the resource. This
then has to be scraped or parsed for metadata, which could
appear anywhere in the file and in any format. This technique
works, but is not particularly robust or scalable because every
time the style of a particular Web site changes, the screen-
scraper will probably break as well [136]. Some Web sites such
as PubMed Central make this easier, by clearly identifying
metadata in files, so they can easily be parsed by tools and
machines.
2.http HEAD the URI. This returns metadata only, not the
whole resource. These metadata will not include the author,
journal, title, date, etc., of the publication but basic information
such as the MIME type which indicates what the resource is
(text, image, video, etc. [137]), Last-Modified date [135], and
so on.
The lack of an adequate method for retrieving metadata has led
to proposals such as the Life Sciences Identifier (LSID) [138,139]
and BioGUID [140] (Biological Globally Unique IDentifier).
These may be useful in the future if they become more widely
adopted, but do not change the current state of the digital library.
As it stands, it is not possible to perform mundane and seemingly
simple tasks such as, ‘‘get me all publications that fulfill some
criteria and for which I have licensed access as PDF’’ to save
locally, or ‘‘get me a specific publication and all those it
immediately references’’.
Which metadata? Even if there were a standard way to
retrieve metadata for publications, there is still the problem of how
to represent and describe them. In addition to EndNote (RIS) and
BibTeX, there are also various XML schemas such as the U.S.
Library of Congress Metadata Object Description Schema
(MODS) format [141] and RDF vocabularies, such as the
Dublin Core mentioned earlier. Having all these different
metadata standards would not be a problem if they could easily
be converted to and from each other, a process known as ‘‘round-
tripping’’. However, some conversions gain or lose information
along the way. Lossy and irreversible conversions create dead-ends
for metadata, and many of these mappings are non-trivial, e.g.,
XML to RDF and back again [123]. In addition to basic metadata
found in EndNote and BibTeX, there are also more complex
metadata such as the inbound and outbound citations, related
articles, and ‘‘supplementary’’ information.
The identity crisis, inability to get metadata easily, and
proliferation of metadata standards are three of the main reasons
that libraries are particularly difficult to use and search as
automatically as one would wish. These are challenging problems
to overcome, and the tools we describe in the next section tackle
these problems in different ways.
Figure 4. A typical workflow for using a digital library representing a subset of the literature. Tasks represented by white nodes are
normally performed exclusively by humans, while tasks shown in blue nodes can be performed wholly or partly by machines of some kind. The main
problematic tasks that make digital libraries difficult to use for both machines and humans are ‘‘GET’’ (publication) and ‘‘GET METADATA’’. These are
shown in bold and discussed further in the Identity Crisis section of this paper.
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Some Tools for Defrosting Libraries
Although libraries can be cold, the tools described in this section
could potentially make them much warmer. They do this in two
main ways. Personalization allows users to say this is my library,
the sources I am interested in, my collection of references, as well
as literature I have authored or co-authored. Socialization
allows users to share their personal collections and see who else is
reading the same publications, including added information such
as related papers with the same keyword (or ‘‘tag’’) and what notes
other people have written about a given publication. The ability to
share data and metadata in this way is becoming increasingly
important as more and more science is done by larger and more
distributed teams [142] rather than by individuals. Such social
bookmarking is already available on the Web site of publications
such as the Proceedings of the National Academy of Sciences
(http://www.pnas.org) and the journals published by Oxford
University Press.
The result of personalization and socialization is integration of a
kind that cannot be achieved by machines alone. First, we look at
personalization-only style tools, then we examine tools that also
allow socialization of the library through sharing.
Zotero.org and Mendeley. Zotero [143] is an extension for
the Firefox browser that enables users to manage references
directly from the Web browser. As with most Web-based tools,
Zotero can recognise and extract data and metadata from a range
of different digital libraries. Users can bookmark publications, and
then add their own personal tags and notes. Currently, Zotero does
not allow users to share their tags in the same way that more
‘‘sociable’’ tools such as CiteULike and Connotea do (see below),
although enhancements to the current 1.0 version of Zotero may
include this feature. Zotero bookmarks cannot be identified using
URIs, so it is not possible to link in from external sources to these
personal collections. Mendeley [144] is a similar application that
helps to manage and share research papers, although as well as
having a Web-based browser version it is possible to store
bibliographies using a more powerful desktop-based client that
automatically extracts metadata from PDF files, but it can only do this
where metadata is available in an amenable format [110].
MyNCBI. MyNCBI [77] allows users to save PubMed
searches and to customize search results. It also features an
option to update and e-mail search results automatically from
saved searches. MyNCBI includes extra features for highlighting
search terms, filtering search results, and setting LinkOut [145],
document delivery, and external tool preferences. Like Zotero,
MyNCBI currently allows personalization only, with no
socialization features. It is also limited to publications in
PubMed. As we have previously seen, computational biologists
frequently require access to many publications outside PubMed, so
they cannot capture their entire library in MyNCBI alone. Like
Zotero, it is currently not possible to link to personal collections
created in MyNCBI.
Mekentosj Papers. Papers [146,147] is an application for
managing electronic publications, originally designed by
Alexander Griekspoor and Tom Groothuis. Although it is not a
typical browser-based Web application, it can be closely integrated
with several services on the Web-like Google Scholar, PubMed,
ISI Web of Knowledge, and Scopus mentioned in the Digital
Libraries section of this paper. The Papers application
demonstrates how large collections of PDF files can be managed
more easily. Papers provides a simple and intuitive interface shown
in Figure 5 to a collection of PDF files stored on a personal hard
drive. It looks and behaves much like Apple’s iTunes, an
application for managing music files, because the user does not
have to know where the data (PDF file) is stored on their hard
drive [110]. Unfortunately, Papers is only available for Apple
Macintosh users, and there is no version for Windows, which limits
its uptake by scientists.
The personalization of libraries is nothing especially new or
groundbreaking, and scientists have been creating personal
libraries for years, for example by having their own EndNote
library or BibTeX file. Tools such as Zotero, MyNCBI, and
Papers just make the process of personalization simpler. However,
socialization of digital libraries is relatively new, in particular the
ability of multiple users to associate arbitrary tags [27,28,148] with
URIs that represent scientific publications. This is what CiteU-
Like, Connotea, and HubMed (see below) all allow, thereby
capturing some of the supposed ‘‘wisdom of crowds’’ [149] in
classifying information.
CiteULike.org. CiteULike [150] is a free online service to
organize academic publications, now run by Oversity. It has been
on the Web since October 2004 when its originator was attached
to the University of Manchester, and was the first Web-based
social bookmarking tool designed specifically for the needs of
scientists and scholars. In the style of other popular social
bookmarking sites such as delicious.com [151,152], it allows
users to bookmark or ‘‘tag’’ URIs with personal metadata using a
Web browser; these bookmarks can then be shared using simple
links such as those shown below. The number of articles
bookmarked in CiteULike is approaching 2 million, indicated by
the roughly incremental numbering used. While the CiteULike
software is not open source, part of the dataset it collects is
currently in the public domain [153]. Publication URIs are simple:
http://www.citeulike.org/article/1708098.
CiteULike normalizes bookmarks before adding them to its
database, which means it calculates whether each URI bookmarked
identifies an identical publication added by another user, with an
equivalent URI. This is important for social tagging applications,
because part of their value is the ability to see how many people (and
who) have bookmarked a given publication. CiteULike also
captures another important bibliometric, viz how many users have
potentially read a publication, not just cited it. It seems likely that the
number of readers considerably exceeds the number of citers
[84,150], and this can be valuable information. Time lags matter,
too. This is particularly the case with Open Access, where the
‘‘most-accessed’’ Journal of Biology paper of 2007 [154] had in June
2008 been accessed in excess of 12,000 times, but has been cited just
nine times (note that early access statistics can provide good
predictors for later citations [155]). CiteULike provides metadata
for all publications in RIS (EndNote) and BibTeX, providing a
solution to the ‘‘Get Metadata’’ problem described in the previous
section Metadata: You Can’t Always GET What You Want,
because every CiteULike URI for a publication has metadata
associated with it in exactly the same way.
Connotea.org. Connotea [156] is run by Nature Publishing
Group and provides a similar set of features to CiteULike with some
differences. It has been available on the Web since November 2004.
Connotea uses MD5 hashes [157] to store URIs that users bookmark,
and normalizes them after adding them to its database, rather than
before. This post-normalization means Connotea does not always
currently recognize when different URIs (such as the examples in the
section Identity Crisis) identify the same publication, a bug known as
‘‘buggotea’’ [158], which also affects CiteULike to a lesser extent.
Like CiteULike, URIs in Connotea are simple. A publication about
Connotea [156], for example, is identified by the URI http://www.
connotea.org/uri/685b90ae66cfbc3fc8ebeed0a5def571. Metadata
are available from Connotea in a wider variety of formats than
from CiteULike, including RIS, BibTeX, MODS, Word 2007
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bibliography, and RDF, but these have to be downloaded in bulk only,
rather than individually per publication URI. The source code for
Connotea [159] is available, and there is an API that allows software
engineers to build extra functionality around Connnotea, for example
the Entity Describer [160].
HubMed.org. HubMed [161] is a ‘‘rewired’’ version of
PubMed, and provides an alternative interface with extra features,
such as standard metadata and Web feeds [116,117], which can be
subscribed to using a feed reader. This allows users to subscribe to
a particular journal and receive updates when new content (e.g., a
new issue) becomes available. An example URI for a publication
on HubMed [161] is http://www.hubmed.org/display.
cgi?uids = 16845111. Like CiteULike, HubMed also solves the
‘‘Get Metadata’’ problem because metadata are available from
each HubMed URI in a wide variety of formats not offered by
NCBI. This is one of HubMed’s most useful features. At the time
of writing, HubMed provides metadata in RIS (for EndNote),
BibTeX, RDF, and MODS style XML. Users can also log in to
HubMed to use various personalized features such as tagging.
Advantages of using CiteULike and Connotea. Both
CiteULike and Connotea require users to invest time and effort
learning how to use them, and importing or entering bibliographic
information. Why should they bother? Managing bibliographic
metadata using these tools has several advantages over the common
scenario of storing un-indexed PDF files locally on a personal
computer. Both CiteULike and Connotea provide a single place (a
Web server) where data (PDFs) and metadata can both be shared
and more tightly coupled; this has the following benefits.
Searching. Easier and more sophisticated searching is
possible. Conversely, given a collection of PDFs on a hard drive,
it is typically difficult (or impossible) to make simple queries such as
‘‘retrieve all papers by [a given author]’’.
Managing. When authoring manuscripts, managing
references in a Web-based repository can save some of the pain
of re-typing metadata (e.g., author names) for a given publication.
Provided the publication has a URI that is recognized by these
tools, metadata are automatically harvested on behalf of the user,
saving them time.
Tagging. Tags are just keywords, but these allow both
personalisation and socialisation of bibliographic data, see [162] for
papers cited in this Review as an example. Tagging of papers by other
users allows non-expert users to explore related papers in ways that
may not be possible through traditional reference lists, since exploring
a subject of research in which you are not expert is made easier by
following links added by other potentially more expert users.
Server-based. Hosting a bibliography on a Web server
means that, if and when the user moves computer, the library is
still accessible. However, keeping local and remote versions
requires appropriate synchronisation, which can be problematic.
Serendipity. Many serendipitous discoveries [163] or
intellectual linkages that may be determined via co-occurrences
(e.g., [43,49,164–167]) exist in science, and these can be assisted
by browsing links provided via social tagging.
Future tools. The tools described here are the first wave of
Web 2.0, Library 2.0 [168], or even Science 2.0 [169] style tools
that are helping to defrost the digital library. There will certainly
be plenty more in the future; for example, the Research
Information Centre [170] from the British Library is
investigating innovative new tools in this area, backed by
Microsoft. Some are calling it ‘‘Web 3.0’’ [171], but, whatever
Figure 5. Mekentosj Papers can organize large collections of locally stored PDF files, with their metadata. It looks and feels much like
the popular iTunes application, allowing users to manage their digital libraries by categories shown at the top. It is presently available only under Mac
OS/X.
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the name, it seems likely that we will see many digital library
applications that will exploit the novel social features of platforms
such as Facebook [172,173] and OpenSocial [174]. Here they can
exploit the identity mechanisms already built into those systems.
Personalization and socialization of information will increas-
ingly blur the distinction between databases and journals [175],
and this is especially true in computational biology where
contributions are particularly of a digital nature. Scientific
contributions to digital knowledge on the Web often do not fit
into traditional scientific publishing models [31]. This is usually
because they are either too ‘‘small’’ or too ‘‘big’’ to fit into journals.
Web logs or ‘‘blogs’’ are beginning to fill the ‘‘too small’’ (see
‘‘microattribution’’ [176]) gap and can be used for communicating
preliminary results, discussion, opinion, supplementary material,
and short technical reports [177–179] in the style of a traditional
laboratory notebook. Biological databases, such as those listed in
the annual NAR database review [180], have long filled the ‘‘too
big’’ gap in scientific publishing. They are clearly more significant
than their publications alone. As we move in biology from a focus
on hypothesis-driven to data-driven science [1,181,182], it is
increasingly recognized that databases, software models, and
instrumentation are the scientific output, rather than the
conventional and more discursive descriptions of experiments
and their results.
In the digital library, these size differences are becoming
increasingly meaningless as data, information, and knowledge
become more integrated, socialized, personalized, and accessible.
Take Postgenomic [183], for example, which aggregates scientific
blog posts from a wide variety of sources. These posts can contain
commentary on peer-reviewed literature and links into primary
database sources. Ultimately, this means that the boundaries between
the different types of information and knowledge are continually
blurring, and future tools seem likely to continue this trend.
A Future with Warmer Libraries
The software described in the section Some Tools for Defrosting
Libraries are a promising start to improving the digital library.
They make data and metadata more integrated, personal, and
sometimes more sociable. While they are a promising start, they
face considerable obstacles to further success.
Obstacles to warmer libraries. We suggest that the main
obstacles to warmer libraries are primarily social [184] rather than
technical in nature [185]. Identity, trust, and privacy are all
potential stumbling blocks to better libraries in the future.
One identity to rule them all? The basic ability to identify
publications and their authors uniquely is currently a huge
barrier to making digital libraries more personal, sociable, and
integrated. The identity of people is a twofold problem because
applications need to identify people as users in a system and as
authors of publications. The lack of identity currently prevents
answering very simple questions such as, ‘show me all person x
publications’, unless the authors concerned are lucky enough to
have unique names. Both the NCBI and CrossRef have
initiatives to identify authors uniquely in digital libraries, but
these have yet to be implemented successfully. The use of Single
Sign-On (SSO) schemes such as Shibboleth [186] and OpenID
[187] (the latter is used in projects such as myExperiment.org
[188] and Connotea) could have a huge impact, enabling
identity and personalization, without the need for hundreds of
different usernames and password combinations. It remains to be
seen what their impact on scientific literature will be.
Technically, there are also tough challenges for creating
unique author names [74,113], such as synonymy, name
changes, and variable use of initials and first names, which are
ongoing legacy issues.
Who can scientists trust? Passing valuable data and
metadata onto a third party requires that users trust the
organization providing the service. For large publishers such as
Nature Publishing Group, responsible for Connotea, this is not
necessarily a problem. That said, many users are liable to distrust
commercial publishers when their business models may
unilaterally change their data model, making the tools for
accessing their data backwards incompatible, a common
occurrence in bioinformatics. Smaller startup companies, who
are often responsible for innovative new tools, may struggle to gain
the trust of larger institutions and libraries. Most of the software
described in the section Tools for Defrosting Libraries require a
considerable initial investment from users to import their libraries
into the system. Users have to trust service providers that this
investment has a good chance of paying off in the longer term.
Scientists also have to decide how much to trust and rely on
commercial for-profit companies to build and maintain the
cyberinfrastructure they require for managing digital libraries. Not
all commercial companies provide the best value-for-money services,
and this is often true in scientific publishing. Paul Ginsparg, for
example, has estimated that arXiv operates with a cost that is 100 to
1,000 times lower than a conventional peer-reviewed publishing
system [189]. If the market will not provide scientists with the
services they require, at a price they are willing to pay, they need to
build and fund them themselves. The danger is that too much
electronic infrastructure will be owned and run by private
companies, and science will then be no better served than it was
with paper-based publishing.
What data do scientists want to share? Although the
practice of sharing raw data immediately, as with Open Notebook
Science [190], is gaining ground, many users are understandably
cautious about sharing information online before peer-reviewed
publication. Scientists can be highly secretive and reticent at times
[191], selfishly not wanting to share their data and metadata freely
with everyone and anyone, for fear of being ‘‘scooped’’ or copied
without proper credit and attribution. Some tools provide security
features, e.g., both CiteULike and Connotea allow users to hide
references. However, this requires users to trust external providers
to respect and protect their privacy, since the information is on a
public server, and out of users’ control.
Recommendations
Warmer digital libraries cannot be achieved by software tools
alone. The digital libraries themselves can take simple steps to
make data and metadata more amenable to human and
automated use, making their content more useful and useable.
Only with proper and better access to linked data and metadata
can the tools that computational biologists require be built. We
make the following recommendations to achieve this goal.
Simple URIs. URIs for human use should be as simple as
possible, to allow easy linking to individual publications and their
authors. Short URIs are much more likely to be used and cited
[192] than longer, more complicated URIs.
Persistent URIs. It has been noted many times before
[193,194], but it is worth repeatedly restating: persistent URIs
make digital libraries a much more useful and usable place.
Although URIs will inevitably decay [195,196], many (but not all)
will be preserved by the Internet Archive [197,198], and every
effort should be made to keep them persistent where possible.
Exposing metadata. Publication metadata, in whatever style
(EndNote, BibTeX, XML, RDF, etc.), should be transparently
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exposed and readily available, programmatically and manually,
from URIs, HTML [199], and PDF files of publications.
Identifying publications. URNs (such as Digital Object
Identifiers) should be used to identify publications wherever
possible. Most large publishers already do this, although there are
still many confounding exceptions.
Identifying people. This problem is twofold: people need to
be identified as users of a system and as authors of publications. To
tackle the first issue, tools and libraries should use Single Sign On
(SSO) schemes, such as OpenID [187] to provide access to
personalized features where possible, as this prevents the endless
and frustrating proliferation of username/passwords to identify
users in Web applications. The second requires unique author
identification, an ongoing and as yet unsolved issue for digital
libraries.
By following these recommendations, publishers, scientists, and
libraries of all kinds can add significant value to the information
they manage for the digital library.
Conclusions
The future of digital libraries and the scientific publications they
contain is uncertain. Rumours of the death of printed books [200]
and the death of the journal [201] have (so far) been greatly
exaggerated. In scientific publishing, we are beginning to see books
and electronic journals becoming more integrated with databases,
blogs, and other digital media on the Web. These and other
changes could lead to a resurgence in the role of nonprofit
professional societies and institutional libraries in the scientific
enterprise [104] as the cost of publishing falls. But the outcome is
still far from certain.
What is certain is the fact that we can look forward to a digital
library that is more integrated, sociable, personalized, and
accessible, although it may never be completely ‘‘frost-free’’.
Ultimately, better libraries will be a massive benefit to science. The
current breed of Web-based tools we have described are
facilitating this change, and future tools look set to continue this
trend. Ultimately, data and metadata will become less isolated and
rigid, moving more fluidly between applications on the Web.
There are still issues with trust, privacy, and identity that may
hinder the next generation of Web-based digital libraries, and
these social problems will need addressing.
It has frequently been observed that scientists lag behind
other communities in their use of the Web to communicate
research [202], and that this is ironic given that the Web was
invented in a scientific laboratory for use primarily by scientists
Box 1. Glossary and Abbreviations
The following terms and abbreviations are used throughout this paper.
API Application Programming Interface. An API allows software engineers to re-use other people’s software with standard
programmatic ‘‘hooks.’’
Blog WebLog, a suite of technologies for rapid publishing on the Web [177–179,208,209].
DOI Digital Object Identifier, a persistent and unique identifier for Objects, usually publications [55,56], specific type of URN
(see below and http://www.doi.org/).
DTD Document Type Definition, a template or schema for describing the structure of XML documents. The most prominent of
these is that set down by the National Library of Medicine, http://dtd.nlm.nih.gov/, although each publisher tends to have their
own.
Dublin Core A standard for describing metadata across many different domains, http://dublincore.org/.
HTTP Hypertext Transfer Protocol, a communications protocol used to transfer information on the Web [135].
IETF Internet Engineering Task Force develops and promotes Internet standards such as HTTP, URIs, http://www.ietf.org/.
MeSH Medical Subject Heading terms represent a controlled vocabulary used by the National Library of Medicine, http://www.
nlm.nih.gov/mesh/.
Metadata Metadata are data about data, e.g., publication metadata include author, date, publisher, etc.
MODS Metadata Object Description Schema, a proposed standard for metadata emanating from the Library of Congress,
http://www.loc.gov/standards/mods/.
OpenURL Standard syntax for URLs that link to scholarly publications, requiring an OpenURL resolver [89] to make use of
them.
OWL Web Ontology Language, a W3C semantic Web standard for creating ontologies that makes extensive use of logical
reasoners; see, e.g., [123,210].
RDF Resource Description Framework, a W3C semantic Web standard for describing meta/data as graphs [123].
SSO Single Sign-On, a method for authenticating human users that allows one username/password to provide access to many
different resources.
URI Uniform Resource Identifier, a URI can be further classified as a locator (URL), a name (URN), or both [25].
URL Uniform Resource Locator refers to the subset of URIs that, in addition to naming a resource, provides a means of locating
the resource using, e.g., http://www.plos.org.
URN Uniform Resource Name, an identifier usually required to remain globally unique and persistent. Unlike URLs, URNs provide
a mechanism for naming resources without specifying where they are located; for example, urn:isbn:0387484361 is a URN for a
book, that says nothing about where the book can be located.
W3C The World Wide Web Consortium, http://www.w3.org/, an international standards body responsible for standards such as
HTML, XML, RDF, and OWL, led by Tim Berners-Lee.
Web 1.0 The original Web, the first version created in 1990 [63].
Web 2.0 The Web in 2004, a phrase coined by Tim O’Reilly [26] to describe changes since 1990, such as ‘‘social software.’’
Web 3.0 Used to refer to future versions of the Web that do not yet exist [171]; for instance, (largely) the Semantic Web.
Web feed Web feeds allow users to subscribe to content that changes, and to be notified when it does, using either RSS or
ATOM [116]. This can save time visiting Web sites manually to check for updates. Many journals now make Tables of Contents
available in this way.
XML eXtensible Markup Language, a W3C standard for describing meta/data as ‘‘trees.’’
PLoS Computational Biology | www.ploscompbiol.org 11 October 2008 | Volume 4 | Issue 10 | e1000204

[63]. Most scientists are painfully familiar with the shortcomings
of the databases and software described in this Review, because
these tools are at the very heart of science. Digital libraries are,
and always will be, fundamental components of e-science, and of
the ‘‘cyber-infrastructure’’ [59,203–205], necessary for both
computational and experimental biology in the 21st century.
Acknowledgments
Duncan Hull would like to thank Timo Hannay and Tim O’Reilly for an
invitation to Science Foo Camp [206] 2007, where some of the issues
described in this publication were discussed; Kevin Emamy, Richard
Cameron, Martin Flack, and Ian Mulvany for answering questions on the
CiteULike and Connotea mailing lists; and Greg Tyrelle for ongoing discus-
sion about metadata and the semantic Web at http://www.nodalpoint.org.
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PLoS Computational Biology | www.ploscompbiol.org 14 October 2008 | Volume 4 | Issue 10 | e1000204