<abstract xmlns="http://www.w3.org/1999/xhtml"><sec id="j_jdis-2017-0019_s_010_w2aab3b7b3b1b6b1aab1c17b1Aa"><h3>Purpose</h3><p>The late Don R. Swanson was well appreciated during his lifetime as Dean of the Graduate Library School at University of Chicago, as winner of the American Society for Information Science Award of Merit for 2000, and as author of many seminal articles. In this informal essay, I will give my personal perspective on Don’s contributions to science, and outline some current and future directions in literature-based discovery that are rooted in concepts that he developed.</p></sec><sec id="j_jdis-2017-0019_s_011_w2aab3b7b3b1b6b1aab1c17b2Aa"><h3>Design/methodology/approach</h3><p>Personal recollections and literature review.</p></sec><sec id="j_jdis-2017-0019_s_012_w2aab3b7b3b1b6b1aab1c17b3Aa"><h3>Findings</h3><p>The Swanson A-B-C model of literature-based discovery has been successfully used by laboratory investigators analyzing their findings and hypotheses. It continues to be a fertile area of research in a wide range of application areas including text mining, drug repurposing, studies of scientific innovation, knowledge discovery in databases, and bioinformatics. Recently, additional modes of discovery that do not follow the A-B-C model have also been proposed and explored (e.g. so-called storytelling, gaps, analogies, link prediction, negative consensus, outliers, and revival of neglected or discarded research questions).</p></sec><sec id="j_jdis-2017-0019_s_013_w2aab3b7b3b1b6b1aab1c17b4Aa"><h3>Research limitations</h3><p>This paper reflects the opinions of the author and is not a comprehensive nor technically based review of literature-based discovery.</p></sec><sec id="j_jdis-2017-0019_s_014_w2aab3b7b3b1b6b1aab1c17b5Aa"><h3>Practical implications</h3><p>The general scientific public is still not aware of the availability of tools for literature-based discovery. Our Arrowsmith project site maintains a suite of discovery tools that are free and open to the public (<ext-link ext-link-type="uri" xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="http://arrowsmith.psych.uic.edu)">http://arrowsmith.psych.uic.edu)</ext-link>, as does BITOLA which is maintained by Dmitar Hristovski (<ext-link ext-link-type="uri" xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="http://http://ibmi.mf.uni-lj.si/bitola)">http://http://ibmi.mf.uni-lj.si/bitola)</ext-link>, and Epiphanet which is maintained by Trevor Cohen (<ext-link ext-link-type="uri" xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="http://epiphanet.uth.tmc.edu/)">http://epiphanet.uth.tmc.edu/)</ext-link>. Bringing user-friendly tools to the public should be a high priority, since even more than advancing basic research in informatics, it is vital that we ensure that scientists actually use discovery tools and that these are actually able to help them make experimental discoveries in the lab and in the clinic.</p></sec><sec id="j_jdis-2017-0019_s_015_w2aab3b7b3b1b6b1aab1c17b6Aa"><h3>Originality/value</h3><p>This paper discusses problems and issues which were inherent in Don’s thoughts during his life, including those which have not yet been fully taken up and studied systematically.</p></sec></abstract>

PurposeThe late Don R. Swanson was well appreciated during his lifetime as Dean of the Graduate Library School at University of Chicago, as winner of the American Society for Information Science Award of Merit for 2000, and as author of many seminal articles. In this informal essay, I will give my personal perspective on Don’s contributions to science, and outline some current and future directions in literature-based discovery that are rooted in concepts that he developed.Design/methodology/approachPersonal recollections and literature review.FindingsThe Swanson A-B-C model of literature-based discovery has been successfully used by laboratory investigators analyzing their findings and hypotheses. It continues to be a fertile area of research in a wide range of application areas including text mining, drug repurposing, studies of scientific innovation, knowledge discovery in databases, and bioinformatics. Recently, additional modes of discovery that do not follow the A-B-C model have also been proposed and explored (e.g. so-called storytelling, gaps, analogies, link prediction, negative consensus, outliers, and revival of neglected or discarded research questions).Research limitationsThis paper reflects the opinions of the author and is not a comprehensive nor technically based review of literature-based discovery.Practical implicationsThe general scientific public is still not aware of the availability of tools for literature-based discovery. Our Arrowsmith project site maintains a suite of discovery tools that are free and open to the public (http://arrowsmith.psych.uic.edu), as does BITOLA which is maintained by Dmitar Hristovski (http://http://ibmi.mf.uni-lj.si/bitola), and Epiphanet which is maintained by Trevor Cohen (http://epiphanet.uth.tmc.edu/). Bringing user-friendly tools to the public should be a high priority, since even more than advancing basic research in informatics, it is vital that we ensure that scientists actually use discovery tools and that these are actually able to help them make experimental discoveries in the lab and in the clinic.Originality/valueThis paper discusses problems and issues which were inherent in Don’s thoughts during his life, including those which have not yet been fully taken up and studied systematically.

Rediscovering Don Swanson:The Past, Present and Future of Literature-based Discovery

Journal of Data and Information Science

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

PurposeThe late Don R. Swanson was well appreciated during his lifetime as Dean of the Graduate Library School at University of Chicago, as winner of the...

No.	Feature
1	Does the B-term occur in more than one paper within literatures A and C?
2	Do the AB and BC sub-literatures share any MeSH terms?
3	Does the B-term map to at least one UMLS semantic category?
4	Does the B-term have a high literature cohesion score?
5	Is the B-term moderately frequent within MEDLINE as a whole?
6	Did the B-term first appear recently within MEDLINE as a whole?
7	Is the B-term highly characteristic within literature A or C?
8	Do the words within the B-term all occur on the customized 1,400-word stoplist?

Rediscovering Don Swanson:The Past, Present and Future of Literature-based Discovery

Article Category: Expert Review

Published Online: Dec 29, 2017

Page range: 43 - 64

Received: Aug 09, 2017

Accepted: Sep 13, 2017

DOI: https://doi.org/10.1515/jdis-2017-0019

Keywords
Literature-based discovery, Biography, Text mining, Knowledge discovery in databases, Implicit information, Information science

© 2017 Walter de Gruyter GmbH, Berlin/Boston

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Figure 1

Figure 2

Figure 3

Eight features used to characterize each B-term.

Rediscovering Don Swanson:The Past, Present and Future of Literature-based Discovery

Article Category: Expert Review

Published Online: Dec 29, 2017

Page range: 43 - 64

Received: Aug 09, 2017

Accepted: Sep 13, 2017

DOI: https://doi.org/10.1515/jdis-2017-0019

KeywordsLiterature-based discovery, Biography, Text mining, Knowledge discovery in databases, Implicit information, Information science

© 2017 Walter de Gruyter GmbH, Berlin/Boston

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Figure 1

Figure 2

Figure 3

Eight features used to characterize each B-term.

Keywords
Literature-based discovery, Biography, Text mining, Knowledge discovery in databases, Implicit information, Information science