Paper on scientometrics

David Wojick dwojick at CRAIGELLACHIE.US
Sun Jul 28 12:17:37 EDT 2013

On the other hand there is a sense in which the Kuhnian model applies at 
many different scales, down to the individual scientist, so the concept of 
micro- and macro-revolutions makes empirical sense. Kuhn was focused on the 
biggest revolutions because that is what philosophy of science did 50 years 
ago. The subsequent emergence of things like network analysis and scaling 
theory opens the door to a more comprehensive and detailed analysis of 
scientific activity.

I am less comfortable with viewing normal and revolutionary science as 
dispensable polar opposites, because there is an epistemic factor involved, 
namely that the propositions in question must be judged to be either true 
or false. The sun goes around the earth or it does not. Knowledge tends to 
be an either-or matter and revolutions usually involve important new 

One basic problem is that we do not have an agreed upon operational 
definition of revolution. So if we are measuring different things under the 
same name we may get differing results that do not actually disagree.


At 10:41 AM 7/28/2013, you wrote:
>Adminstrative info for SIGMETRICS (for example unsubscribe): 
>Thanks for the addition.
>"He notes that what may seem evolutionary, at the specialty level, over a 
>short period may later be interpreted as revolutionary in the longer run 
>(micro-revolutions, or more)."
>My take of Henry's insightful observation is that, as an alternative 
>interpretation, the judgement on evolutionary or revolutionary can be 
>profoundly influenced by
>the particular perspective, the mindset, the viewpoint, the paradigm (and 
>etc.) that one (collectively and/or individually) is taking. A step could 
>be seen as incremental to one perspective, but radical to another 
>perspective. Along with the change of time, the change of viewpoint along 
>the way may also provide an explanation of the change of judgement over time.
>Chaomei Chen
>From: ASIS&T Special Interest Group on Metrics 
>[SIGMETRICS at LISTSERV.UTK.EDU] on behalf of David A. Pendlebury 
>[david.pendlebury at THOMSONREUTERS.COM]
>Sent: Sunday, July 28, 2013 9:50 AM
>Subject: Re: [SIGMETRICS] Paper on scientometrics
>Adminstrative info for SIGMETRICS (for example unsubscribe): 
>Henry Small had some valuable practical remarks on this theme in:
>Title: Paradigms, citations, and maps of science: A personal history
>Author(s): Small, H (Small, H)
>TECHNOLOGY  Volume: 54  Issue: 5  Pages: 394-399  DOI: 
>10.1002/asi.10225  Published: MAR 2003
>Times Cited in Web of Science: 45
>Total Times Cited: 50
>Abstract: Can maps of science tell us anything about paradigms? The author 
>reviews his earlier work on this question, including Kuhn's reaction to 
>it. Kuhn's view of the role of bibliometrics differs substantially from 
>the kinds of reinterpretations of paradigms that information scientists 
>are currently advocating. But these reinterpretations are necessary if his 
>theory will ever be empirically tested, and further progress is to be made 
>in understanding the growth of scientific knowledge. A new Web tool is 
>discussed that highlights rapidly changing specialties that may lead to 
>new ways of monitoring revolutionary change in real time. It is suggested 
>that revolutionary and normal science be seen as extremes on a continuum 
>of rates of change rather than, as Kuhn originally asserted, as an all or 
>none proposition.
>He notes that what may seem evolutionary, at the specialty level, over a 
>short period may later be interpreted as revolutionary in the longer run 
>(micro-revolutions, or more).
>“Eventually, the extremes of normal and revolutionary science that Kuhn 
>describes may survive only as idealized polar opposites; what remains is a 
>continuum of rates of change from slow to rapid, as a function of the time 
>window.” See page 399 in the paper above.
>Dr. Bornmann (and Dr. Marx) cited this paper in the recent article:
>Title: The emergence of plate tectonics and the Kuhnian model of paradigm 
>shift: a bibliometric case study based on the Anna Karenina principle
>Author(s): Marx, W (Marx, Werner); Bornmann, L (Bornmann, Lutz)
>Source: SCIENTOMETRICS  Volume: 94  Issue: 2  Pages: 595-614  DOI: 
>10.1007/s11192-012-0741-6  Published: FEB 2013
>But others interested in this discussion may not know about Henry’s 2003 
>paper and his observations.
>Regards, David Pendlebury
>From: ASIS&T Special Interest Group on Metrics 
>[mailto:SIGMETRICS at LISTSERV.UTK.EDU] On Behalf Of Chen,Chaomei
>Sent: Sunday, July 28, 2013 6:17 AM
>Subject: Re: [SIGMETRICS] Paper on scientometrics
>To address what may serve as an early sign for a conceptual revolution, a 
>few lines of research are particularly relevant and share something in 
>common: it seems to be worthwhile watching the currently void but 
>potentially somewhere that could be filled up very rapidly (e.g. Don 
>Swanson on disjoint publically available knowledge, Lee Fleming on 
>patents, Loet+Ismael+Porter on interdisciplinarity, Klavans et al. on 
>conformity, and our own work on structural variation). Of course, this may 
>be just one of many potentially ways that may lead to a revolution.
>An intuitive metaphor is that one way to empirically detect such signals 
>is to look at new 'conceptual' bridges emerging and connecting previously 
>isolated islands of thinking. If a revolutionary idea eventually takes 
>off, then we'd expect to see a rapid increase of traffic on at least some 
>of these bridges so much so that at the system-level the global landscape 
>transforms its previous structure to something noticeably different.
>I don't know how to post a picture to this list, but here is a link to a 
>visualization that shows, retrospectively, after the Watts 1998 paper, 
>which has since attracted so much attention to the study of complex 
>networks such as small-world, scale-free networks, how previously 
>separated islands are stitched together by subsequent publications that 
>reinforce the structural change.
>For details, see:
>Chen, C. (2012) Predictive effects of structural variation on citation 
>counts. Journal of the American Society for Information Science and 
>Technology, 63(3), 431-449.
>Chaomei Chen
>From: ASIS&T Special Interest Group on Metrics 
>[SIGMETRICS at LISTSERV.UTK.EDU] on behalf of David Wojick 
>[dwojick at CRAIGELLACHIE.US]
>Sent: Sunday, July 28, 2013 8:02 AM
>Subject: Re: [SIGMETRICS] Paper on scientometrics
>Adminstrative info for SIGMETRICS (for example unsubscribe): 
>Dear Lutz,
>Note the exponential growth potential of the issue tree. If the rate of 
>branching is just three nodes per node then the tenth level already has 
>about 60,000 nodes. This is how new ideas can take off so rapidly, when 
>community attention turns to them. That is the normal science phase, when 
>the new idea is being actively investigated. The revolution is just the 
>top of the tree. There is a lot of confusion about this. The period of 
>rapid growth is not the revolution, rather it is the normal product of the 
>revolution. In many ways it is more interesting than the revolution. It is 
>like the difference between a gold strike and a gold mine. Mining is 
>interesting, and labor intensive.
>Your search for empirical studies may be premature. One first needs a 
>theoretical framework (says the theoretician).
>On Jul 28, 2013, at 1:04 AM, "Bornmann, Lutz" 
><<mailto:lutz.bornmann at GV.MPG.DE>lutz.bornmann at GV.MPG.DE> wrote:
>>Adminstrative info for SIGMETRICS (for example unsubscribe): 
>>Thanks for the link to the tree model. Interesting! But I am searching 
>>for large-scale empirical studies.
>>This is an interesting question: in which time period is the productivity 
>>(in terms of publication numbers) higher: in normal science or during 
>>revolutions? If one looks back on the scientific progress in a 
>>discipline, the progress is normally described alongside big discoveries 
>>(revolutions). Periods of normal science are not so interesting here, 
>>although most of the papers in the discipline might have been published 
>>in these periods.
>>Von meinem iPad gesendet
>><mailto:dwojick at CRAIGELLACHIE.US>Am 27.07.2013 um 22:23 schrieb "David 
>>Wojick" <<mailto:dwojick at CRAIGELLACHIE.US>dwojick at CRAIGELLACHIE.US>:
>>>Adminstrative info for SIGMETRICS (for example unsubscribe): 
>>> On the theoretical side my 
>>>issue tree model of scientific progress helps explain the growth of 
>>>subfields. See 
>>>But I am puzzled by your second paragraph. Most progress occurs during 
>>>normal science for that is when many specific things get explained. 
>>>Revolutions are not productive when they are occurring. The productivity 
>>>comes during the subsequent normal science period.
>>>At 03:41 PM 7/27/2013, you wrote:
>>>Adminstrative info for SIGMETRICS (for example unsubscribe): 
>>>Great comment, Andrea! Concerning altmetrics, these new metrics have 
>>>been more and more examined. Most of the studies analyzed their 
>>>correlations with citations. Because the correlation is far from 
>>>perfect, it is not clear which aspects are really measured. I believe 
>>>that "advanced" altmetrics (which will be developed) will be able to 
>>>measure some kind of societal impact.
>>>The later Kuhn described two possible ways of scientific progress in a 
>>>field: the first way is a revolution; the second way is specialization 
>>>by the creation of subfields.
>>>Colleagues, are you aware of large-scale empirical studies which 
>>>examined the development of the subfield structure in disciplines?
>>>Von meinem iPad gesendet
>>>Am 27.07.2013 um 14:54 schrieb "Andrea Scharnhorst" 
>>><<mailto:andrea.scharnhorst at DANS.KNAW.NL> 
>>><mailto:andrea.scharnhorst at DANS.KNAW.NL>andrea.scharnhorst at DANS.KNAW.NL>:
>>><>Adminstrative info for 
>>>SIGMETRICS (for example unsubscribe): 
>>>Dear all,
>>>The raise of scientometrics has different roots: the societal need for 
>>>monitoring expenses in time of a growing science system and the 
>>>emergence of knowledge-based societies; and  the need for efficient 
>>>information retrieval and knowledge discovery as a service for the 
>>>sciences themselves, and here I echo contributions of others.
>>>Having as object of study scholarship, it is only naturally that with 
>>>changes in this very scholarship also the topics and methods of 
>>>scientometrics change. There has been a longer debate if digital 
>>>scholarship presents a revolution or not. (see also Wouters et al. 
>>>Virtual Knowledge, MIT 2013)
>>>What of these changes should be called a revolution, for sure depends on 
>>>the point of reference. I always find Galison's approach to scientific 
>>>revolution helpful. He argues that breaks and changes occur in 
>>>theoretical threads as well as in empirical one and in methodological 
>>>one; sometimes this occurs in parallel, sometimes with a time delay; 
>>>sometimes in one specialty only – sometimes affecting a whole field. So, 
>>>instead of looking at a singular event, one better can talk of an 
>>>accumulation of different changes. Galison uses often geological, 
>>>geomorphological metaphors to describe this. (see his book: Image and 
>>>Logic). I think one cannot talk about a revolution with defining the 
>>>boundaries of the system of reference first.
>>>As an observer of scientometrics from the periphery or better as an 
>>>occasional visitor, I found remarkable how in the past the 
>>>scientometrics community embraced and integrated the visual turn 
>>>(science maps) and the turn towards the authors. The latter was very 
>>>visible at the last ISSI just a week ago. 
>>>impression is also that scientometrics managed to claim authority in the 
>>>turn from "little bibliometrics" to "big bibliometrics" as Wolfgang 
>>>Glaenzel called it in 2006, in a presentation I still find interesting 
>>>to watch/read (see 
>>>). I'm not sure if Wolfgang would still support his statement from seven 
>>>years ago that "bibliometrics evolved from a sub discipline of LIS to a 
>>>evaluation and benchmarking tool". But, it seems that it is still the 
>>>scientometrics community which discusses and defines indicators used broadly.
>>>What concerns the digital revolution, and in particular the web, indeed 
>>>scientometrics has incorporated altmetrics, taken up the challenge and 
>>>made own original contributions (thanks to pioneers as Judit BarIlan, 
>>>Mike Thelwall, Isidro Aguillo and many others). But, if I may say so, 
>>>here scientometrics acted rather as a client, using the new data 
>>>sources. Its behavior towards web-based information was and is very 
>>>similar to the behavior towards the commercial bibliographic databases: 
>>>namely to build indicators based on data export from them.
>>>What I think is a challenge to be mastered in the upcoming years, is the 
>>>semantic web and Linked Open Data. Here, I would like to back-up 
>>>Clement's contribution, and actually reading his list and the thread as 
>>>a whole triggered this now growing more lengthy comment ;-)
>>><>If the attempts of the semantic web community mature 
>>>further, and if research information as a standard becomes available 
>>>semantic referencable on the web, we talk about a profound change in the 
>>>data source landscape for scientometrics. There is a possibility to 
>>>eventually link between the 'old' input/expenditure statistics, human 
>>>capital information and other institutional information and the 
>>>traditional output – the scholarly communication – which for so many 
>>>decades has dominated scientometrics, also just because of its 
>>>availability in a standardized form. One example for this movement is 
>>>VIVO, <> But, working in a research data 
>>>archive I witness the raise of standards, API's, LOD in this area and it 
>>>is obvious that the web of scholarly information is just before (in not 
>>>in the middle) of another big change.
>>>Semantic reasoning over research information in Linked Open Data (LOD) 
>>>formats will enable services (including indicators) different from what 
>>>we have now. It does not concern 'just another data base' or another 
>>>social media one can harvest data from; it concerns a whole set of other 
>>>techniques. Either scientometrics embraces this too, and learns to play 
>>>on the "Klaviatur" (keyboard) of the semantic web, or the knowledge of 
>>>the community might become obsolete.
>>>Personally, I think the LOD and semantic web technologies are the future 
>>>methodological innovation in scientometics, and I'm curious to hear 
>>>comments on this. According to Lutz, this than would not count as a 
>>>revolution, being 'just' another method. But, if it means that other 
>>>communities could become the carrier for scientometric analysis, it 
>>>might be a revolution – at least for the field of scientometics as we 
>>>know it now.
>>>Dr. Andrea Scharnhorst
>>>Head of e-research at Data Archiving and Networked Services (DANS)
>>>Scientific Coordinator of the Computational Humanities Programme, 
>>>e-Humanities group
>>>Chair of the COST Action KnowEscape
>>>Royal Netherlands Academy of Arts and Sciences
>>>From: Clement Levallois <<mailto:clement_levallois at YAHOO.FR> 
>>><mailto:clement_levallois at YAHOO.FR>clement_levallois at YAHOO.FR>
>>>Reply-To: ASIS&T Special Interest Group on Metrics 
>>>Date: Fri, 26 Jul 2013 16:41:46 +0200
>>>Subject: Re: [SIGMETRICS] Paper on scientometrics
>>>Adminstrative info for SIGMETRICS (for example unsubscribe): 
>>>Difficult to say where we are going, but there is an expanding list of 
>>>practices that are pushing for an evolution of scientometrics.
>>>- open access
>>>- open data (Figshare, etc.)
>>>- semantic web / linked data
>>>- science communication / science making on social media
>>><>- digital scholarship (see 
>>>- networks (can we neglect relations between the units under measurement?)
>>>- the altac movement
>>>- and altmetrics (drawing on all the previous)
>>>I'd be curious, what else do you see as "disruptive" (sorry for the buzz 
>>>word) today in scientometrics?
>>>Best regards,
>>>Clement Levallois, PhD
>>>Erasmus University Rotterdam
>>>The Netherlands
>>>website / <>personal website
>>>twitter and skype: @seinecle
>>>Discover the NESSHI project:
>>>check my new app:
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