Do younger Sleeping Beauties prefer a technological prince?
Do younger Sleeping Beauties prefer a technological prince?
Anthony F. J. van Raan 0 1
Jos J. Winnink 0 1
0 Centre for Science and Technology Studies, Leiden University , Kolffpad 1, P.O. Box 905, 2300 AX Leiden , The Netherlands
1 & Anthony F. J. van Raan
In this paper we investigate recent Sleeping Beauties cited in patents (SBSNPRs). We find that the increasing trend of the relative number of SBs stopped around 1998. Moreover, we find that the time lag between the publication year of the SB-SNPRs and their first citation in a patent is becoming shorter in recent years. Our observations also suggest that, on average, in the more recent years SBs are awakened increasingly earlier by a 'technological prince' rather than by a 'scientific prince'. These observations suggest that SBs with technological importance are 'discovered' earlier in an application-oriented context. Then, because of this earlier recognized technological relevance, papers may be cited also earlier in a scientific context. Thus early recognized technological relevance may 'prevent' papers to become an SB. The scientific impact of Sleeping Beauties is generally not necessarily related to the technological importance of the SBs, as far as measured with number and impact of the citing patents. The analysis of the occurrence of inventor-author relations as well as the citation years of inventor-author patents suggest that the scientific awakening of Sleeping Beauties only rarely occurs by inventor-author self-citation.
Sleeping Beauties; Patent citations; Time lag; Inventor-author relations; Technological impact; Technological awakening; Scientific awakening
A ‘Sleeping Beauty in Science’ is a publication that goes unnoticed (‘sleeps’) for a long
time and then, almost suddenly, attracts a lot of attention (‘is awakened by a prince’). This
phenomenon of ‘delayed recognition’ attracted the attention of Eugene Garfield already
more than 45 year ago, in the early history of the Science Citation Index. With an essay
‘Would Mendel’s work have been ignored if the Science Citation Index was available
100 years ago?’ Garfield opened in 1970 the debate on unnoticed scientific breakthroughs
and therefore uncited by contemporary colleague-researchers
1970, 1980, 1989, 1990)
. Particularly, delayed recognition was linked to ‘premature
discovery’ or ‘being ahead of time’, i.e., publishing work that is too far outside the body of
knowledge at the time of publication
(Stent 1972; Garfield 1980)
. We refer to our earlier
(van Raan 2015)
for a comprehensive overview of the literature on Sleeping Beauties
(SBs). In that paper we discussed the results of an extensive analysis of Sleeping Beauties
in physics, chemistry, and engineering and computer science (referred to as the three main
fields) in order to find out the extent to which Sleeping Beauties are application-oriented
and thus are potential Sleeping Innovations. We found that more than half of the SBs are
In a next paper
(van Raan 2017a)
we took a further step by investigating whether the
Sleeping Beauties in physics, chemistry, and engineering and computer science are also
cited in patents, i.e., SBs as scientific non-patent references (SNPR) in patents. One of our
central topics was the time lag between the publication year of the SB-SNPRs and their
first citation in a patent. We found evidences that this time lag was becoming shorter in
recent years. In this paper we investigate this further by using as recent as possible SBs
cited in patents. Furthermore, we focus on an interesting phenomenon: who will be first,
the scientific or the technological prince?
The structure of this paper is as follows. We first discuss the selection of specific sets of
SBs, the data collection and numbers of identified SBs as a function of time. Next we
discuss the matching of the SBs with patent citation data in order to find SBs cited in
patents and to analyze the time lag between publication year of the SB and the year of the
first patent citation. We also highlight the technological impact of the patents that cite the
SBs. Finally, we summarize our findings and discuss further research.
Recent trends in the occurrence of Sleeping Beauties
Choice of sets of Sleeping Beauties
In the foregoing papers
(van Raan 2015, 2017a, b)
we discussed our fast and efficient
search algorithm written in SQL which can be applied to the CWTS enhanced Web of
Science (WoS) database. With this algorithm we can tune the following four main
variables: (1) length of the sleep in years after publication (s); (2) depth of sleep in terms of a
maximum citation rate during the sleeping period (csmax); (3) awake period in years after
the sleeping period (amin and amax); and (4) awake intensity in terms of a minimum citation
rate during the awake period (camin). We define csmax = 0 as a coma, csmax = 0.5 as a very
deep sleep, and csmax = 1.0 as a deep sleep.
For a proper analysis of the SBs, we need a total time period equal to sleeping period
plus awakening period. Clearly, the longer s, the less publication years we have for our
investigation. For instance, if s = 20, we need a time period 20 ? 5 = 25 years. Given
that our database is updated up till 2016, and that we want to focus our analyses on an as
recent as possible time period (say, from 1990), only publication years (publ y) 1990, 1991,
and 1992 can be used.
We identified Sleeping Beauties in the fields of physics, chemistry, engineering and
computer science (WoS fields are given in Table 3 of the ‘‘Appendix’’) with the following
s = 20; csmax = 0.0, 0.5, and 1.0; amin = amax = 5; camin = 5.0; publ y: 1990–1992;
s = 15; csmax = 0.0, 0.5, and 1.0; amin = amax = 5; camin = 5.0; publ y: 1990–1997;
s = 10; csmax = 0.0, 0.5, and 1.0; amin = amax = 5; camin = 5.0; publ y: 1990–2002;
s = 5; csmax = 0.0, 0.5, and 1.0; amin = amax = 5; camin = 5.0; publ y: 1990–2007.
Having identified with help of our SQL search algorithm the SBs that meet the above
parameters, we are able to determine the annual numbers of these SBs. We discuss these
quantitative aspects in detail in the next section.
Numbers and trends
The total number of publications covered by the WoS increases constantly over the
measuring period. Obviously, if more papers in a given field are published, the number of
SBs will, in principle, also increase. If however the number of SBs would increase less than
the total number of publications in the given fields, then this could be an indication that the
probability for a publication to become a SB decreases. But, of course, this remains to be
seen. To examine the above considerations more closely, we first counted the annual
number of publications for the period 1990–2007 in physics, chemistry, engineering and
computer science. The results are given in Table 1. We used 1990 as the index year.
In Fig. 1 we show this annual trend (again 1990 as index year). Clearly, there is an
exponential growth of the physics, chemistry, engineering and computer science literature
covered by the WoS of about 4% per year.
The annual numbers of SBs are determined with our SQL search algorithm. On the basis
of the growth factors given in Table 1 we normalized these annual numbers of the
identified SBs, see Table 2 where the absolute (real) and the relative (normalized) numbers are
In Fig. 2 we show the relative annual trends. Given the very low numbers in the case of
the very long sleeping period s = 20, and in addition the short measuring period for this
sleeping period, we present the trends for s = 15, 10, and 5, and csmax = 0.5 and 1.0, and
in the case of s = 5 also for csmax = 0.0.
SBs with s = 5 have the shortest sleeping period and thus they can be analyzed for the
most recent times, until 2007. Our results show that from around 1998 the relative number
of SBs is not increasing anymore. This is an interesting and perhaps also counterintuitive
finding: it appears that, probably, the expanding worldwide facilities to access scientific
publications stopped the earlier increasing trend. But nevertheless it apparently does not
prevent that a more or less constant fraction of publications still becomes an SB.
b Fig. 2 Trend in the relative (normalized) number of SBs. Upper part: SBs with s = 15, csmax = 0.5 and
1.0; middle part: SBs with s = 10, csmax = 0.5 and 1.0; lower part: SBs with s = 5, csmax = 0.0, 0.5 and
Scientific or technological awakening?
Time lags between publication year and year of first patent citation
Patents are documents with a legal status to describe and claim technological inventions in
which, similar to scientific publications, references are given. These references concern
mainly earlier patents (‘prior art’) in order to prove novelty in view of the existing
technological developments. Generally, but to a lesser extent, patents also have references to
non-patent items, particularly scientific publications, the ‘scientific non-patent references’
(SNPRs). References in scientific publications are the sole responsibility of the authors.
References in patents, however, come from two sources: they can be given by both the
inventors as well as by the patent examiners. In this study patent citations of both sources
are considered to have the same function of linking science with technology. Clearly, these
SNPRs represent a bridge between science and technology although they do not necessarily
indicate the direct scientific basis of the invention described in the patent. Nevertheless,
(for an overview see for instance Callaert et al. 2014)
importance of further research of the role of SNPRs in relation to the patented
technological invention. In this study we elaborate further on our previous work on SBs that are
SNPRs (SB-SNPRs) by focusing on as recent as possible SBs.
Patent data were collected by searching the EPO Worldwide Patent Statistical Database
(PATSTAT), Spring 2016 version. We group patents describing the same invention in
‘patent families’1 to prevent double counting. In order to find out whether an SB is cited by
patents, we matched all SBs on the basis of their WoS UT-codes with the citations given in
patents. For more details we refer to
Winnink and Tijssen (2014)
. We choose two sets for
matching with patent data: (1) SBs sleeping long (s = 10) and deep (csmax = 0.5), and (2)
SBs sleeping short (s = 5) but in coma (csmax = 0.0). We find, as follows from Table 1,
282 SBs for set 1, and 176 SBs for set 2. As we discussed earlier, in both cases
amin = amax = 5 and camin = 5.0.
With the matching algorithm (written as an SQL-query applicable to the PATSTAT
database) we find that 44 of the 282 SBs in set 1 are cited by patents, i.e., 16% (2 of these
SB-SNPRs are a note, and one is a review paper); and that 18 of the 176 SBs in set 2 are
cited by patents, i.e., 10% (none of these SB-SNPRs are notes or reviews). Similar to
citations given by publications, also the number of citations by patents is characterized by a
skew distribution. For instance, about half of the SB-SNPRS in set 1 are cited by 1 or 2
patents, and five (of the 44) are cited by 5 of more patents. In total, the 44 SB-SNPRs in set
1 are cited by 119 patents. In Set 2 the large majority of SB-SNPRs are cited by only 1
patent and one is cited by 17 patents. In total, the 18 SB-SNPRs in set 2 are cited by 37
In a next step we determined for the identified SB-SNPRs the filing year of the citing
patents. The difference between the filing year of the patent that is the first citer of the
SBSNPR and the publication year of the SB-SNPR defines the time lag between publication
and the first citation by a patent (pcy). This time lag ranges in set 1 from 1 to 18 years
1 In this study a patent family is a set of, in legal terms, equivalent patents that describe one and the same
invention. This is for instance the case when the same invention is patented in more than one country.
(average 8.5, SD = 4.3), and in set 2 from 1 to 14 years (average 6.7, SD = 4.4). The
average values of pcy relates to a long measuring period. In order to find out if there is a
trend in the course of time, we calculated averages of pcy for successive, partly
overlapping 5-year periods. In the case of the long sleeping SBs (s = 10) these periods are
1990–1994, 1991–1995,…1998–2002. In Figs. 3 and 4 we present the results for set 1 and
set 2, respectively. Remarkably, for the set 1 SB-SNPRs the time lag (pcy) becomes rapidly
shorter in the measured period (1990–2002) than the sleeping time (s = 10). For the set 2
SB-SNPRs we see that initially the time lag is considerably higher (around 10 years) than
the sleeping period (s = 5). But even more rapidly than in the case of set 1, the time lag
decreases, and also for this set 2 the time lag becomes shorter than the sleeping period (in
this case 5 years). Both observations suggest that, on average, in the more recent years SBs
are awakened more and more earlier by a ‘technological prince’ rather than by a ‘scientific
On the basis of the scope of the journals in which the SBs are published we find that 174
of the 282 SBs (62%) in set 1 are typically application-oriented, for the 44 SB-SNPRs in
this set this percentage is considerably higher (91%). In set 2 these percentages are 66 and
78%, respectively, so comparable with the results for set 1, but less pronounced.
Are Sleeping Beauties cited by high impact patents?
Just as in the case of publications, also patents show a wide variety of impact. Only a
relatively small amount of patents represents important technological breakthroughs
(Albert et al. 1991)
. Patent-to-patent citations provide a first indication of the importance of
the cited patents
, particularly if they are highly cited and belong to, for
instance, the top-10% cited patents in their field.
Harhoff et al. (1999)
found that patents
renewed to full-term (which is the maximum duration of the patent protection, mostly
20 years) were significantly more highly cited than patents allowed to expire before their
full term. The higher an invention’s economic value estimate was, the more the patent was
subsequently cited. For an overview of patent citation analysis studies we refer to van Raan
In this section we analyze the extent to which the patents that cited our SB-SNPRs are
themselves cited by other patents. In the foregoing section we discussed that the 44
SBSNPRs in set 1 (sleep is long (s = 10) and very deep (csmax = 0.5)) have been cited by in
total 119 patents of which the majority is cited by other patents. These cited patents relate
to 39 SB-SNPRs. Thus the majority (82%) of the SB-SNPRs in set 1 do have patents that
are cited by other patents after their publication within a 5-year citation window (longer
citation windows such as 10 or 15 years can only be applied to the oldest SB-SNPRS in our
set). In total, the patents that cite the SB-SNPRs are themselves cited 1530 times by other
patents within the 5 years window. Taking the total of patent citations for each SB-SNPR
we find that the distribution is very skew. For two SB-SNPRs their citing patents are cited
633 and 126 times respectively, for five SB-SNPRs it is between 50 and 100 times, for 18
SB-SNPRS between 10 and 50, and the 14 remaining SB-SNPRs it is between 1 and 10.
The above mentioned SB-SNPR with 633 patent citations is published in 1992 and it
describes a new technique with which for the first time p–n-junctions were formed in GaAs
quantum wire crystals
(Haraguchi et al. 1992)
. The high-impact patent cited this SB-SNPR
10 years after its publication, so the technological and scientific awakening happened
around at the same time. Figure 5 shows the citation history of the Haraguchi SB-SNPR.
After a long (s = 10) and very deep sleep (csmax = 0.5) the scientific awakening is just
before the first patent citation in 2002. After an increase in citations by other publications
until 2010, the scientific impact of the Haraguchi SB-SNPR decreases rapidly. The
technological impact of its citing patents, however, continues to increase substantially from
633 patent citations in the 5 years window to 1215 in a 15 years window (covering the
time period up to and including 2016).
Another interesting and more recent case in set 1 is the SB-SNPR by
Lu and Dahn
. It is not cited at all during its sleep period of 10 years, and thus this SB-SNPR is in
fact characterized by a very long ‘coma’. The authors discuss an X-ray diffraction study to
find the molecular structure of a metal oxide that is crucial in the construction of high
performance cathodes for rechargeable sodium ion batteries. During this coma period the
first patent citation is received 7 years after publication. Figure 6 shows the citation history
of the Lu and Dahn SB-SNPR. We see that the first citing patent act as the technological
prince, and this happens before the scientific prince arrives. After the scientific awakening
the impact of this SB-SNPR in terms of citations by other papers increases very rapidly.
The impact of the citing patents, however, is low as compared to the Haraguchi case (17
patent citations in the 5 year window) and increases hardly anymore. Thus, the Lu and
Dahn and the Haraguchi SB-SNPRs represent two quite opposite cases.
For SB-SNPRs in set 1 we found no significant correlation between the number of
citations by other publications during the awake period and both the number of patents that
cite the SB-SNPR as well as the number of time these patents are cited themselves by other
patents. This means that the scientific impact of Sleeping Beauties is generally not related
to the technological importance of the SBs, as far as measured with number and impact of
the citing patents.
For set 2 [sleep is short (s = 5) but coma (csmax = 0.0)] the 18 SB-SNPRs have been
cited by in total 37 patents. The majority of the 18 SB-SNPRs are cited by 1 to 3 patents
and one is cited by 17 patents of which the majority is cited by other patents. These cited
patents relate to 15 SB-SNPRs. Thus, also in set 2 the majority (83%) of the SB-SNPRs do
have patents that are cited by other patents after their publication. Similar to our analysis of
set 1, we apply also here a 5-year citation window. Taking the total of patent citations for
each SB-SNPR we again find that the distribution is very skew. For one SB-SNPR its citing
patents are cited 351 times, for four other SB-SNPRs it is between 10 and 50 times, and the
for the remaining SB-SNPRs it is between 1 and 6. The SB-SNPR with 351 patent citations
is published in 1991 and concerns a novel type switch chip with algorithms implemented in
(Katevenis et al. 1991)
. Also this technologically important SB-SNPR is not a
paper with a very high scientific impact in terms of citations by other publications, but still
it belongs to the top-25% of set 2. Scientifically this SB-SNPR slept in coma for 5 years,
but she awakened technologically already 2 years after her publication being cited by one
of the high impact patents.
Figure 7 shows the citation history of this Katevenis SB-SNPR. After a short (s = 5)
coma sleep (cs = 0.0) the scientific awakening is 3 years after the technological
awakening, i.e., the first patent citation in 1993. After a rapid increase in citations by other
publications until 2003, the scientific impact of the Katevenis SB-SNPR decreases. The
technological impact of its citing patents, however, increases from 351 patent citations in
the 5 years window to 585 in a 15 years window (covering the time period up to and
One of the most recent SB-SNPRs in set 2 is the paper by
Xiao et al. (2006)
authors discuss a method on the optical flow estimation related to the motion of objects in
computerized vision such as video and TV. Figure 8 shows the citation history of the Xiao
SB-SNPR. We see that already a year after its publication the first (and only) citing patent
was received. Also in this case clearly a technological prince, arrives before the scientific
awakening. After the scientific awakening the impact of the Xiao SB-SNPR in terms of
citations by other papers increases during a few years and then decreases. The impact of
the citing patent, however, is still increasing (29 citations by other patents in the 5-years
window, and 61 in a 10-years window) showing the importance of the technology related
to the Xiao SB-SNPR.
In the foregoing study
(van Raan 2017a)
we investigated the extent to which SB-SNPRs
are cited in patents of which at least one of the inventors is also an author of the cited
SBSNPR. Such an inventor-author self-citation may trigger a ‘self-awakening’ of the Sleeping
Beauty. We concluded however that only for a small minority (5%) of the Sleeping
Beauties that are cited in patents the authors are also inventors of the technology described
in the citing patent.
This study confirms the earlier observations. We find that in set 1 (long (s = 10) and
very deep (csmax = 0.5) sleep), the 44 SB-SNPRs with in total 141 authors are cited by 117
patents which have in total 425 inventors. Only in ten cases these inventors are also author,
and this concerns five different SB-SNPRs (of the 44). On the basis of the patent citation
year of the inventor-author patent we find that for four of the five SB-SNPRs the
inventorauthor patent did not trigger the scientific wakening. For one SB-SNPR the inventor-author
patent citation took place in the year of the scientific awakening, so here the
inventorauthor patent may have triggered the scientific awakening. Thus based on our observations
in set 1 we first conclude that inventor-author self-citation is quite rare, and, secondly, that
in most of the cases where inventor-author self-citation occurred, we found no trigger
effect for the scientific awakening.
In set 2 (short sleep (s = 5) but in coma (csmax = 0.0)) the 18 SB-SNPRs with in total
57 authors are cited by 37 patents which have in total 109 inventors. Only three of these
inventors are also author, and this concerns three different SB-SNPRs. One of these three is
the Katevenis SB-SNPR. Katevenis is the inventor of a patent that cites the Katevenis
Sleeping Beauty in 1995
(Katevenis et al. 1991)
, 4 years after the publication of the SB.
However, this inventor-author self-citation is not the first patent citation of the Katevenis
SB; as discussed in the foregoing section and shown in Fig. 7, the Katevenis SB was first
cited by a patent (of which Katevenis was not an inventor) 2 year after its publication. This
first patent citation clearly did not trigger the scientific awakening. Remarkably, the
inventor-author self-citation by the Katevenis patent is in the year just before the scientific
awakening. For the two other SB-SNPRs the inventor-author self-citation took place after
the scientific awakening.
We investigated characteristics of Sleeping Beauties that are cited in patents (SB-SNPRs)
with a focus on recent cases. In line with earlier observations in our previous study
we find that also in the case of recent Sleeping Beauties patent citation may
occur before or after the scientific awakening.
Another observation in the previous study was that the average time lag between the
publication year of an SB-SNPR and its first citation in a patent appears to decrease in the
1980s and early 1990s. In this study we find that this trend continues in the more recent
years, the later 1990s and the early 2000s. In other words, the time lag between the
publication year of the SB-SNPRs and their first citation in a patent is becoming shorter in
recent years. This means that, on average, in the more recent years SBs are awakened
increasingly earlier by a ‘technological prince’ than by a ‘scientific prince’. Thus, we think
that the question posed in the title of this paper can be answered with yes. We discussed
examples of this phenomenon, particularly the cases with a high technological impact of
the citing patents.
At the same time, we find that the increasing trend of the relative number of SBs
stopped around 1998. The above observations suggest the following possible scenario. We
think that SBs with technological importance are ‘discovered’ increasingly earlier in an
application-oriented context. Then, because of this earlier recognized technological
relevance, papers may be cited also earlier in a scientific context. Thus early recognized
technological relevance may ‘prevent’ papers to become an SB.
In this study we also find that the scientific impact of Sleeping Beauties is generally not
related to the technological importance of the SBs, as far as measured with number and
impact of the citing patents. In both sets of Sleeping Beauties analyzed in this study we do
find a relation of the scope of the journal in which the SBs are published with patent
citations: the SB-SNPRs are significantly more published in application-oriented journals
as compared to the SB-nonSPNRs. Given the fact that patents can be considered ‘solutions
to technical problems’ this focus of SB-SPNRs on application-oriented journals seems
In our previous study we found that only for a small minority of the Sleeping Beauties
that are cited in patents the authors are also inventors of the technology described in the
citing patent. This study confirms the earlier observation. In addition, the analysis of the
citation years of the inventor-author patents suggest that the scientific awakening of
Sleeping Beauties only rarely occurs by inventor-author self-citation.
Follow-up research will focus on two crucial issues. First, further evidence is needed to
support the observation made in this study that in the more recent years SBs are awakened
more and more earlier by a ‘technological prince’ than by a ‘scientific prince’. Secondly,
an analysis of the opinions of the SB authors as well as of the ‘princes’ is necessary to
answer the question whether a publication became a SB because it was (to far) ahead of its
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See Table 3.
WoS Fields codes and names of physics, chemistry, engineering and computer science
Engineering and computer science
WoS field code and name
Computer science, Artificial intelligence
Computer science, Cybernetics
Computer science, Hardware and architecture
Computer science, Information systems
Computer science, Interdisc applications
Computer science, Software engineering
Computer science, Theory and methods
Construction and building technology
Energy and fuels
Engineering, Electrical and electronic
Food science and technology
Instruments and instrumentation
Operations research and management science
Medical laboratory technology
Metallurgy and metallurgical engineering
Nuclear science and technology
Imaging science and photographic technology
Mining and mineral processing
Transportation science and technology
Critical care medicine
Integrative and complementary medicine
Nanoscience and nanotechnology
Cell and tissue engineering
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