We estimated the level of interactions between all the pairs of the research groups and between all the pairs of the research divisions for 4 five-year periods on base of Dimensions data. The level of interactions is assessed by Jaccard index. Paired interaction for research divisions shows that every consecutive five-year period has decreased irregularity of its distribution of interaction. Cumulative interaction shows that all research divisions tend to have their stickiness index decreased over time. Paired interaction for research groups showed the same results but difference between two consecutive periods is greater by a larger factor. On base of interacting assessments we identified 5 research groups that have been suspiciously assigned to divisions in ANZSRC. Identified research groups have more similar research groups in concurrent divisions with statistically significant level. Those 5 research groups also have strong semantic ties with concurrent divisions, this can be an argument for adapting of ANZSRC.
Interdisciplinarity is a fashion direction in modern education and science. Inter-disciplinarity is impossible without interactions between research from various fields. For quantitative assessment of level of interdisciplinarity, of level different research fields interactions a lot of approaches are proposed in recent years.
Currently the most widely used approaches to quantitative measuring of interdisciplinarity use
bibliometrics. They take into account co-authorships, collaborations, references, citations and
cocitations. The most common bibliometric technique for measuring inderdisciplinarity is some kind of
citation analysis. A citation environment is defined as all journals that cite or are cited by a specific
journal [
In [
Another approach based on citations is presented in [
A slightly less used approach for measuring interdisciplinarity using bibliometric uses
collaborations. In [
Some of the studies use text analysis to quantify the interaction and evolution of scientific
disciplines. In [
All the above mentioned approaches require large information resources. Methods that based on
citation analysis, are pretty inertial. It is impossible to assess interdisciplinarity of a new paper
instantly, because citations take time to take place. As opposed to the mentioned approaches, paper [
The current paper extends idea of [
Dimensions uses two-level version of ANZSRC. There are 22 research divisions at high level with 157 groups at low level. For example, division 08 Information and Computing Sciences contains the following research groups: 0801 Artificial Intelligence and Image Processing; 0802 Computation Theory and Mathematics; 0803 Computer Software; 0804 Data Format; 0805 Distributed Computing; 0806 Information Systems; 0807 Library and Information Studies; 0899 Other Information and Computing Sciences.
Dimensions has indexed over 110M research papers. Each paper is assigned to one or several
research groups. Such categorization is carried out in by Dimensions itself by special software based on
machine learning guided by topic experts [
Based on Dimensions data we can retrieve a number of papers assigned to each research division.
At the same time, we can get the number of above-mentioned papers that were assigned to several
research divisions simultaneously. By using this information we assess the interaction of any pair of
research divisions using 2 queries. According to [
N AB N A N B N AB , where N A is a number of papers in division A; N B is a number of papers in research division B; N AB is a number of papers assigned to divisions A and B simultaneously.
For example, there are 353 347 papers assigned to division 08 Information and Computing Sciences in 2019, and 11391 of them also belong to division 17 Psychology and Cognitive Sciences. Division 17 consists of 178 156 papers published in 2019. Hence, the quantitative assessment of interaction of these divisions is S(08, 17) 11391 0.021 .
353347 178156 11391
Jaccard index distributions for two research divisions within the four of the five-year periods are shown in Figure 1. The x-axis corresponds to ranked list of pairs of divisions sorted ascending for each period separately. The y-axis corresponds to their level of interaction plotted in log scale. Overall, we analyzed 231 pairs of divisions. Figure 1 shows that every consecutive five-year period has decreased irregularity of its distribution of interaction. We can see that by observing that pairs of divisions from the beginning of Jaccard index distribution has their interaction decreased over time and the pairs at the end of the distribution on the contrary – increased. This observation is confirmed by Gini coefficient that decreases in time in the following way:
GiniD (2001 2005 ) 0.739 ; GiniD (2006 2010 ) 0.737 ; GiniD (2011 2015 ) 0.733 ; GiniD (2016 2020 ) 0.733 .
Also, we observe decrease of D mean (S Q4 ) – ratio of mean value of Jaccard indexes from mean (S Q1) the fourth and the first quartiles as follows: D (2001 2005 ) 434.9 ; D (2006 2010 ) 372.1; D (2011 2015 ) 288 .1 ; D (2016 2020 ) 250.7 .
Figure 2 shows the dynamic of interaction of the most tied divisions. For each five-year period 5 pairs of divisions with the greatest Jaccard index are selected. For the first three periods, we observe the same leaders of divisions’ pairs: 20 Language, Communication and Culture & 21 History and Archaeology; 01 Mathematical Sciences & 02 Physical Sciences; 19 Studies in Creative Arts and Writing & 20 Language, Communication and Culture; 02 Physical Sciences & 09 Engineering; 21 History and Archaeology & 22 Philosophy and Religious Studies.
Two last pairs of the leaders moved down to the 6-th and 10-th positions respectively in the last period. The following pairs replaced them: 03 Chemical Sciences & 09 Engineering, and 05 Environmental Sciences & 06 Biological Sciences. Among seven leaders the following pair 02 Physical Sciences & 09 Engineering has the highest decrease in interaction. Its Jaccard index dropped from 0.1085 in 2001–2005 to 0.0600 in 2016–2020. The data for the last 2 years shows that the decrease has stopped – Jaccard index increased by a tiny value from 0.0595 in 2019 to 0.0560 in 2020. Among leaders, the highest increasing in interaction is demonstrated by pair 05 Environmental Sciences & 06 Biological Sciences. It moved down from the position #12 in the first period to position #4 in the last period. The data for the last 2 years shows that interaction between divisions 05 and 06 continues to grow with 4.8% per year rate.
Figure 3 shows dynamic for the most changeable pairs of research divisions. We considered only pairs that at least in one of the periods has fallen into a quartile with the greatest values of Jaccard index. Within these pairs, we chose the 6 most dynamic; the one that has their Jaccard index changed the most in terms of increasing and decreasing between the first (2001-2005) and last (2016-2020) periods. Among chosen pairs the most rapid decrease in interaction happened for divisions 14 Economics & 22 Philosophy and Religious Studies – it has dropped from 0.031 in 2001-2005 to 0.0121 in 2016-2020. The data for the last 2 years shows that it continues to decrease with 9.4% per year rate. In 2020, Jaccard index for divisions 14 & 22 takes a value of 0.0096. For all time of observations, the highest increase in interaction happens for divisions 03 Chemical Sciences & 10 Technology – from 0.0073 in 2001-2005 to 0.0241 in 2016-2020. However, in the last five-year period the increase has stopped. The data for the last 2 years shows that decrease is present with a rate of -9% per year. In 2020, Jaccard index for divisions 03 Chemical Sciences & 10 Technology takes value of 0.0203. For the last 2 years, interaction between divisions 03 Chemical Sciences & 05 Environmental Sciences has increased drastically (24%). In 2020 Jaccard index for divisions 03 Chemical Sciences & 05 Environmental Sciences takes a value of 0.024.
In addition to paired interaction, we analyzed the cumulative interaction of divisions. For this
stickiness index [
G( A)
S( A, p) , p: pF, pA where F denotes a set of research divisions.
In addition to research divisions based on Dimensions data we can retrieve a number of papers assigned with each research group. At the same time, we can get a number of above-mentioned papers that were assigned to several research groups simultaneously. By using this data, we can assess the level of interaction between two research groups in the same way as for divisions. For example, there are 80115 papers assigned to group 0806 Information Systems in 2019, and 2934 of them also belong to group 1503 Business and Management. Group 1503 consist of 59662 papers published in 2019. ness and Management is S(0806, 1503)
Figure 5 shows the Jaccard index distributions for pairs of research groups with different divisions within the four of the five-year periods. We empirically set a threshold for a number of papers for a research division to be 1000, so that research divisions with less than 1000 papers are not considered. In total 145 research groups are considered, hence the interactive level of 10440 pairs of the research groups for each five-year period were calculated. Most of the research groups have zero Jaccard index. Figure 4 shows the same results as with the research divisions’ interactions. But now the pairs at the end of the distribution have their interactions increased by a larger factor which shows that as the time goes on interdisciplinarity between research divisions increases. This can be seen by looking at Figure 5 and observing that the first period 2001-2005 has 334 pairs of research divisions with Jaccard index greater than zero. The last period has 551 pairs, which give an increase of 217 pairs over the last 2 decades. The same effect shows Gini coefficient that decreases in time in the following way: GiniG (2001 2005 ) 0.983 ; GiniG (2006 2010 ) 0.98 ; GiniG (2011 2015 ) 0.978 ;
GiniG (2016 2020 ) 0.975 .
Figure 6 shows the dynamic of the interaction for the most tied groups. We apply the same selection here as for the divisions. For the all four periods, we observe the following 3 lea ders that always stay in the top 5: 1205 Urban and Regional Planning & 1507 Transportation and Freight Services; 1903 Journalism and Professional Writing & 2001 Communication and Media Studies; 1902 Film, Television and Digital Media & 2001 Communication and Media Studies.
Some of the leaders increase interaction as time goes on, some decrease interaction, some switch between increasing and decreasing interaction. A trend towards increasing interaction shows 0502 Environmental Science and Management & 0602 Ecology. This pair increases the interaction from 0.11 in the first period to 0.16 in the last period. A trend towards decreasing interaction show a few pairs of groups: 1205 Urban and Regional Planning & 1507 Transportation and Freight Services, 1903 Journalism and Professional Writing & 2001 Communication and Media Studies, and 0702 Animal Production & 0908 Food Sciences. They decrease interaction for the first 3 periods but have a slight increase for the last period. Hence, no leader changed its interactive level significantly.
Figure 7 shows dynamic for the most changeable research groups. We use the same approach as with the research divisions’ selection. Overall we analyzed the 6 most changeable research groups: 0399 Other Chemical Sciences & 0699 Other Biological Sciences; 0206 Quantum Physics & 0906 Electrical and Electronic Engineering; 0601 Biochemistry and Cell Biology & 1112 Oncology and Carcinogenesis; 0401 Atmospheric Sciences & 0912 Materials Engineering; 0202 Atomic, Molecular, Nuclear, Particle and Plasma Physics & 0307 Theoretical and Computational Chemistry; 0401 Atmospheric Sciences & 0901 Aerospace Engineering.
Among chosen pairs the most rapid increase in interaction happened for groups 0399 Other Chemical Sciences & 0699 Other Biological Sciences – it has increased at 378% from 0.02113 in 20012005 to 0.10121 in 2016-2020. In 2020 Jaccard index for this pair equals 0.1411. But, the year pace fell, and became 9.1% for 2019–2020. The pair 0206 Quantum Physics & 0906 Electrical and Electronic Engineering has increased interaction at 288% from 0.00634 to 0.02464. In 2020 Jaccard index for this pair equals 0.0258. But, the year pace fell, and became 7.1% for 2019–2020. The pair 0601 Biochemistry and Cell Biology & 1112 Oncology and Carcinogenesis has increased interaction from 0.00630 to 0.01869. The most rapid decrease in interactions is observed for the pair 0401 Atmospheric Sciences & 0912 Materials Engineering with moving from 0.00834 to 0.00125 (about 84%). The pairs 0202 Atomic, Molecular, Nuclear, Particle and Plasma Physics & 0307 Theoretical and Computational Chemistry and 0401 Atmospheric Sciences & 0901 Aerospace Engineering show approximately the same decrease in interaction at about 80%.
We also observed that many pairs of research groups have moved from zero interaction to greater than zero and vice versa. According to our calculations 235 pairs of research groups has exceeded zero interaction and only 18 pairs has reached zero interaction when comparing the first (2001-2005) and last (2016-2020) periods. It conforms to earlier evidence about the increase of interdisciplinarity on the low level.
As well as with research divisions, we analyzed the cumulative interaction of groups. We used the same formula of stickiness index but, naturally, applied to Jaccard indexes of research groups. The distributions of stickiness indexes for each of the periods are shown in Figure 8. The leaders by stickiness index are: 0502 Environmental Science and Management; 2001 Communication and Media Studies; 1205 Urban and Regional Planning.
Figure 8 confirms to the previous conclusion regarding to divisions and shows that with time research groups tend to have a more equally distributed stickiness index. It is also observed from the number of research groups that increased their stickiness index from zero to greater than zero. 11 research groups have increased their stickiness index from zero in the first period to positive number in the last period, and only one research group has decreased it to zero. The same effect shows Gini index for the stickiness index that decreases from 0.4722 in the first period to 0.4519 in the last period. For all time of observations, the most rapid decrease in stickiness index took place for the following research groups: 1603 Demography – -92%; 1301 Education Systems – -83%; 0901 Aerospace Engineering – -71%; 0307 Theoretical and Computational Chemistry – -59%; 1101 Medical Biochemistry and Metabolomics – -59%.
ANZSRC as any hierarchical classifying system tries to combine the similar objects in the same cluster and makes any two clusters dissimilar. Hence, a research group has to be more similar, has to have higher interaction with the research groups inside its division, than with the research groups from any other division. To formalize this thesis regarding to research group G11 from division D1 we introduce the following:
1) G12 and G13 denote research groups with highest interaction with G11 inside division D1 , and besides J (G11, G12) J (G11, G13) ; 2)
G22 and G23 denote research groups from division D2 , which are most tied with the research group G11 from division D1 , and besides J (G11, G22) J (G11, G23) .
Assumption: research group G11 is assigned suspiciously to division D1 , if J (G11, G12) J (G11, G22) AND J (G11, G13) J (G11, G23) . In this case, division D2 is more suitable for research group G11 , than division D . Hence, ANZSRC may be improving its classifying system by 1 moving research group G11 from division D1 to division D2 .
We checked all the research groups on base of their Jaccard index for 2016-2020 data and found 5 problem research groups according to proposed Assumption (Table 1). For reliability reason only research groups with J (G11, G23) 0.05 are considered.
According to Table 1 the following changes in ANZSRC are proposed: 1) move 2001 Communication and Media Studies from 20 Language, Communication and Culture to 19 Studies in Creative Arts and Writing; 2) move 0909 Geomatic Engineering from 09 Engineering to 04 Earth Sciences; 3) move 1502 Banking, Finance and Investment from 15 Commerce, Management, Tourism and Services to 14 Economics; 4) move 0105 Mathematical Physics from 01 Mathematical Sciences to 02 Physical Sciences; 5) move 0602 Ecology from 06 Biological Sciences to 05 Environmental Sciences.
We analyzed the interaction of research divisions and research groups for 4 five-year periods. The level of interactions is assessed by Jaccard index. We analyzed paired and cumulative interaction for both research divisions and research groups. Only research groups of different research divisions were considered. Paired interaction allowed to find pairs that interact the most and analyze the behavior of different interactions over time.
Using paired interaction we analyzed leaders and the most changeable research divisions and groups in terms of interaction. Paired interaction for research divisions shows that every consecutive five-year period has decreased irregularity of its distribution of interaction. This also confirms the Gini index and the number of pairs with non-zero interaction. Cumulative interaction shows that all research divisions tend to have their stickiness decreased over time. The same effect shows Gini index for the stickiness index that decreases from 0.197 in the first period (2001-2005) to 0.188 in the last period (2016-2020).
Paired interaction for research groups showed the same results but difference between two consecutive periods is greater by a larger factor. Cumulative interaction for research groups showed that with time research groups tend to have a more equally distributed stickiness index. It is also observed from the number of research groups that increased their stickiness index from zero to greater than zero and Gini index.
On base of interacting assessments during 2016-2020 we identified 5 research groups that have been assigned suspiciously to divisions in ANZSRC. They are as follows: 0105 Mathematical Physics, 0602 Ecology, 0909 Geomatic Engineering, 1502 Banking, Finance and Investment and 2001 Communication and Media Studies. All the mentioned research groups have at least a pair of more similar research groups in concurrent divisions with statistically significant level. Those 5 research groups also have strong semantic ties with concurrent divisions, this can be an argument for adapting of ANZSRC.