Mathematical aspects of a new criterion for ranking scientific institutions based on the h-index

We develop and discuss the theoretical basis of a new criterion for ranking scientific institutions. Our novel index, which is related to the h-index, provides a metric which removes the size dependence. We discuss its mathematical properties such as merging rules of two sets of papers and analyze the relations between the underlying rank/citation-frequency law and the h-index. The proposed index should be seen as a complement to the h-index, to compare the scientific production of institutions (universities, laboratories or journals) that could be of disparate sizes.     

Creation of journal-based publication profiles of scientific institutions — A methodology for the interdisciplinary comparison of scientific research based on the J-factor

A form of normalisation is presented for the evaluation of citation data on multidisciplinary research. This method is based on the existing classification according to the publishing journals and not on the classification of output according to ISI subject categories. A publication profile is created for each institution to be investigated. This profile accounts for the weight of publications in a journal, represented by the number of publications as a proportion of the total output of the institution. In accordance with this weight, the citation rate of each journal is compared to a qualified relative indicator. The final result is a relative citation rate J, which is the relative perception of the performance of an institution accounting for its publication and citation habits and makes a transdisciplinary comparison possible.     

Mapping scientific institutions

We have developed a set of routines that allows to draw easily different maps of the research carried out in a scientific institution. Our toolkit uses OpenSource elements to analyze bibliometric data gathered from the Web Of Science. We take the example of our institution, ENS de Lyon, to show how different maps, using co-occurrence (of authors, keywords, institutions…) and bibliographic coupling can be built. These maps may become a valuable tool for discussing institutions’ policies, as they offer different views on the institution at a global scale.     

Neophilia ranking of scientific journals

The ranking of scientific journals is important because of the signal it sends to scientists about what is considered most vital for scientific progress. Existing ranking systems focus on measuring the influence of a scientific paper (citations)—these rankings do not reward journals for publishing innovative work that builds on new ideas. We propose an alternative ranking based on the proclivity of journals to publish papers that build on new ideas, and we implement this ranking via a text-based analysis of all published biomedical papers dating back to 1946. In addition, we compare our neophilia ranking to citation-based (impact factor) rankings; this comparison shows that the two ranking approaches are distinct. Prior theoretical work suggests an active role for our neophilia index in science policy. Absent an explicit incentive to pursue novel science, scientists underinvest in innovative work because of a coordination problem: for work on a new idea to flourish, many scientists must decide to adopt it in their work. Rankings that are based purely on influence thus do not provide sufficient incentives for publishing innovative work. By contrast, adoption of the neophilia index as part of journal-ranking procedures by funding agencies and university administrators would provide an explicit incentive for journals to publish innovative work and thus help solve the coordination problem by increasing scientists’ incentives to pursue innovative work.     

A methodology for developing scientific diversification strategy of countries

Scientometrics - This paper introduces the use of co-nomination as a method to map research fields by directly accessing their knowledge networks organised around exchange relationships of...     

A semi-quantitative reasoning methodology for filtering and ranking HAZOP results in HAZOPExpert

Hazard and Operability (HAZOP) analysis is the most widely used and recognized as the preferred Process Hazards Analysis (PHA) approach in the chemical process industry. Recently, a diagraph-model based framework and an expert system called HAZOPExpert was developed for automating this analysis. Upon testing the performance of the system on various industrial case studies. HAZOPExpert was found to successfully mimic the human expert's reasoning and identify the hazards. But, with the increasing complexity of the processes, the HAZOPExpert system generated a large number of consequences compared to those identified by a team of experts. This is mainly due to the strict qualitative reasoning approach implemented in the HAZOPExpert system. In order to filter and rank the consequences generated by the HAZOPExpert system, a semi-quantitative reasoning methodology is proposed using additional quantitative knowledge in the form of design and operating specifications of the process units, and process material property values. This filtering approach combines the qualitative digraph-based HAZOP models and the quantitative knowledge to eliminate the unrealizable consequences. Significant reduction in the number of consequences was obtained using this approach on an ethylene process plant HAZOP case study.     

A decision making methodology for material selection using an improved compromise ranking method

An ever increasing variety of materials is available today, with each having its own characteristics, applications, advantages, and limitations. In choosing the right material, there is not always a single definite attribute of selection and the designers and engineers have to take into account a large number of material selection attributes. This paper presents a logical procedure for material selection for a given engineering application. The procedure is based on an improved compromise ranking method considering the material selection attributes and their relative importance for the application considered. Two examples are included to illustrate the approach.     

A new quantification algorithm for the GO methodology

This paper provides a new quantification algorithm in the GO methodology, which includes three parts: (1) A signal state cumulative probability is introduced and defined based on the definitions of the signal states in the GO method. (2) The quantitative formulas of signal state cumulative probabilities have been derived, so it is unnecessary to calculate the joint probability of the complex combination of states. (3) The calculation process and the transfer rules about the shared signal have been presented, therefore, the new algorithm permits the direct calculation of all signal state cumulative probability. The new algorithm is very easy for programming. It is an improved algorithm in the GO methodology instead of the joint probability algorithm. The result of an example shows that the algorithm is practical and meaningful for development and application of the GO methodology and useful in practice.     

Development of a database: DACTARI for a radiotoxic element ranking methodology

Dosimetric impact studies aim at evaluating potential radiological effects of chronic or acute releases from nuclear facilities. A methodology for ranking radionuclides (RN) in terms of their health-related impact on the human population was first developed at CEA with specific criteria for each RN that could be applied to a variety of situations. It is based, in particular, on applying physico-chemical criteria to the complete RN inventory (present in the release or in the source term) and on applying norms related to radiation protection and chemical toxicology. The initial step consisted in identifying and collecting data necessary to apply the methodology, with reference to a previous database of long-lived radionuclides (LLRN, with half-lives ranging from 30 to 10(14) y) containing 95 radionuclides. The initial results have allowed us to identify missing data and revealed the need to complete the study for both toxic and radiotoxic aspects. This led us to the next step, developing a specific database, DAtabase for Chemical Toxicity and Radiotoxicity Assessment of RadIonuclides (DACTARI), to collect data on chemical toxicity and radiotoxicity, including acute or chronic toxicity, the chemical form of the compounds, the contamination route (ingestion, inhalation), lethal doses, target organs, intestinal and maternal-foetal transfer, drinking water guidelines and the mutagenic and carcinogenic properties.     

A new methodology for quantitative LSPR biosensing and imaging

A new quantitative analysis methodology for localized surface plasmon resonance (LSPR) biosensing which determines surface-receptor fractional occupancy, as well as an LSPR imaging technique for the spatiotemporal mapping of binding events, is presented. Electron beam nanolithography was used to fabricate 20 × 20 arrays of gold nanostructures atop glass coverslips. A single biotinylated array was used to measure the association kinetics of neutravidin to the surface by spectroscopically determining the fractional occupancy as a function of time. By regenerating the same array, a reliable comparison of the kinetics could be made between control samples and neutravidin concentrations ranging from 1 μM to 50 nM. CCD-based imagery of the array, taken simultaneously with the spectroscopic measurements, reveals the binding of neutravidin to the surface as manifested by enhanced scattering over the majority of the resonance peak. The temporal resolution of the LSPR imaging technique was 200 ms and the spatial resolution was 8 μm(2).     

Review on ranking and selection: A new perspective

In this paper, we briefly review the development of ranking and selection (R&S) in the past 70 years, especially the theoretical achievements and practical applications in the past 20 years. Different from the frequentist and Bayesian classifications adopted by Kim and Nelson (2006b) and Chick (2006) in their review articles, we categorize existing R&S procedures into fixed-precision and fixed-budget procedures, as in Hunter and Nelson (2017). We show that these two categories of procedures essentially differ in the underlying methodological formulations, i.e., they are built on hypothesis testing and dynamic programming, respectively. In light of this variation, we review in detail some well-known procedures in the literature and show how they fit into these two formulations. In addition, we discuss the use of R&S procedures in solving various practical problems and propose what we think are the important research questions in the field.     

Profiling citation impact: A new methodology

A methodology for creating bibliometric impact profiles is described. The advantages of such profiles as a management tool to supplement the reporting power of traditional average impact metrics are discussed. The impact profile for the UK as a whole reveals the extent to which the median and modal UK impact values differ from and are significantly below average impact. Only one-third of UK output for 1995-2004 is above world average impact although the UK’s average world-normalised impact is 1.24. Time-categorised impact profiles are used to test hypotheses about changing impact and confirm that the increase in average UK impact is due to real improvement rather than a reduction in low impact outputs. The impact profile methodology has been applied across disciplines as well as years and is shown to work well in all subject categories. It reveals substantial variations in performance between disciplines. The value of calculating the profile median and mode as well as the average impact are demonstrated. Finally, the methodology is applied to a specific data-set to compare the impact profile of the elite Laboratory of Molecular Biology (Cambridge) with the relevant UK average. This demonstrates an application of the methodology by identifying where the institute’s exceptional performance is located. The value of impact profiles lies in their role as an interpretive aid for non-specialists, not as a technical transformation of the data for scientometricians.     

Tweet Coupling: a social media methodology for clustering scientific publications

Scientometrics - We argue that classic citation-based scientific document clustering approaches, like co-citation or Bibliographic Coupling, lack to leverage the social-usage of the scientific...     

A new explicit variable time-integration self-starting methodology for computational structural dynamics

A new explicit variable time-integration methodology and architecture which possesses self-starting attributes, eliminates the need to involve acceleration computations, and which has improved accuracy characteristics in comparison to the traditional central-difference-type formulations customarily advocated is described for applicability to computational structural dynamics. To sharpen the focus of the present study, an explicit variable time-integration architecture which is relatively simple, yet effective, is described. Unlike variable explicit time-integration formulations adopted in the past, the present self-starting variable time-integration architecture and implementation aspects facilitate a simplified representation and a straightforward and effective approach for combining finite element meshes requiring different time steps in a single analysis. Numerical test cases are provided which demonstrate the applicability of the proposed formulations.     

A new indicator for international visibility: exploring Brazilian scientific community

Brazilian science has increased fast during the last decades. An example is the increasing in the country’s share in the world’s scientific publication within the main international databases. But what is the actual weight of international publications to the whole Brazilian productivity? In order to respond this question, we have elaborated a new indicator, the International Publication Ratio (IPR). The data source was Lattes Database, a database organized by one of the main Brazilian S&;T funding agency, which encompasses publication data from 1997 to 2004 of about 51,000 Brazilian researchers. Influences of distinct parameters, such as sectors, fields, career age and gender, are analyzed. We hope the data presented may help S&;T managers and other S&;T interests to better understand the complexity under the concept scientific productivity, especially in peripheral countries in science, such as Brazil.     

Language use reflects scientific methodology: A corpus-based study of peer-reviewed journal articles

Recently, philosophers of science have argued that the epistemological requirements of different scientific fields lead necessarily to differences in scientific method. In this paper, we examine possible variation in how language is used in peer-reviewed journal articles from various fields to see if features of such variation may help to elucidate and support claims of methodological variation among the sciences. We hypothesize that significant methodological differences will be reflected in related differences in scientists’ language style. This paper reports a corpus-based study of peer-reviewed articles from twelve separate journals in six fields of experimental and historical sciences. Machine learning methods were applied to compare the discourse styles of articles in different fields, based on easily-extracted linguistic features of the text. Features included function word frequencies, as used often in computational stylistics, as well as lexical features based on systemic functional linguistics, which affords rich resources for comparative textual analysis. We found that indeed the style of writing in the historical sciences is readily distinguishable from that of the experimental sciences. Furthermore, the most significant linguistic features of these distinctive styles are directly related to the methodological differences posited by philosophers of science between historical and experimental sciences, lending empirical weight to their contentions.     

A methodology for evaluating appropriateness of new energy resources in rural applications

In this paper a method to determine the appropriateness of energy resources in rural applications is discussed. Feasible energy resources are comparatively evaluated using eight attributes representing the criteria of appropriateness. ‘Appropriateness’ is defined as a linear combination of attribute weights multiplied by attribute attainment levels which have been mapped into utility for decision-makers. The uncertainty in data is handled using Monte-Carlo techniques. Sample results indicate a set of dominant energy resources for a particular task. This method can be applied in real-life decision making concerning energy resources for rural applications.     

Important institutions of interinstitutional scientific collaboration networks in materials science

Interinstitutional scientific collaboration plays an important role in knowledge production and scientific development. Together with the increasing scale of scientific collaboration, a few institutions that positively participate in interinstitutional scientific collaboration are important in collaboration networks. However, whether becoming an important institution in collaboration networks could be a contributing factor to research success and how these important institutions collaborate are still indistinct. In this paper, we identified the scientific institutions that possess the highest degree centrality as important institutions of an interinstitutional scientific collaboration network in materials science and examined their collaboration preferences utilizing several network measures. We first visualized the appearance of these important institutions that had the most positive collaborations in the interinstitutional scientific collaboration networks during the period of 2005–2015 and found an obvious scale-free feature in interinstitutional scientific collaboration networks. Then, we measured the advantages of being important in collaboration networks to research performance and found that positive interinstitutional collaborations can always bring both publication advantages and citation advantages. Finally, we identified two collaboration preferences of these important institutions in collaboration networks—one type of important institution represented by the Chinese Academy of Science plays an intermediary role between domestic institutions and foreign institutions with high betweenness centrality and a low clustering coefficient. This type of important institution has better performance in the number of publications. The other type of important institution represented by MIT tends to collaborate with similar institutions that have positive collaborations and possess a larger citation growth rate. Our finding can provide a better understanding of important institutions’ collaboration preferences and have significant reference for government policy and institutional collaboration strategies.