RESEARCH IMPACT: LEVEL OF RESULTS, CITATION, MERIT
The appeal of metric evaluation of research impact has attracted considerable interest in recent times. Although the public at large and administrative bodies are much interested in the idea, scientists and other researchers are much more cautious, insisting that metrics are but an auxiliary instrument to the qualitative peer-based judgement. The goal of this article is to propose availing of such a well positioned construct as domain taxonomy as a tool for directly assessing the scope and quality of research. We first show how taxonomies can be used to analyse the scope and perspectives of a set of research projects or papers. Then we proceed to define a research team or researcher’s rank by those nodes in the hierarchy that have been created or significantly transformed by the results of the researcher. An experimental test of the approach in the data analysis domain is described. Although the concept of taxonomy seems rather simplistic to describe all the richness of a research domain, its changes and use can be made transparent and subject to open discussions.
Three different approaches for evaluation of the research impact by a scientist are considered. Two of them are conventional ones, scoring the impact over (a) citation metrics and (b) merit metrics. The third one relates to the level of results. It involves a taxonomy of the research field, that is, a hierarchy representing its composition. The impact is evaluated according to the taxonomy ranks of the subjects that have emerged or have been crucially transformed due to the results by the scientist under consideration Mirkin (Control Large Syst Spec Issue 44:292–307, 2013). To aggregate criteria in approaches (a) and (b) we use an in-house automated criteria weighting method oriented towards as tight a representation of the strata as possible Orlov (Bus Inf, 2014). To compare the approaches empirically, we use publicly available data of about 30 scientists in the areas of data analysis and machine learning. As our taxonomy of the field, we invoke a corresponding part of the ACM Computing Classification System 2012 and slightly modify it to better reflect results by the scientists in our sample. The obtained ABC stratifications are rather far each other. This supports the view that all the three approaches (citations, merits, taxonomic rank) should be considered as different aspects, and, therefore, a good method for scoring research impact should involve all the three.
Indicators of publication activity recognized as one of the main output measures of scientific work at the organizational level as well as ways to assess "visibility" and to compare the positions of countries at the global arena. The paper explores dynamics of the main bibliometric indicators that characterize the overall productivity and recognition of Russian authors from 2000 to 2014. The analysis is based on information derived from the Web of Science database for the above-mentioned period. The results show that despite the steady growth of the publication activity level and noticeable representation of papers in global research fronts, Russian researchers are likely to contribute to the knowledge development locally rather than globally; international cooperation is carried out in well established and even «traditional» areas for the country and based on long-term partnerships with a selected number of countries.
A model for organizing cargo transportation between two node stations connected by a railway line which contains a certain number of intermediate stations is considered. The movement of cargo is in one direction. Such a situation may occur, for example, if one of the node stations is located in a region which produce raw material for manufacturing industry located in another region, and there is another node station. The organization of freight traﬃc is performed by means of a number of technologies. These technologies determine the rules for taking on cargo at the initial node station, the rules of interaction between neighboring stations, as well as the rule of distribution of cargo to the ﬁnal node stations. The process of cargo transportation is followed by the set rule of control. For such a model, one must determine possible modes of cargo transportation and describe their properties. This model is described by a ﬁnite-dimensional system of diﬀerential equations with nonlocal linear restrictions. The class of the solution satisfying nonlocal linear restrictions is extremely narrow. It results in the need for the “correct” extension of solutions of a system of diﬀerential equations to a class of quasi-solutions having the distinctive feature of gaps in a countable number of points. It was possible numerically using the Runge–Kutta method of the fourth order to build these quasi-solutions and determine their rate of growth. Let us note that in the technical plan the main complexity consisted in obtaining quasi-solutions satisfying the nonlocal linear restrictions. Furthermore, we investigated the dependence of quasi-solutions and, in particular, sizes of gaps (jumps) of solutions on a number of parameters of the model characterizing a rule of control, technologies for transportation of cargo and intensity of giving of cargo on a node station.
Event logs collected by modern information and technical systems usually contain enough data for automated process models discovery. A variety of algorithms was developed for process models discovery, conformance checking, log to model alignment, comparison of process models, etc., nevertheless a quick analysis of ad-hoc selected parts of a journal still have not get a full-fledged implementation. This paper describes an ROLAP-based method of multidimensional event logs storage for process mining. The result of the analysis of the journal is visualized as directed graph representing the union of all possible event sequences, ranked by their occurrence probability. Our implementation allows the analyst to discover process models for sublogs defined by ad-hoc selection of criteria and value of occurrence probability
The geographic information system (GIS) is based on the first and only Russian Imperial Census of 1897 and the First All-Union Census of the Soviet Union of 1926. The GIS features vector data (shapefiles) of allprovinces of the two states. For the 1897 census, there is information about linguistic, religious, and social estate groups. The part based on the 1926 census features nationality. Both shapefiles include information on gender, rural and urban population. The GIS allows for producing any necessary maps for individual studies of the period which require the administrative boundaries and demographic information.
Existing approaches suggest that IT strategy should be a reflection of business strategy. However, actually organisations do not often follow business strategy even if it is formally declared. In these conditions, IT strategy can be viewed not as a plan, but as an organisational shared view on the role of information systems. This approach generally reflects only a top-down perspective of IT strategy. So, it can be supplemented by a strategic behaviour pattern (i.e., more or less standard response to a changes that is formed as result of previous experience) to implement bottom-up approach. Two components that can help to establish effective reaction regarding new initiatives in IT are proposed here: model of IT-related decision making, and efficiency measurement metric to estimate maturity of business processes and appropriate IT. Usage of proposed tools is demonstrated in practical cases.