Visualization of Data Science Community in Russia.
We present in the form of two visualizations some preliminary results of the ongoing study of data science community in Russia. The rst visualization aggregates data about top researches and their elds of interest according to the Google Scholar service. The second graph is a map of the largest online communities on date science on VKontakte platform.
In this paper, we present our current research regarding information interaction strategies of students of minor specialization in Data Science. We employed an online platform, consisted of a third-party and our software, to provide students with means of learning and analyse their learning activity. We developed several indicators to estimate their activity: coding activity, friends network size, and Q&A activity. We show that high-achieving and low-achieving students use resources in different ways, with substantial inequality in resource access/use. Based on the research, we propose two features that supposedly would provoke students to participate in a Q&A activity decreasing inequality in the use of these resources.
Following the great success of DSAA’2014 in Shanghai, the 2015 IEEE International Conference on Data Science and Advanced Analytics (IEEE DSAA’2015), to be held on 19-21 October 2015 in Paris, has seen the significant growth of the number of submissions, participates, sponsors and key stakeholders. Without any doubt, DSAA has been recognized to be the first and most influential event in the data science and analytics focused community. Data driven scientific discovery and innovation and practical development, applications and economy have been increasingly recognized as the major trend of future IT and business. Data science, big data and advanced analytics play the most important role in driving data innovation and economy. DSAA thus carries a critical role in substantially promoting and strengthening the above trends and results.
In this paper we consider formal model of an online community as a combination of social and semantic networks. An approach is suggested to measurement of maturity level of a professional community based on two groups of parameters, which characterize competency level and density of contacts correspondingly. We present preliminary results of the pilot testing of the proposed approach for evaluating several city IT-communities in Central Russia. The paper is based on the authors’ experience and achievements obtained in their work to develop Virtual Skolkovo online community.
The article concerns views of Russian advokats with regard to issues of professional ethics as well as their evaluation of frequency of violation of rights of defendants by representatives of low-enforcement agencies. The basis for analysis was the data of interrogation of advokats carried out in 2013 by by the Institute of Analysis of Enterprises and Markets of the National Research University "Higher School of Economics" in combination with the "Association of Lawyers of Russia". The authors show that professional community of advokats constantly interacting judicial and law-enforcement systems could be important sourse of information on the state of inforesement for authorities and society.
Software system Cordiet-FCA is presented, which is designed for knowledge discovery in big dynamic data collections, including texts in natural language. Cordiet-FCA allows one to compose ontology-controlled queries and outputs concept lattice, implication bases, association rules, and other useful concept-based artifacts. Efficient algorithms for data preprocessing, text processing, and visualization of results are discussed. Examples of applying the system to problems of medical diagnostics, criminal investigations are considered.