Russian Science Citation Index: Areas for Development Identified by Active Users

The current state of the Russian Science Citation Index is analyzed. Several areas for its further development identified by long-standing active users, such as data searching, refinement, and storage; current user alerts; data input with the Science Index license; patent information; and the application programming interface (API) are investigated.     

Interdisciplinary scholarly collaboration in data-intensive,public-funded,international digital humanities project work

The information practices of collaborative interdisciplinary researchers, especially in distributed environments, remain understudied. Embracing the naturalistic paradigm, this qualitative case study relies upon semi-structured interviews, snowball sampling, and grounded analysis. Based on interviews with 53 participants from 11 Digging Into Data 3 (DID3, 2014-2016) projects, this study examines the working practices of scholars (library and information science professionals, humanists, and computer scientists) engaging in collaborative, international, data-intensive, publicly-funded interdisciplinary research. Benefits of such work include avoiding redundancy, exploding disciplinary silos, and more ambitious, larger-scale outputs. Challenges and lessons learned center on innovation, flexibility, and failure, translation, intermediaries, divisions of labor and delegation of responsibilities and tasks, conflict resolution, technology, outputs and publication, and timeframe, sustainability, and infrastructure.     

Retrieving and classifying instances of source code plagiarism

Automatic detection of source code plagiarism is an important research field for both the commercial software industry and within the research community. Existing methods of plagiarism detection primarily involve exhaustive pairwise document comparison, which does not scale well for large software collections. To achieve scalability, we approach the problem from an information retrieval (IR) perspective. We retrieve a ranked list of candidate documents in response to a pseudo-query representation constructed from each source code document in the collection. The challenge in source code document retrieval is that the standard bag-of-words (BoW) representation model for such documents is likely to result in many false positives being retrieved, because of the use of identical programming language specific constructs and keywords. To address this problem, we make use of an abstract syntax tree (AST) representation of the source code documents. While the IR approach is efficient, it is essentially unsupervised in nature. To further improve its effectiveness, we apply a supervised classifier (pre-trained with features extracted from sample plagiarized source code pairs) on the top ranked retrieved documents. We report experiments on the SOCO-2014 dataset comprising 12K Java source files with almost 1M lines of code. Our experiments confirm that the AST based approach produces significantly better retrieval effectiveness than a standard BoW representation, i.e., the AST based approach is able to identify a higher number of plagiarized source code documents at top ranks in response to a query source code document. The supervised classifier, trained on features extracted from sample plagiarized source code pairs, is shown to effectively filter and thus further improve the ranked list of retrieved candidate plagiarized documents.     

On the training of highly qualified scientific staff in the field of information security

This article considers the dynamics and specifics of training highly qualified scientific staff (philosophy doctors and doctors of sciences) in the field of information security and data protection in a 10-year period of 2004–2013 in basic research specialties as classified by the Higher Attestation Commission (VAC) of the Ministry of Education and Science of the Russian Federation.     

Symbolic Management of the Degree of Information Security by Integer Splitting

This paper demonstrates the application of module arithmetic for controlling the level of information security by a new technique referred as integer splitting. The basic definitions and concepts of the method are provided. The mathematical function of arising transformation is described in detail; its properties were studied and the basic theorems were proven that justify the use of splitting in practical applications. An active system was designed and characteristic cases of its operation are considered.     

How do Tertiary Dropouts Fare in the Labour Market? A Comparison between EU Countries

Dropping out of university is regularly discussed as a negative indicator. However, research on actual career trajectories of dropouts is virtually non‐existent. This study estimates the association between tertiary dropouts and career chances in 15 European countries. Using data from the 2011 Programme for the International Assessment of Adult Competencies (PIAAC), estimates are derived from the application of propensity score matching taking a variety of individual background characteristics including cognitive skills into account. Results indicate that individuals are likely to fare better in the labour market if they enrol in university and drop out than if they do not enrol at all. Policy makers need to revise the notion that dropping out is purely negative.