The materials community in both science and industry use crystallographic data models on a daily basis to visualize, explain and predict the behavior of chemicals and materials. Access to reliable information on the structure of crystalline materials helps researchers concentrate experimental work in directions that optimize the discovery process. The Inorganic Crystal Structure Database (ICSD) is a comprehensive collection of more than 60 000 crystal structure entries for inorganic materials and is produced cooperatively by Fachinformationszentrum Karlsruhe (FIZ), Germany, and the US National Institute of Standards and Technology (NIST). The ICSD is disseminated in computerized formats with scienti®c software tools to exploit the content of the database. Features of a new Windows-based graphical user interface for the ICSD are outlined, together with directions for future development in support of materials research and design.

This paper presents a bibliometric analysis of the literature published in the field of mathematics from 1868 to date. The data originate from the Zentralblatt MATH database. The increase rate of publications per year reflects the growth of the mathematics community and both can well be represented by exponential or linear functions, the latter especially after the Second World War. The distribution of publications follows Bradford 0 s law but in contrast to many other disciplines there is no strong domination of a small number of journals. The productivity of authors follows two inverse power laws of the Lotka form with different parameters, one in the range of low productivity and the other in the range of high productivity. The average productivity has changed only slightly since the year 1870. As far as multiple authorship is concerned the distribution of the number of authors per publication can be described quite well by a Gamma Distribution. The average number of authors per publication has been increasing steadily; while it was close to 1 up to the first quarter of the last century it has now reached a value of 2 in the last few years. This means that the percentage of single-authored papers has fallen from over 95% in the years before 1930 to about 30% today.

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Cybersecurity solutions are traditionally static and signature-based. The traditional solutions along with the use of analytic models, machine learning and big data could be improved by automatically trigger mitigation or provide relevant awareness to control or limit consequences of threats. This kind of intelligent solutions is covered in the context of Data Science for Cybersecurity. Data Science provides a significant role in cybersecurity by utilising the power of data (and big data), high-performance computing and data mining (and machine learning) to protect users against cybercrimes. For this purpose, a successful data science project requires an effective methodology to cover all issues and provide adequate resources. In this paper, we are introducing popular data science methodologies and will compare them in accordance with cybersecurity challenges. A comparison discussion has also delivered to explain methodologies' strengths and weaknesses in case of cybersecurity projects.

This is an application of the mathematical and statistical techniques of bibliometrics to the field of crystallography. This study is, however, restricted to inorganic compounds. The data were taken from the Inorganic Crystal Structure Database, which is a well defined and evaluated body of literature and data published from 1913 to date. The data were loaded in a relational database system, which allows a widespread analysis. The following results were obtained: The cumulative growth rate of the number of experimentally determined crystal structures is best described by a third-degree polynomial function. Except for the upper end of the curve, Bradford's plot can be described well by the analytical Leimkuhler function. The publication process is dominated by a small number of periodicals. The probability of the author productivity in terms of publications follows an inverse power law of the Lotka form and in terms of database entries an inverse power law in the Mandelbrot form. In both cases the exponent is about 1.7. For the lower tail of the data an exponential correction factor has to be applied. Multiple authorship has increased from 1.4 authors per publication to about four within the past eight decades. The author distribution itself is represented by a lognormal distribution.