This paper tried to discuss the phenomena for designing and developing a central metadata harvesting repository from selected Indian Institutional Digital Repositories. The metadata Standard format used is the Dublin Core Metadata. For metadata harvesting from the IDRs we used the Open Archives Initiative Protocol for Metadata Harvesting standard version 2.0. The study primarily tried to focus on building a central indexed repository. The repository is configured using Dspace version 4.1 and harvesting is done using its user interface. The number of digital repositories is increasing enormously around the world. With reference to DOAR in India there are presently 68 digital repositories. User's want relevant information according to their query with minimum interval of time. Henceforth they compled to search the individual repositories for getting his or her desire documents. This study tries to solve the mentioned problem of "searching individual repositories" by building a central indexed repository and providing a single search dialog box. In order to allow users to search efficiently from various institutional digital repositories we have configure a central indexed repository which will harvest metadata as well as Bitstream only if ORE support is configured in the data provider server. Metadata harvesting is the process of aggregating metadata from various data providers. Then DSpace service uses these aggregated metadata and apache SOLR indexes them and finally provides a resource discovery solution to the library patrons.
This paper has empirically established a relationship between the number of citations received by the articles (both topten cited and others) and number of articles retrieved from Web of Science database in some areas of astrophysics. The study is based on the data retrieved from Web of Science (WoS) database for the period 1990 to 2014 in some areas of astrophysics. The search terms used in WoS were selected from Thesaurus of astronomy. In all, eighteen search terms were selected from some domains of astrophysics using systematic sampling method. Four fundamental variables associated with each search term are considered for this study. These variables are: Number of retrieved documents; total citations received by all retrieved documents (including self citation); total citations received by top 10 cited documents (including self citation) and age of the retrieved documents. On the basis of these four fundamental variables, five new variables are defined as follows, i.e. Average number of citations received by all retrieved articles; average number of citations received by top ten cited articles; Citation Gain; Citation Gain Index and Citation Gain Index per unit Age or Temporary Citation Gain Index. It has been observed that citation gain is directly proportional to number of retrievals. The analysis empirically established the skewed nature of citation distribution, i.e. accumulation of more citations around highly cited articles. The Temporary Citation Gain Index showed rectangular hyperbolic pattern with Publication age.
Преданный историк науки Дерек Дж. де Солла Прайс в 1962 г. читал курс лекций в Брукхейвенской национальной лаборатории, посвященный обсуждению науки и ее взаимодействию с обществом. Конспект этих лекций был опубликован в 1963 г. как книга под названием «Малая наука, большая наука». В ней Прайс эмпирически установил, что начальная экспоненциальная схема роста литературы достигает потолка (предела высоты) через определенный промежуток времени, который приводит к логистической схеме роста. В данной статье анализируется эмпирическая теория Прайса на основе 198 статей, представляющих рост литературы по различным предметным областям и опубликованных с 1913 по 2018 г. В целом найдены 214 моделей роста в 198 статьях, анализирующих рост литературы по более 50 предметным областям. Обнаружено, что схемы роста, найденные в почти 50% статей, подтверждают эмпирическую теорию Прайса, т.е. экспоненциальную и логистическую схему роста, тогда как оставшиеся 50% статей следуют другим схемам роста - степенной модели, линейной модели и т.д. Все схемы роста, представленные 198 статьями, были широко категоризированы в 5 групп на основе данных статистики, т.е. экспоненциальная + логистическая, рост без определенной схемы, линейная, нелинейная и снижающаяся модели. Сформулированная здесь нулевая гипотеза утверждает, что 214 схем роста, отмечаемые различными предметными областями, описанными в 198 статьях, будут придерживаться любой из пяти моделей, подпадающей под действие закона Брэдфорда о библиографическом рассеянии. Нулевая гипотеза проверяется хи-квадрат тестом. Делается вывод, что распределение различных моделей роста литературы подчиняется закону Брэдфорда, в котором ядро или зона вокруг такого ядра отведена логистической и экспоненциальной модели, т.е. эмпирическая модель Прайса доминирует в ядерной зоне закона Брэдфорда.
Proteomics is the large scale of study of proteins with their function and structure. It is an approach for studying changes in metabolism in response to different stress conditions. It indicates the entire set of proteins that is, or can be, expressed by a genome, cell, tissue, or organism at a certain time. In India, the term ‘Proteomics’ was first used in an article on genomics in 1999. This paper presents the growth dynamics study of Indian and global proteomics research output with a comparative analysis. The growth pattern in India during 1999 to 2007 was exponential in nature followed by saturating power model, while the same for global research showed exponential pattern, followed by the saturating logarithmic curve. The speed of Indian growth was fast compared to global growth since after 2008 as evident from the magnitudes of AIS/AGS. The growth patterns followed Price’s law with an initial exponential trend followed by saturation thereafter. The magnitudes of the Activity Index over the years shows that Indian proteomics research is still far below the world average level, though the lowest AI in the year 2001 (0.002) escalated 19.5 times in 2015 (0.039). The Attractivity Index (AAI) values are found less than one indicating lower than world average impact values of Indian proteomics research, though it is continuously growing.
This paper presents scientometric analysis of superconductivity research output in India from 1981 to 2014 and compares it with Global output as reported in Web of Science. The study shows that superconductivity research in India had a steep growth between 1981 and 1988, particularly an abrupt hike in 1987 is noticeable (both Indian and Global) followed by a more or less steady pattern thereafter up to 2014. The Indian growth pattern however differs from Global pattern. A sudden climb was noticed in 1987, which touched the crest in 1991. It started to descend thereafter steadily and troughed in 2003 followed by another steady rise again up to 2014. Indian trend thus shows a dip between 1992 and 2014 unlike Global pattern which was nearly steady over the span. The author productivity pattern only approximately corresponds to Lotka’s law. The number of core journals in the subject area is comparatively less as obtainable by employing Bradford’s law of scattering.
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