Data Mashups as Collection Management Tools

Paynter, Robin

doi:10.1080/01462679.2011.531682

Cited by 3 publications

(1 citation statement)

References 4 publications

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“…Machine learning algorithms and computing intelligence method is a key solution meant to deal with massive data from IoT perspective. Major advancements which are linked to the IoT are evaluated in multiple pieces of research done [18].…”

Section: Internet Of Things (Iot) For Big Datamentioning

confidence: 99%

An Analytical Research on the Big Data Tools and Techniques

Akiyama

Aravindhan²

2020

International Journal of Advanced Information and Communication Technology

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A massive segment of information terabytes is produced daily due to the advent of technological systems and modern systems such as cloud computing and the Internet of Things (IoT). The evaluation of the big data analytics impacts significant effort of the many dimensions considered in the process of extracting data that is essential for the process of making proper decisions in an organization. In that regard, big data analytics is the immediate area of concern for research and development experts. The primary purpose of this paper is to provide an analysis of the big data analytics, including the issues and tools linked to the process of extensive information analysis. Moreover, this academic paper presents an avenue that stimulates the exploration of big data at an incredible measure. As such, this research provides a new platform of analytics to formulate a remedy to the problems and the gaps available in research.

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Section: Internet Of Things (Iot) For Big Datamentioning

confidence: 99%

An Analytical Research on the Big Data Tools and Techniques

Akiyama

Aravindhan²

2020

International Journal of Advanced Information and Communication Technology

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Significance of big data analytics and the internet of things (IoT) aspects in industrial development, governance and sustainability

Andersen

Ashbrook

Karlborg

2020

International Journal of Intelligent Networks

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Citations and Citation Metrics in a Serial Assessment Using Master's Theses

Timms

2018

Collection Management

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We analyzed serial citations in 72 marine biology master's theses as well as the ranking data of aquatic science serials from six global serial citation metrics, to assess serial use by marine biology graduate students from two perspectives. From 1,035 unique serials, a core of 123 titles was identified and evaluated for access. Citation ages averaged 13.5 years, with 27% of serial citations dated prior to 1996. Students cited serials from disciplines beyond marine biology, demonstrating broad title dispersion compared to several other studies. Recommendations are offered for future investigation to develop a stronger understanding of graduate students' use of the library's serial collection.

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Data Mashups as Collection Management Tools

Abstract: Mashups in end-user library applications are burgeoning, while staff-side applications are just beginning to come into their own. Collection management mashups are discussed here, with special emphasis on the development of the new mashup version of the Core Psychology Journals list.

Cited by 3 publications

References 4 publications

An Analytical Research on the Big Data Tools and Techniques

An Analytical Research on the Big Data Tools and Techniques

Significance of big data analytics and the internet of things (IoT) aspects in industrial development, governance and sustainability

Citations and Citation Metrics in a Serial Assessment Using Master's Theses

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