Big Data and Academic Libraries

B Radhika Rani Asst. Professor, Head Dept. of Library & Inf. Sci Kakatiya University [email protected]

Prof. S Sudarshan Rao UGC Emeritus Fellow Dept. of Lib. & Inf. Sci. Osmania University [email protected]

ABSRACT

In Knowledge Based Society, both enterprise application data and machine generated data, known as Big Data, continue to grow exponentially, challenging industry experts and researchers to develop new innovative techniques to find information and solutions to the problems of the organizations. This has lead to new advances in data storage and analysis and the concept of “big data” – massive data sets that can yield surprising insights when analyzed. This Paper briefly describes what and why is big data important to Academic Libraries. It explores the possibilities and its implications on librarians and enumerates some of the Big Data projects.

Introduction In the Knowledge society, the competitive advantage is gained through understanding the information and predicting the evolution of facts based on data.

Introduction, contd… The crux of the “Big Data paradigm’ is actually not the increasingly large amount of data itself, but its analysis for intelligent decision-making. The process can be seen as the natural consequence in the evolution from the “Information Age” and “Information Societies.”

Big Data Wrold

What is Big Data? Anderson (2008) - “the era of big data, where more isn’t

just more. More is different.” Ward and Barker (2013) - Big data is a phrase describing

the storage and analysis of large and or complex data sets using a series of techniques. TechAmerica Foundation’s Federal Big data Commission

defines “Big data is a term that describes large volumes of high velocity, complex and variable data that require advanced techniques and technologies to enable the capture, storage, distribution, management and analysis of the information”.

Big Data Characteristic features of Big Data 3Vs(Berman, 2014) Volume Variety Velocity Few more Vs suggested by People working on Big Data projects are: Vision Verification Validation

Existence of Big Data / Sources of Big Data

An organization that collected a lot of data, can

seek to organize the data so that materials can be retrieved, as needed. The Big Data effort is intended to streamline the regular activities of the organization. The collected data can be used, in its totality, to improve quality of service, increasing staff efficiency and reducing operational costs. An organization that collected a lot of data, may enable them to develop new products based on the preferences of their loyal customers to reach new markets.

Existence of Big Data, Contd.. An organization is part of a group of entities that have

large data resources. All of whom understand that it would be to their mutual advantage to federate their data resources. An organization with skills and vision develops a project where in large amounts of data are collected and organized to the benefit of themselves and their userclients. An entity / organization has no data and has no particular expertise in Big Data technologies, but it has money and vision. The entity seeks to fund and coordinate a group of data creators and data holders who will build a Big Data resource that can be used by others.

Who will benefit from Big Data Government agencies, Corporate organizations, research institutions, etc. NSF (National Science Foundations, 2012 ), USA envisions that: Predictions of Natural Disasters Responses to disaster recovery. Complete health/disease/genome. Accurate high-resolution models to support forecasting. Consumers have the information they need Civil engineers Students and researchers

Characteristics of Big Data

Big Data resources are permanent, and the

data within the resource is immutable. Big Data resources are permanent, any analysis can be critically examined with the same set of data, or reanalyzed anytime in the future. All the data in the informational universe is complex built from simple data. Just as starts can exhaust themselves explode, or even collapse under their own weight to become black holes.

Big Data and Libraries

Big data technologies make it easier to work

with large datasets, link different datasets, detect patterns in real time, predict outcomes, undertake dynamic risk scoring and test hypotheses. Libraries and librarians are uniquely suited to working with big data. Libraries have a long tradition of being information handlers and technology adopters, and big data should be no exception.

How librarians can get involved with Big Data Collection Development and Preservation of Data Sets. Usage Data – Use Statistics Research Data Management Data Literacy into their Instructional Programs

But all these requires understanding of what data we have, what data we need to have created, what data we need to negotiate for, and then gaining access and doing the analysis. Then, it requires us presenting the results of our analysis to our management and users, so as to make decisions. It helps us “steer” our organizations further.

Big Data Projects and Resources Amazon Web Services Public Data Sets. ClueWeb09 Data.gov/Education Open Data Census Project Gutenberg National Government Statistical Web Sites National Space Science Data Center

Conclusion We live in an era of Big Data, the data generated in

academic institutions is vast and complex. The idea of extracting new and exciting insights from previously unmanageable data is a bit like finding the proverbial ‘needle in a haystack’. Just as they have with previous technological advances, librarians should become familiar with the possibilities and problems inherent to big data and use that knowledge to help their patrons choose the right tools. The academic librarians have a clear role in data analytics to help the institutions and the stakeholders in bettering the services and quality of education.