2020•Education for InformationOpen access

Changes in academic libraries in the era of Open Science

Stefka Tzanova

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Abstract

In this paper we study the changes in academic library services inspired by the Open Science movement and especially the changes prompted from Open Data as a founding part of Open Science. We argue that academic libraries face the even bigger challenges for accommodating and providing support for Open Big Data composed from existing raw data sets and new massive sets generated from data driven research. Ensuring the veracity of Open Big Data is a complex problem dominated by data science. For academic libraries, that challenge triggers not only the expansion of traditional library services, but also leads to adoption of a set of new roles and responsibilities. That includes, but is not limited to development of the supporting models for Research Data Management, providing Data Management Plan assistance, expanding the qualifications of library personnel toward data science literacy, integration of the library services into research and educational process by taking part in research grants and many others. We outline several approaches taken by some academic libraries and by libraries at the City University of New York (CUNY) to meet necessities imposed by doing research and education with Open Big Data – from changes in libraries’ administrative structure, changes in personnel qualifications and duties, leading the interdisciplinary advisory groups, to active collaboration in principal projects.

About this research paper

What this paper is about

In this paper we study the changes in academic library services inspired by the Open Science movement and especially the changes prompted from Open Data as a founding part of Open Science. We argue that academic libraries face the even bigger challenges for accommodating and providing support for Open Big Data composed from existing raw data sets and new massive sets generated from data driven research. Ensuring the veracity of Open Big Data is a complex problem dominated by data science. For academic libraries, that challenge triggers not only the expansion of traditional library services, but also leads to adoption of a set of new roles and responsibilities. That includes, but is not limited to development of the supporting models for Research Data Management, providing Data Management Plan assistance, expanding the qualifications of library personnel toward data science literacy, integration of the library services into research and educational process by taking part in research grants and many others. We outline several approaches taken by some academic libraries and by libraries at the City University of New York (CUNY) to meet necessities imposed by doing research and education with Open Big Data – from changes in libraries’ administrative structure, changes in personnel qualifications and duties, leading the interdisciplinary advisory groups, to active collaboration in principal projects.

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Available abstract

In this paper we study the changes in academic library services inspired by the Open Science movement and especially the changes prompted from Open Data as a founding part of Open Science. We argue that academic libraries face the even bigger challenges for accommodating and providing support for Open Big Data composed from existing raw data sets and new massive sets generated from data driven research. Ensuring the veracity of Open Big Data is a complex problem dominated by data science. For academic libraries, that challenge triggers not only the expansion of traditional library services, but also leads to adoption of a set of new roles and responsibilities. That includes, but is not limited to development of the supporting models for Research Data Management, providing Data Management Plan assistance, expanding the qualifications of library personnel toward data science literacy, integration of the library services into research and educational process by taking part in research grants and many others. We outline several approaches taken by some academic libraries and by libraries at the City University of New York (CUNY) to meet necessities imposed by doing research and education with Open Big Data – from changes in libraries’ administrative structure, changes in personnel qualifications and duties, leading the interdisciplinary advisory groups, to active collaboration in principal projects.

Key concepts: Big data, Face (sociological concept), Plan (archaeology), Open data, Open science, Process (computing), Computer science, Data science

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