Bridging the Data Talent Gap: Positioning the iSchool as an Agent for Change

Abstract

This paper examines the role, functions and value of the “iSchool” as an agent of change in the data informatics and data curation arena. A brief background to the iSchool movement is given followed by a brief review of the data decade, which highlights key data trends from the iSchool perspective: open data and open science, big data and disciplinary data diversity. The growing emphasis on the shortage of data talent is noted and a family of data science roles identified. The paper moves on to describe three primary functions of iSchools: education, research intelligence and professional practice, which form the foundations of a new Capability Ramp Model. The model is illustrated by mini-case studies from the School of Information Sciences, University of Pittsburgh: the immersive (laboratory-based) component of two new Research Data Management and Research Data Infrastructures graduate courses, a new practice partnership with the University Library System centred on RDM, and the mapping of disciplinary data practice using the Community Capability Model Profile Tool. The paper closes with a look to the future and, based on the assertion that data is mission-critical for iSchools, some steps are proposed for the next data decade: moving data education programs into the mainstream core curriculum, adopting a translational data science perspective and strengthening engagement with the Research Data Alliance.

Computing Academics into New Age Programs and Fields: Big Data Analytics & Data Sciences in Indian Academics—An Academic Investigation of Private Universities

“…Moreover, these are offered with few data analysis and tools as well such as statistics, data mining, and predictive. Probability models, pattern recognition are also important in Big Data Systems and it is also involved also with the areas of learning, visualization, machine learning, signal processing, statistical learning, database and mining, predictive analytics and databases, and so on [5], [7], [9]. The large amount of data affairs is called Big Data and organizations and institutions at large currently adopted Data Management benefits in different spaces [12], [13].…”

Transparency: The Emerging Third Dimension of Open Science and Open Data

“…Transparency Agents can be characterized as defined roles or named individuals or organisations, who execute a specific action or intervention. They are exemplified by six new Data Science roles described by Lyon and Brenner (2015) A presentation of transparency terms as "transparency standards" has been developed by the Center for Open Science as a part of the Open Science Framework and as a modular approach to their TOP Guidelines for Transparency and Openness promotion in Journal Policies and Practices (Center for Open Science, 2015). These transparency standards include 1.…”

“…There are a range of new roles associated with this field which encompass data analysis, stewardship, software engineering, journalism, managing data archives and data librarianship (Lyon & Brenner, 2015). Some academic libraries are extending their existing Research Support Services to include Research Data Management as a key component with advocacy and advisory services (Cox & Pinfield, 2014).…”

“…The need to re-engineer LIS education to deliver a curriculum suited to the new data science roles has been noted (Lyon & Brenner, 2015). iSchool programs and courses require real-world relevance in order to produce workready graduates who can assume one of these new data science positions.…”

“…Many iSchools now have data curation or digital stewardship courses, but are transparency and reproducibility concepts embedded in the curriculum? The School of Information Sciences (iSchool) University of Pittsburgh MLIS Program is adopting an innovative translational data science approach ('the transition of data skills, software tools and research intelligence from the iSchool to the marketplace' defined in Lyon and Brenner, 2015), which mirrors the established terminology of translational medicine. New Masters courses in Research Data Management and Research Data Infrastructures address transparency, reproducibility and validation concepts.…”