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  • Print publication year: 2016
  • Online publication date: June 2018

4 - Training researchers to manage data for better results, re-use and long-term access

from PART 2 - DATA SERVICES AND DATA LITERACY

Summary

Introduction

The existing academic research workforce is ill-equipped to manage research data using the increasingly complex computing technologies available to them. Despite the availability of ever more powerful desktops and mobile technologies, and of high-performance cloud computing and storage, universities are failing to provide graduate students with adequate data management skills for research in academia or industry. The challenge for mid- and late-career faculty is even greater, because of the difficulty in changing established research practices for ongoing studies. This skills gap places at risk billions of research dollars, the integrity of vast quantities of research data, and the quality of life for millions of people.

Providing this workforce with the skills they need to collect, manage and share their data effectively is a challenge many academic libraries are taking on. Though libraries may provide some technological solutions, our most valuable contributions lie in expertise and trust. We have the resources to fill this skills gap by using our information management expertise, teaching ability, ability to facilitate conversation across departmental and disciplinary boundaries, and a uniquely holistic understanding of the scholarly record. At Indiana University Purdue University Indianapolis (IUPUI), education and advocacy is the foundation of our data services. This choice is shaped by the recognition that many graduate programmes are not sufficiently preparing students to manage digital research data. Before we can expect academic researchers to share, preserve and curate their data, they must understand the value and importance of data management.

This chapter will describe IUPUI's initial foray into data information literacy instruction, and the lessons learned, and look forward to the future of such programmes. We drew upon best practices in instructional design and information literacy, the scientific lab experience (Coates, 2014), and interdisciplinary data management expertise to develop the programme. The focus is on practical techniques for responsible data management and relies heavily on the data management plan (DMP) as a tool for teaching and research. Our initial trainings have reached a diverse audience, many of whom were not identified as stakeholders when developing the curriculum. This chapter will describe the development of our instructional programme, assessment results, and modifications to portray an emerging data literacy programme at a high-research-activity university.