Building Library Services for Data Driven Scholarship

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Digital Scholarship Centers: Building Library Services for Data-Driven Scholarship

 

Date/Time: November 28 - 30, 2016, 9:00 a.m. - 5:15 p.m.

Venue: Level 3, Main Library, the University of Hong Kong, Hong Kong

Register: To register, please email Trevor Lui at trev@hku.hk (reg. fee: HKD$3800).  Or CLICK here / http://goo.gl/3MX0XO

 

Description:

As research practices across academic disciplines increasingly draw upon digital and data-driven methodologies, libraries have likewise shifted their service models to include spaces for supporting digital scholarship that we call the “digital scholarship centers”. In these often unorthodox and technology-focused spaces, hardware, software, and in-person expertise meet to empower researchers with the tools, skills, and information resources to incorporate computational methods into their work. This three-day workshop introduces the digital scholarship center model for library support of academic research. Combining lectures and hands-on labs, this workshop will equip attendees with practical strategies for supporting or partnering in digital scholarship both in and out of digital scholarship centers at their own institutions.

 

Workshop Leaders:

Prof. J. Stephen Downie
School of Information Sciences, University of Illinois

Ms. Harriett Green
University Library, University of Illinois

Ms. Eleanor Dickson
University Library, University of Illinois

Dr. Nic Weber
Information School, University of Washington

Dr. Xiao Hu
Faculty of Education, University of Hong Kong

 

Guest Speakers:

Ms. Karen Hogenboom
University Library, University of Illinois

Prof. Allen Renear
School of Information Sciences, University of Illinois

 

Organizing Committee Members:

Prof. Stephen Downie, University of Illinois

Dr. Xiao Hu, I&TS, Faculty of Education, HKU

Dr. Sam CHU, Head, I&TS Division, HKU

Mr. Peter Sidorko, University Librarian, HKU

 

Program:

Day 1: Introduction

Morning Plenary lectures (9:00 a.m.-12:00p.m.)

  • What are digital scholarship centers? (Eleanor)
    • An overview of the shifting landscape of digital scholarship in Social Science, Humanities, and Science and Engineering, which are emerging research needs that libraries must address.
  • Digital Humanities: The landscape (Harriett)
    • A summary history and comments on the future of digital humanities research practices, techniques, & outcomes.
  • Text Mining concepts and methods: HTRC and non-consumptive research (Stephen)
    • This presentation will introduce attendees to concepts and strategies in text analysis, and use the HathiTrust Research Center and its approach to providing computational access to 14+ million digitized texts as an example of what is possible.

Afternoon Labs - participant groups will switch after 90 minutes (2:00 p.m.-5:15 p.m.)

  • Lab A:  Text Analysis with the HTRC Extracted Features (Stephen and Xiao)
    • A beginner’s look at text analysis using an openly available dataset, the HTRC Extracted Features.
  • Lab B: Spatial Humanities: GIS and Mapping (Harriett)
    • A hands-on introduction to web-based mapping tools, including StoryMap and/or ArcGIS online.

Daily Wrap-Up (15 minutes)

 

Day 2: Working with Data

Morning Plenary lectures (9:00 a.m.-12:00p.m.)

  • Data Discovery and use (Guest lecture: Karen Hogenboom)
    • Where do researchers find data, and how can they best incorporate data analysis in their scholarship? This session will explore the library’s role in facilitating access to and research using datasets.
  • Quick and Painless Introduction to Machine Learning (Stephen and Xiao)
    • Overview of the concepts and methods important to machine learning. Assumes no prior knowledge. Interesting real-world examples used as illustrations.

Afternoon Labs - participant groups will switch after 90 minutes (2:00 p.m.-5:15 p.m.)

  • Lab A: Data Wrangling with OpenRefine (Nic)
    • How to normalize, clean-up, and manage tabular data using the open-source program OpenRefine.
  • Lab B: Weka Machine Learning Tools: A Friendly Interactive Exploration (Xiao and Stephen)
    • Interactive exploration of the Weka open-source machine learning software. Ties directly in with the “Quick and Painless Introduction to Machine Learning Lecture.”

Daily Wrap-Up (15 minutes)

 

Day 3: Publishing and Visualizing Data

Morning Plenary lectures (9:00 a.m.-12:00p.m.)

  • Data Visualization: an overview (Harriett)
    • An overview of the methods and tools/resources used in data visualization, including approaches such as network analysis and topic modeling; and tools such as Gephi, Google Fusion Tables, and Tableau.
  • Data Publishing and Open Data (Nic)
    • Overview of methods, trends, and practices in publishing data on the web. This will include licensing, and policy directives for open data.

Afternoon Labs - participant groups will switch after 90 minutes (2:00 p.m.-5:15 p.m.)

  • LAB A: Voyant + HTRC Bookworm (Eleanor and Harriett)
    • A look at easy-to-use, web-based tools for visualizing textual data.
  • LAB B: Tableau (Nic)
    • A hands-on demonstration and tutorial on visualizing open data with the Tableau Public interface.

Plenary Closing Remarks (20-30 minutes)