Open Data Week Will Feature ContentMine, Data Visualization, Panel Discussions

The University Libraries will be hosting its second Open Data Week on April 10-13 with opportunities to learn more about sharing, visualizing, finding, mining, and reusing data for research. In addition to panel discussions on open research data as well as on text and data mining, there will be two sessions on data visualization. From Tuesday through Thursday, join one or more sessions featuring guests Thomas Arrow and Stefan Kasberger from ContentMine to learn about open source tools in development for mining scholarly and research literature. ContentMine software “allows users to gather papers from many different sources, standardize the material, and process them to look up and/or search for key terms, phrases, patterns, and more.” Be sure to register for limited capacity events (Lunch on Wednesday 4/12, and the in-depth workshop on Thursday 4/13); links and full schedule below. For more information, see our Open Data Week guide, and use our hashtag, #VTODW.

Open Data Week featuring ContentMine

Monday April 10
Open Research/Open Data Forum: Transparency, Sharing, and Reproducibility in Scholarship
6:30-8:00pm, in Torgersen Hall 1100 (NLI credit available)

Join our panelists for a discussion on challenges and opportunities related to sharing and using open data in research, including meeting funder and journal guidelines:

  • Daniel Chen (Ph.D. candidate in Genetics, Bioinformatics, and Computational Biology)
  • Karen DePauw (Vice President and Dean for Graduate Education)
  • Sally Morton (Dean, College of Science)
  • Jon Petters (Data Management Consultant, University Libraries)
  • David Radcliffe (English)
  • Laura Sands (Center for Gerontology)

Tuesday April 11
Introduction to Content Mine – Tools for Mining Scholarly Literature
9:30-10:45am, Newman Library Multipurpose Room (NLI credit available)

Join ContentMine instructors for an overview of text and data mining, and an introduction to ContentMine tools for text and data mining of scholarly and research literature.

Tuesday April 11
Data Visualization with Tableau
10:30 am -12:00 pm, Torgersen 1100 (NLI registration)

With the Tableau data visualization software, you or your students can easily turn research data into detailed, interactive visualizations that tell the story that numbers alone struggle to express. The software can link directly to your data sources so you always have the most up-to-date data on hand without exporting manually, and easily generate hundreds of types of visualizations that include interactive elements.

Wednesday April 12
Introduction to Content Mine: Tools for Mining Scholarly Literature
9:00-9:55am, Newman Library Multipurpose Room (NLI credit available)

Join ContentMine instructors for an overview of text and data mining, and an introduction to ContentMine tools for text and data mining of scholarly and research literature.

Wednesday April 12
Making Visible the Invisible: Data Visualization and Poster Design
9:30-11:00am, Newman 207A (NLI registration)

Visually representing data helps users and readers engage with the content, understand key findings, and retain information. Exploring, creating, and presenting these visual representations is becoming critical for teaching, academic research, and professional engagement. In this session we will explore the basics of data visualization and poster design, and look at a few tools to create different kinds of visualizations. We will also discuss the academic and professional value in visualizing data.

Wednesday April 12
ContentMine and Specialized Tools for Life Sciences Research
11:15-12:05pm, Newman Library Multipurpose Room (NLI credit available)

Join students in a computational biochemistry informatics class session for an introduction to ContentMine open source tools for text and data mining to explore research literature sources, with a focus on tools related to mining and exploring content for Life Sciences research (phylogeny and and visualization).

Wednesday April 12
Lunch with ContentMine guest speakers and program participants
12:30-1:30, Location TBA (Registration required; Limit: 50 participants)

Wednesday April 12
Text and Data Mining Forum
2:30-3:45pm, Newman MultiPurpose Room (NLI credit available)

Join our panelists for a discussion about opportunities and challenges related to text and data mining, with a focus on research purposes and information access. Audience questions are encouraged.

  • Tom Arrow (ContentMine)
  • Tom Ewing (College of Liberal Arts and Human Sciences, Virginia Tech)
  • Weiguo (Patrick) Fan (Pamplin College of Business, Virginia Tech)
  • Ed Fox (Computer Science, Virginia Tech)
  • Leanna House (Statistics, Virginia Tech)
  • Brent Huang (Computer Science, Virginia Tech)

ContentMine logo

Wednesday April 12
Introduction to Content Mine: Tools for Mining Scholarly Literature
4:00-5:15pm, Newman ScaleUp Classroom (101S) (NLI credit available)

Join ContentMine instructors for an overview of text and data mining, and an introduction to ContentMine tools for text and data mining of scholarly and research literature.

Thursday April 13
ContentMine Tools to Explore Scholarly Literature: A Full Day, Hands-On Workshop
9:00am – 4:00pm, Newman Library 207A (Registration required; also, NLI credit available; Coffee and Lunch provided)

During this workshop participants will: (1) ensure the software is functioning on their laptop computer, (2) participate in individual and group hands-on exercises to become more familiar with ContentMine tools, and (3) have the opportunity to experiment with using ContentMine tools with ContentMine instructors’ support – to mine scholarly literature and explore results specific to their own research project goals. Prior to the workshop, attendees will receive instructions to download software and make any other preparations to get the most of of the workshop.

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About Philip Young

Philip Young is Scholarly Communication Librarian at Virginia Tech where he supports outreach about open access, copyright/open licensing, open data, ORCID, and metrics/altmetrics.
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