Constellate, the new text and data analytics service from JSTOR and Portico is a platform for learning and performing text analysis, building datasets, and sharing analytics course materials. The demand for analytics skills across all domains is growing exponentially. Text and data analysis is one of those skills, yet it
Can I use R?
Absolutely. Our Binder environment supports using R in Jupyter notebooks and RStudio. We have chosen to start developing Python Jupyter notebooks first, but we would love to see community-developed, open educational resources created in R. If you'd like to help us get started, see How can I create/adapt a
Collections to Analyze
JSTORJSTOR is a digital library for the intellectually curious. We help everyone discover, share, and connect valuable ideas. Content Type: journal articles, book chapters, research reports Size: over 14 million documents Document Publication Date Distribution: Distribution of JSTOR Content in Constellate by Year from 1700-CurrentMetadata Quality: High Text Accuracy: High
Participate and Beta Evaluation Period
The demand for analytics skills across all domains is growing exponentially. Text and data analysis is one of those skills, yet it remains difficult to learn. Researchers and students are often teased by black box, point-and-click tools that produce a few quick visualizations that whet the appetite; however, the next
What is Constellate?
Constellate, the new text and data analytics service from JSTOR and Portico is a platform for learning and performing text analysis, building datasets, and sharing analytics course materials. The platform provides value to users in three core areas -- they can teach and learn text analytics, build datasets from across
Technology Driving Constellate
Constellate uses the following software: Ghost -- a publishing platform that hosts our “about” and help pagesAWS -- our platform is built in the cloud and is currently running in Amazon Web Services.BinderHub -- the web application behind our Analytics LabJupyter -- our code tutorials are all written in
Institutions in the Beta EvaluationWe are grateful to all the institutions participating in our beta program. Arizona State UniversityBaylor UniversityBoston CollegeCalPolyCalPolyPomonaCentral Washington UniversityClemson UniversityColby CollegeDartmouth CollegeFramingham State UniversityGeorge Mason UniversityJames Madison UniversityLouisiana State UniversityLoyola University ChicagoManhattan CollegeMarquette UniversityMurray State UniversityNC State UniversityNortheastern UniversityNorthwestern UniversityNorth Carolina School of Science and MathematicsThe
Differences from JSTOR's Data for Research (DfR)
The new platform offers a modern revitalization of the existing JSTOR DfR service. The key improvements include: Considerably more content, including an additional 15 million articles from over 3,000 journals and 42 publishers.A number of built-in visualizations, including an n-gram or term frequency viewer.An Analytics Lab that
Constellate provides a number of dataset options: Datasets in CSV of just bibliographic metadata. We allow individuals to download datasets of 25,000 items (or 50,000 if your institution participates in our beta program) within the Constellate dataset builder. We cap creation at 10 of these datasets a day