Draw from .
Draw graphs of your own.
Data Pen is a prototype research tool for humanities data. Connecting linked data sources to filtering and graphing tools, Data Pen provides a framework for humanities researchers to access, explore, and manipulate multidimensional historical data.
Pull in data from established sources.

By connecting to authorities and archives like VIAF, the Library of Congress, Geonames, and Wikidata, Data Pen empowers researchers with the interconnected knowledge of the scholarly community and the larger linked data ecosystem.

Import data en masse from sources as a starting point, or use them as a reference to enrich datasets built one entity at a time. Either way, a node labelled “John Locke” can be identified as a person with already defined relationships to other people, places, and objects in the data set.

Screenshot of the sources level of Data Pen.
Filter and investigate your dataset.

Having access to multiple archives’ worth of data means needing a way to navigate that data. Data Pen’s filtering tools provide a variety of ways to explore the rich web of linked data available to researchers, and to focus on what’s important.

Make your dataset more manageable with visual filters like timelines and facet filters, as well as tabular filtering tools. Use those same tools to investigate large and small datasets, in both tabular and visualised forms, to develop a contextual understanding of the data that’s available.

Screenshot of the sources level of Data Pen.
Draw with data.

Data Pen leverages linked data to aid researchers, not to replace them. Use the canvas as a blank slate to think visually, accompanied by a tabular view to keep the data close at hand. Add, remove, and edit nodes as your research shifts, and construct graphs that are meaningful to you.

Create, arrange, group, and annotate nodes by hand, or utilise the underlying data to help you. Select an entity on the canvas, and pull in any people or places associated with them. Save snapshots of your canvas to return to later, or to share with colleagues. Nothing moves unless you want it to.

Screenshot of the sources level of Data Pen.
Core team

Dan Edelstein Stanford University

Nicole Coleman Stanford University Libraries

Eetu Mäkelä University of Helsinki / Aalto University

Ethan Jewett Coredatra

Alex Sherman Center for Spatial and Textual Analysis

Tim Busuttil University of Technology, Sydney

Thomas Ricciardiello University of Technology, Sydney

Consultants and participants

Ruth Ahnert Queen Mary University of London

Sebastian Ahnert University of Cambridge

Arno Bosse Oxford University

Simon Burrows University of Western Sydney

Paolo Ciuccarelli Politecnico di Milano

Marten Düring University of Luxembourg

Paula Findlen Stanford University

Mauricio Giraldo New York Public Library

Jo Guldi Brown University

Howard Hotson Oxford University

Eero Hyvönen Aalto University

Matthew Jones Columbia

Christoph Kudella University College Cork

Miranda Lewis Oxford University

Matthew Lincoln Getty Research Institute

Jacqueline Lorber Kasunic University of Technology, Sydney

Sarah Ogilvie Stanford University

Iréne Passeron CNRS Paris

Miriam Posner UCLA

Rob Sanderson J. Paul Getty Trust

Philip Schreur Stanford University Libraries

Daniel Shore Georgetown University

Sarah Sussman Stanford University Libraries

Kate Sweetapple University of Technology, Sydney

Thomas Wallnig University of Vienna

Chris Warren Carnegie Mellon University

Scott Weingart Carnegie Mellon University

Caroline Winterer Stanford University

Funding and support

The Data Pen Project became real thanks to an ACLS Digital Extension grant.

We are also very fortunate for our affiliation with CESTA, the hub of all of our activities. The researchers and staff there are crucial to the success of the project. We also rely heavily on our partnership with the Stanford University Libraries for technical expertise and sharing ideas to create research tools that make the most of the digital library.

Logos for the American Council of Learned Societies, Stanford University Center for Spatial and Textual Analysis and Stanford Libraries.