Article Type

EScience in Action

Publication Date





Data curation is the process of managing data to make it available for reuse and preservation and to allow FAIR (findable, accessible, interoperable, reusable) uses. It is an important part of the research lifecycle as researchers are often either required by funders or generally encouraged to preserve the dataset and make it discoverable and reusable. This has been especially important as the Open Access (OA) policy is being implemented in many institutions across the nation. In facilitating research data discovery and enhancing its easier reuse, an efficient data repository and its data curation play key roles. In this article, we briefly discuss the local institutional repository at Penn State University and the general data curation practices we adopt for the deposited files and datasets, then we focus on a data analytics tool that has recently been applied to extract tabular data from PDF files. This is an enhancement to the existing data curation practices as it adds additional tabular data to deposits with PDF files where tables are often embedded and not easily reused.


data curation, PDF, data extraction, tabular data, reusable, discoverable, institutional repository

Data Availability

The datasets analyzed during the current study are available at https://doi.org/10.7554/elife.44898.


We would like to thank the data curation team at the Penn State University Libraries for the discussions and support for this work, the Data Curation Network (DCN) for all the training and shared expertise in research data curation, Ally Laird, Paulina Krys, and Tara Anthony from the Research Informatics and Publishing at the Penn State University Libraries for feedback on the manuscript, and Dr. Keith C. Cheng from the Penn State College of Medicine for allowing us to use his research article to demonstrate the data extraction process with the data analytics tool.

Corresponding Author

Xuying Xin, W312 Pattee Library, Penn State University, University Park, PA, 16802, United States; xzx1@psu.edu

Rights and Permissions

© 2021 Choi & Xin. This is an open access article licensed under the terms of the Creative Commons Attribution License.

Creative Commons License

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.