Strategies for Digitizing Handwritten Data

In the vast world of science, capturing data is like collecting treasure. But what if that treasure is hidden in handwritten notes? That’s the challenge faced by scientists like Christie Bahlai, who inherited boxes of handwritten data sheets from a ladybird survey project. To unlock this treasure trove, researchers need to digitize the data, turning scribbles into numbers and words that computers can understand. Here are five tips for digitizing handwritten data without losing the treasure along the way.

Plan for Digitization Integrity

Before diving into data entry, create a plan to ensure accuracy every step of the way. Standardized protocols and workflows can prevent errors and reduce costs. Christie Bahlai’s lab assigns meticulous volunteers to transfer data to digital formats, with a careful review process to catch any mistakes.

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Back Up Your Paper

Don’t leave your treasure vulnerable to unexpected disasters! Make copies or scans of your handwritten notes as soon as you return from the field. Joel Correia suggests safeguarding your data against rain, fire, or other unforeseen events by digitizing it early.

Use Several Pairs of Eyes

Reducing errors is a team effort. Have multiple people input the same data, then compare and correct any inconsistencies. Miguel Acevedo suggests experimenting with different numbers of double-checkers to find the sweet spot for error reduction.

Home In on Outliers

Keep an eye out for data that doesn’t quite fit the pattern. Miguel Acevedo once discovered outliers in lizard measurements and traced the issue back to recording units. Linden Ashcroft warns against dismissing outliers too quickly, as they might reveal valuable insights.

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Try OCR (and other software)

OCR (Optical Character Recognition) software can be a helpful tool for converting scanned images into text. Stuart Middleton advises researchers to choose OCR models carefully and be prepared for challenges like messy handwriting. For smaller projects, manual data entry might still be more efficient, but the future of OCR looks promising.