Author: Christine Malinowski

New NIH Policy for Data Management and Sharing

New NIH Policy for Data Management and Sharing

The National Institutes of Health (NIH) is implementing a new policy to further their efforts to improve the reproducibility and reliability...

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Data bites: Summer workshops

Join the MIT Libraries Data Management Services for these 30-minute, online workshops or “Data bites” on essential data management topics. Attend...

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FAIR data, not necessarily open

Applied data science, machine learning, and artificial intelligence research often require computational use of data. FAIR data is machine findable, accessible,...

Data
Globus now freely available for COVID-19 researchers

Globus now freely available for COVID-19 researchers

Are you working on COVID-19 and have large data you need to move about? Globus is here for you! Globus allows...

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Is your data FAIR or FOUL?

Is your data FAIR or FOUL?

Have you ever tried working with data that is Frustrating, Obfuscated, Unmanaged, and maybe even Lost? FOUL data can negatively impact...

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Make your research more reproducible

Make your research more reproducible

Reproducibility is a hot topic. A 2018 Nature special issue on challenges in irreproducible research noted that “there is growing alarm about...

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‘Dear Colleague,’ the NSF supports open science! How can you?

‘Dear Colleague,’ the NSF supports open science! How can you?

The recent ‘Dear Colleague’ letter from the National Science Foundation (NSF) highlights the importance the NSF places on information produced throughout the...

Data
Open Science Framework at MIT

Open Science Framework at MIT

MIT Libraries is excited to announce that we are now a partner institution with Open Science Framework (OSF). MIT affiliates can...

Data
Data: Cite it right!

Data: Cite it right!

It’s not enough to share your research data. It’s important to make sure that other people can cite it! Providing a...

Data