For those learning about fair use, this is a specific example of …
For those learning about fair use, this is a specific example of how fair use may be used in research for text data mining. The book also explores basic copyright and fair use more generally, as well as the specifics of text data mining. From the "about" section of the book:
"This book explores the legal literacies covered during the virtual Building Legal Literacies for Text Data Mining Institute, including copyright (both U.S. and international law), technological protection measures, privacy, and ethical considerations. It describes in detail how we developed and delivered the 4-day institute, and also provides ideas for hosting shorter literacy teaching sessions. Finally, we offer reflections and take-aways on the Institute."
This workshop aims to help students and teachers of Humanities and Social …
This workshop aims to help students and teachers of Humanities and Social Science learn the basics of text-mining using Python. It is meant as an introduction to the use of computational techniques for analysing data for Humanists and Social Scientists. It contains a "Jupyter Notebook", which is basically a website where students will be taught how to write and execute code that will help them solve research problems that Humanists and Social scientists face. Additionally, this lesson also contains a video that demonstrates how to use that website. The total expected time to use this resouce is around 2 hours.
This is an edited volume of chapters from copyright experts around the …
This is an edited volume of chapters from copyright experts around the globe explaining complex copyright issues in a clear, concise way. The majority of the chapters are licensed CC-BY.
This is an edited volume of chapters from copyright experts around the …
This is an edited volume of chapters from copyright experts around the globe explaining complex copyright issues in a clear, concise way. The majority of the chapters are licensed CC-BY.
Open data is a vital pillar of open science and a key …
Open data is a vital pillar of open science and a key enabler for reproducibility, data reuse, and novel discoveries. Enforcement of open-data policies, however, largely relies on manual efforts, which invariably lag behind the increasingly automated generation of biological data. To address this problem, we developed a general approach to automatically identify datasets overdue for public release by applying text mining to identify dataset references in published articles and parse query results from repositories to determine if the datasets remain private. We demonstrate the effectiveness of this approach on 2 popular National Center for Biotechnology Information (NCBI) repositories: Gene Expression Omnibus (GEO) and Sequence Read Archive (SRA). Our Wide-Open system identified a large number of overdue datasets, which spurred administrators to respond directly by releasing 400 datasets in one week.
No restrictions on your remixing, redistributing, or making derivative works. Give credit to the author, as required.
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Your redistributing comes with some restrictions. Do not remix or make derivative works.
Most restrictive license type. Prohibits most uses, sharing, and any changes.
Copyrighted materials, available under Fair Use and the TEACH Act for US-based educators, or other custom arrangements. Go to the resource provider to see their individual restrictions.
