OSF – An Open Science Workflow for Researchers
The Open Science Framework (OSF) is a free, open-source tool hosted by the Center for Open Science. This post shares how OSF can be used to facilitate your research project lifecycle.
The Open Science Framework (OSF) is a free, open-source tool hosted by the Center for Open Science. This post shares how OSF can be used to facilitate your research project lifecycle.
BrowZine allows you to browse much of the Library's subscribed journal content via an easy-to-use and intuitive interface.
Research data is sometimes hard to understand. With so much data being processed in a research, data visualization can provide a better way to understand the data.
ResearchRabbit is a new tool for literature exploration and mapping. As hinted by its name, this tool aims to give you a leg up down the research rabbit hole.
The Library is now trialing scite.ai, a smart citation index that displays the context of citations and classifies their intent using AI. Read the blog to learn how it works and its key features.
Last week, Web of Science rolled out a new interface. As it is one of the most heavily used e-resources, here we highlight some of the noteworthy new features.
IEEE DataPort is an online data repository developed by IEEE. This post is a preliminary review of this relatively new offering. Potential issues on access and deposit of datasets are highlighted.
Altmetrics are new measures of impact by capturing online mentioning of research outputs such as papers and datasets. Altmetric Explorer, Plum Analytics and Impactstory are some popular altmetrics tools, and the Library has recently started a subscription to Altmetric Explorer. In this post, you will learn more about Altmetric Explorer.
Unlike traditional citation databases which would yield results by keyword or topic search, Inciteful creates a graph of academic papers based on “seed papers” of your choice and helps you gain insight from it.
Google Dataset Search is a new search engine which allows you to search for datasets hosted in thousands of repositories across the Web. It looks on publisher sites, digital libraries, dataset providers, and on authors' personal webpages for metadata tags and returns a list of data repositories that best describes the datasets you need for your research. On the other hand, if you want to share your datasets and make them publicly accessible, you can follow the Google's guidelines for dataset providers which is an open standard for tagging and structuring your datasets. These guidelines include salient information about datasets: who created the dataset, when it was published, how the data was collected, what the terms are for using the data, etc. The overall approach is to improve discovery of the datasets by adopting a common standard by which Google and other search engines can better understand the content of the datasets. Here are some examples of what can qualify as a dataset as suggested by Google: