Web of Science Has a New Interface
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.
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:
Last week, we briefly introduced a number of visualization tools for citation network. In this post, we will demonstrate how to use VOSviewer to create a bibliometric visualization for HKUST research network.
Research evaluation measures research quality in several dimensions, such as research projects, researchers, institutions, research output and impact, and more.
VOSviewer is a popular software that visualizes connections between research works. You can use it to create networks of term co-occurrence. Here is a very good training video that guides you to do that.
With Connected papers, you can explore papers in your research field using graphs. You may discover more papers than traditional literature searches.
In your academic writing, you may cite a work to support your findings, or you may cite to refute the argument in the cited work. Citation count ("1" in both cases) does not tell you how a work is cited. Now there are tools that can reveal citation contexts. This post introduces one of such tools: scite.