Elsevier takes the next step in making researchers’ lives easier with the new DataSearch engine. You can search for research data across numerous domains and various types, from a host of domain-specific and cross-domain data repositories. It’s available at (https://datasearch.elsevier.com/) – please join our User Panel to help improve it!
More Focused Searching
Mass search engines are ubiquitous and useful; however, when it comes to specific information tailored to the needs of the modern researcher, a more focused application is required. In response to this need, Elsevier has created DataSearch. Drawing on reputable repositories of information across the internet, researchers can readily find the data sets they need to accelerate their work.
DataSearch offers a new and innovative approach. Most search engines don’t actively involve their users in making them better; we invite you, the user, to join our User Panel and advise how we can improve the results. We are looking for users in a variety of fields, no technical expertise is required (though welcomed). In order to join us, visit https://datasearch.elsevier.com and click on the button marked “Join Our User Panel”. Please detail in your e-mail the following:
We look forward to working with you and improving the research experience.
Last Fall, we wrote about finding what is relevant to your research. We have a long way to go until we reach even half of our goals in helping you discover great content, but we are one tiny step closer as of today.
Today we launched a catalog search engine on the Mendeley Website. Moreover, we already have an advanced search that will be released in two weeks building on top of what you can use starting today. You can start using the basic search by going to the Research papers page.
What is different about Mendeley search compared to other literature search engines?
Two things standout: 1) Diversity of the literature and 2) ReaderRank
Diversity of the literature
Because Mendeley encompasses a broad range of academic disciplines, we have enormous diversity in our data set to draw results from. This is great, but also a challenge. The challenge comes from delivering results that are relevant to you and avoiding ambiguity with other disciplines. This WILL improve as we make tweaks and personalize the search experience. What’s great about this diversity though, is that inter-disciplinary content will surface if it is relevant.
Relevant content is the strongest factor in the results you receive, but we wanted to take advantage of the knowledge of the crowds as well. With that in mind, we have developed an algorithm called ‘ReaderRank’ that will adjust results based on the level of readership for an article. This doesn’t mean the most read articles will always appear at the top, only that it is an additional measure in ranking your results. We have also taken care to prevent artificial enhancement of the results, i.e. gaming the readership. Over time, we hope to refine this algorithm by taking into account other measures of quality such as the reputation of who you trust and follow on Mendeley.
Once again, we will release an advanced search in two weeks that will let you refine search queries. We also want to encourage feedback. So, if you have any thoughts about the quality of results or what you might like to see in terms of search features, please let us know by going to our feedback forum.