Posted by: bluesyemre | September 7, 2020

Best 5 Academic Search Engines for Research (Multidisciplinary)

Best 5 Academic Search Engines for Research (Multidisciplinary)

In this post, we will go through the best 5 free multidisciplinary academic search engines and get to know about their use.

There are a plethora of scholarly materials on the web. It is a difficult task for a researcher to find reliable and relevant scholarly articles from these dense piles of academic materials on the web. The academic search engine alleviates the problems smoothly.

If you want to know the best search engines for academic research, you have come to the right place.

When we talk about web resources searching for our research work, the first name that comes to our mind is the Google search engine.

This is a list of the five best free multidisciplinary academic search engines for accessing influentials and relevant research papers.

List of the Best Five Academic Search Engines

  1. Bielefeld Academic Search Engine (BASE)
  2. Microsoft Academic
  3. Google Scholar
  4. COnnecting REpositories (CORE)
  5. Semantic Scholar

Let’s explore the academic search engines.

#1: Bielefeld Academic Search Engine (BASE)

Bielefeld Academic Search Engine (BASE) is a free open-source multidisciplinary academic search engine. The BASE lets you search scholarly resources on the web. You can search journal abstracts, articles, preprints, images, and videos. 

The BASE search engine was designed and developed by Bielefeld University, Germany. At the time of this writing, this tool provides more than 241,960,866 documents from more than 8,348 sources. 

The academic search engine indexes the metadata of various types of academically relevant materials such as journals, institutional repositories, digital collections, etc.

Here is the snapshot of the web search interface of the BASE search engine:

BASE web search interface a academic search engine for researchers
BASE Web Search Interface

Now, you just enter the keyword of interest in the search area and hit the search button. Here, we use “Open Educational Resources” for searching the relevant academic research articles.

Once you click on the search button, you will then be taken to the search result page:

BASE Search Engine Result using Academic Search Engine
BASE Search Engine Results

Using this tool, you can perform a verbatim search and multilingual search. Besides, it also allows you to search open access scholarly documents.

To search the relevant scholarly articles, you just click on the “Advanced Search” tab. The advance search interface will appear.

 Advanced Search using the BASE Academic Search Engine
BASE-Advance Search

You can narrow a search using the advanced search. There are various types of fields such as DOI (Digital Object Identifier), title, author, ORCID ID ((Open Researcher and Contributor ID), and subject headings in the search engine.

In addition to that, you can also enter part of the URL, the entire document as per your requirement. This tool allows you to narrow your search on Creative Commons (CC).

This state-of-the-art tool lets you search carefully on open access content and free publicly available academic resources. It indexes metadata such as author, title, abstracts of the scholarly documents.

Once you get the search results then you can export bibliographic data in various formats such as RIS, and BibTeX.

This search engine supports modern web browsers like Google Chrome, Apple Safari, Mozilla Firefox, Microsoft Edge.

The BASE website is properly designed to comply with all kinds of operating systems. 

Go to this link for more information- FAQ-Link

#2: Microsoft Academic Search Engine

Microsoft Academic is one of the most important academic search engines. This tool allows you to search journal titles, authors, conference names, and many research topics from various sources on the web.

Microsoft Academic searches meta-data rather than the full-text. This search engine does not allow a boolean search like AND, OR.

This web search engine has been designed and developed over the open dataset provider Microsoft Academic Graph (MAG). You can process the dataset of scholarly metadata offline through the MAG subscriptions.

We have accessed this website on 28th August 2020, the following stats of various resources are displayed on their site.

Numbers of publications, journals, authors, institutions in Microsoft Academic Search Engine
Entire Stats

In order to access this search engine, navigate to Microsoft Academic Homepage, you should see the web search interface like this:

Web Search Interface of Microsoft Academic Search Engine
Microsoft Academic Search Interface

Using this interface, you can search any topic, author and journal, or any combination of these topics.

In our case, we have used the term “Open Educational Resources” for searching purposes. We just put this term in the search box and hit enter.

Once you hit the enter, the following web page will appear.

Search Results for Open Educational Resources by Microsoft Academic Search engine
Search Results

Once the engine completes the search process, you will get the information related to your search topic:

  1. Top Authors and Institutions
  2. Publication Types and Top Topics
  3. Top Journals and Conferences

Besides, it also displays the parent, child, and related topics based on your search topic.

Search related Topics by Microsoft Academic
Related Topics

Moreover, the search engine lets you sort the articles by relevance such as saliency, newest first, oldest first, etc.

Articles sort by relevance using Microsoft Academic search Engine
Articles Sort by Relevance

Once you complete the search then you can export bibliographic data in various formats like APA, MLA, and BibTeX.

The Microsoft Academic web pages comply with all kinds of modern web browsers and operating systems. 

In our earlier post, we briefly described Microsoft Academic Engine.

Go to this link for more information- FAQ-Link

#3: Google Scholar-Academic Search Engine

Google Scholar is one of the largest and most advanced academic search engines. It was launched in 2004. It is a free multidisciplinary, easy to use, robust search engine. The search engine lets you find relevant work across the world of scholarly literature.

You can search across various disciplines and sources like abstracts, articles, theses, books, patents, conference proceedings, online repositories, and other web materials.

It indexes 390 million scholarly literature across a range of disciplines. You can access both open and closed source scholarly materials using this discovery tool.

To perform the above-mentioned job, you open Google Scholar and then enter the search topic. Here, we enter “Open Educational Resources” for obtaining scholarly resources.

Here is a snapshot of the search results page:

Search Results using the free academic search engine
Search Results

Google Scholar lets you create an online library to organize your scholarly articles and so that you can use it later.

In addition, you can create a search alert to know when new scholarly resources on your topic have been uploaded on the web. Since the launch of Google Scholar in 2004, search alert has been the most popular mode of notifying alert among the researchers.

The search alert is one of the most important features of Google Scholar. We have to visit the site repeatedly to perform the same search. A search alert solves this problem and saves you precious time.

You do not need to visit the search engine site repeatedly for the same work. It lets you know when new scholarly materials on your topic have been included on the web.

In a previous post, we wrote about how to set up Search Alert in Google Scholar.

There are various types of search fields in Google scholar such as article, title, author, publication, and date.

If you want to do an advance search, click on the three dash bar on the extreme left. You will see the sub-menu window.

Advanced Search using Google Scholar Academic Search Engine
Advanced Search

Now, once you click on the “Advanced Search”, you will then be taken to the following webpage.

Advanced Search Fields in Google Scholar Academic Search Engine
Advanced Search Web Interface

Once you get the search results then you can export bibliographic data in various formats such as APA, MLA, Chicago, Harvard, Vancouver, RIS, and BibTeX.

The Google Scholar supports all kind of modern web browsers like Google Chrome, Safari, Mozilla Firefox, Microsoft Edge, and operating systems.

Go to this link for more information- Link

#4: COnnecting REpositories (CORE) Academic Search Engsine

COnnecting REpositories (CORE) is one of the largest aggregators of open access research papers. It is a multidisciplinary not-for-profit service delivered by The Open University and JISC.

CORE is designed and developed with more filters and facets. It provides open accessed scholarly literature. Besides, this aggregator harvests and caches full-text scholarly articles from various registries.

In this web search, we just put the keyword “Open Educational Resources” for searching the academic research articles. You should see the window like this:

CORE Search Results

There are two types of search processes such as simple search and advanced search.

Here is the snapshot of the advanced search along with its fields.

Advanced Search using CORE Academic Search Engine
CORE Advanced Search

The advanced search lets users narrow their search to specific fields as shown above. You can export BibTex file using this tool.

From various registries, such as OpenDOAR and DOAJ, it uses the information to include new repositories and journals into CORE.

The CORE supports all kinds of modern browsers like Google Chrome, Safari, Mozilla Firefox, Microsoft Edge, and operating systems.

Go to this link for more information-FAQ Link

#5: Semantic Scholar Academic Search Engine

Semantic Scholar is a free, multidisciplinary AI-powered academic search engine that lets you discover relevant scholarly materials on the web.

This discovery tool was launched in 2015 at the Allen Institute for Artificial Intelligence.

You navigate to Semantic Scholar for searching the high quality, peer-reviewed academic research articles. This state-of-the-art AI-backed tool supports modern web browsers like Google Chrome, Safari, Mozilla Firefox, Microsoft Edge.

Here, we enter “Open Educational Resources” for obtaining influential scholarly resources. Once you press the search button you will get the following results.

Semantic Scholar Academic Search Engine for Researchers
Semantic Scholar Search Results

Using the Artificial Intelligence baked engine, this robust tool extracts the meaning from the scientific literature. This multidisciplinary tool indexes high-quality research articles from all fields of science.

“My Library” is one of the most important features in Semantic Scholar. You can use “My Library” in this tool to add the publications. This allows you to easily revisit any publication in your library through your free account.

In addition to that, you can also create an email alert to stay up-to-date on scholarly literature in your field of study. There are various types of alerts in the Semantic Scholar like authors, papers, and topics.

Once you get the search results, Semantic Scholar lets you export the BibTeX and Endnote file using the “cite” on the search page. In order to export the BibTex(.bib) file, you just click on the BibTex button. You can also download EndNote (.enw) file.

Here is a snapshot of cite tab for exporting data:

Exporting .bib file using BibTex button
Exporting BibTex File

It supports BibTeX, MLA, APA, and Chicago format. You have to select the options from the “cite” tab.

Semantic Scholar supports the latest versions of the most popular operating systems.

Hopefully, this article was useful to you! If you enjoyed this post, lets others know about the best 5 academic search engines.

Dr. Ujjal Marjit leads the Centre for Information Resource Management of the University of Kalyani, India. He received his bachelor honours degree from Visva Bharati, Central University and Master in Computer Application from Jadavpur University, India.He did his BLISc and MLISc from Madurai Kamraj University, India. He obtained his PhD in Computer Science and Engineering from University of Kalyani. He was also a visiting researcher at Norwegian University of Science and Technology (NTNU), Norway. Dr. Marjit was a member of the Association for Computing Machinery (ACM), USA. He has coauthored several book chapters and over 70 research publications in various International Journals and Conferences. Dr. Marjit attended many national and international conferences in India and abroad ( Germany, London, Finland, Norway, Netherlands). He has been working in University since 2001.


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