Accelerate Your Literature Review Process with Iris.ai Researcher Workspace

Table of Contents

1. Introduction
2. The Importance of Literature Review
3. Introducing Iris.ai Researcher Workspace
4. How it Works: An Overview
   • 4.1 Broad exploration with the Explore Tool
   • 4.2 Analyzing and Filtering with the Analyze Tool
   • 4.3 Summarizing with the Summarize Tool
5. Specific Use Case: Tracking Contextually Related Articles
6. Managing Personal Reading Lists
7. Uploading External Document Collections
8. Conclusion
9. Pros and Cons of Iris.ai Researcher Workspace

Introduction

Starting a new research project can be daunting, especially with the vast amount of scientific literature available. Conducting a comprehensive literature review is crucial to formulating and shaping research ideas. However, the process can be overwhelming and time-consuming. This is where Iris.ai's Researcher Workspace comes in. It is an AI-based platform that accelerates the literature discovery process and helps researchers manage their findings effectively.

The Importance of Literature Review

Before diving into the details of Iris.ai Researcher Workspace, it's essential to understand the significance of conducting a literature review. A literature review serves as the foundation of a research project. It involves making connections with related works and shaping one's own research ideas based on existing knowledge. With the ever-increasing number of published research Papers, it becomes impossible to review everything. A comprehensive literature review can help researchers stay informed and guide their research in the right direction.

Introducing Iris.ai Researcher Workspace

Iris.ai Researcher Workspace is an AI-based platform specifically designed to assist researchers and students in their literature discovery process. It offers five modules: Explore, Analyze, Filter, Summarize, and Extract. These tools work together to provide an efficient and effective way of processing scientific knowledge.

How it Works: An Overview

Iris.ai Researcher Workspace simplifies the literature discovery process with its intuitive and powerful tools. Let's take a closer look at how each module works.

4.1 Broad exploration with the Explore Tool

To make new discoveries and explore a research topic broadly, the Explore tool allows users to go beyond traditional keyword searches. By creating an Open Access dataset containing millions of scientific papers, researchers can generate exploratory maps based on their interests. These maps Visualize the connections between articles, uncover Hidden associations, and highlight Relevant articles. Users can easily create multiple maps based on different topics or their own research descriptions.

4.2 Analyzing and Filtering with the Analyze Tool

Once researchers have gathered a reading list, the Analyze tool helps them analyze and filter the articles. It identifies key concepts and topics within the articles, allowing researchers to focus on the most relevant ones. Users can choose to include relevant topics or filter the list based on WORD analysis. This tool provides a comprehensive overview of the selected articles, helping researchers identify common themes and key concepts quickly.

4.3 Summarizing with the Summarize Tool

To get a solid overview of a topic and kickstart the writing process, the Summarize tool generates machine-written summaries from abstracts, full-Texts, or even user-defined descriptions. This tool saves researchers time by providing concise summaries of relevant articles, allowing them to grasp the overall content without reading every article in detail.

Specific Use Case: Tracking Contextually Related Articles

Iris.ai Researcher Workspace offers a unique feature that allows researchers to track contextually related articles over a specific period. By defining additional context and using filters, researchers can narrow down their reading list to the most recent and relevant articles. For example, researchers can track all articles related to a specific chemical compound published in the last seven years. This feature helps researchers stay up to date with the latest developments in their field.

Managing Personal Reading Lists

In addition to exploring and analyzing articles within the platform, Iris.ai Researcher Workspace also allows researchers to manage their personal reading lists. Researchers can upload their own reading lists from external resources or their own collections of PDF articles stored on Google Drive. By using the Analyze tool, researchers can further define their reading lists, apply filters, and summarize the articles of interest. This flexibility makes it easy for researchers to integrate their existing collections and streamline their literature review process.

Uploading External Document Collections

To cater to researchers with large external document collections, Iris.ai Researcher Workspace enables users to upload their collections in various citation formats such as EndNote, BibTex, or CSV. Researchers can then apply the platform's analysis and filtering tools to these collections, extract metadata, and gain valuable insights from their own collection of articles.

Conclusion

Iris.ai Researcher Workspace is a powerful AI-based platform that streamlines the literature discovery process for researchers and students. By providing tools for exploration, analysis, filtering, and summarizing, it helps researchers make new discoveries, manage their reading lists, and stay up to date with the latest developments in their field. With Iris.ai's Researcher Workspace, researchers can save time and focus on writing conclusions and conducting groundbreaking research.

Pros and Cons of Iris.ai Researcher Workspace

Pros:

• Accelerates the literature discovery process
• Provides a comprehensive overview of a research topic
• Helps researchers make new discoveries through contextual exploration
• Efficiently filters and analyzes articles to identify key concepts
• Provides machine-generated summaries for quick understanding

Cons:

• Dependency on the quality and relevance of the articles in the dataset
• Limited to accessing and analyzing articles available in Open Access
• May require additional manual curation for more specific research needs

Highlights

• Iris.ai Researcher Workspace is an AI-based platform that accelerates and streamlines the literature discovery process for researchers and students.
• The platform offers tools for exploration, analysis, filtering, and summarizing, enabling users to make new discoveries, manage reading lists, and track contextually related articles.
• Users can upload external document collections, apply filters and analysis tools, and gain insights from their own collections of articles.
• Iris.ai Researcher Workspace saves researchers time and helps them stay up to date with the latest developments in their field, allowing them to focus on writing conclusions and conducting groundbreaking research.

FAQ

Q: Can I access articles that are not available in Open Access? A: No, Iris.ai Researcher Workspace currently relies on Open Access articles for its dataset.

Q: Can I track contextually related articles beyond the last seven years? A: Yes, the platform allows users to define their own timeframe for tracking contextually related articles.

Q: Can I export my reading lists or analysis results from the platform? A: Yes, Iris.ai Researcher Workspace offers export options for reading lists and analysis results, allowing users to further refine their findings or share them with collaborators.

Resources

• Iris.ai Researcher Workspace
• Iris.ai Blog