Federated search is a technique that allows a user to make a single query which in turn acquires aggregated search results from multiple sources of information into a single interface.
In other words, the same query is executed against multiple databases simultaneously, and the federated search results to these queries are presented together. An example of federated search in action can be seen at Kayak, the travel site that searches for flight and hotel availability across thousands of different websites and returns results that allow the searcher to comparison shop for the best price and availability.
At a high level, the benefits of federated search are clear. In the case of searching for flights there are a limited number of choices between two destinations, but it’s still helpful to compare departure times and prices. But for booking a hotel, a federated search is dramatically faster and enormously more convenient - most destinations have hundreds if not thousands of hotels and motels to choose from.
Other examples of federated solutions for search:
ResoluteAI, now part of the Research Solutions’ family, is a federated search engine that focuses on providing scientific information for research, technology landscaping, and analysis.
Data Consolidation & Improved Experience
Users often search for information from several data sources, including internal data repositories, websites, intranets, and network drives. With a federated search, these users can browse for this data simultaneously from a consistent, unified interface.
This type of technology is instrumental in opening up siloed information from different organization departments. For instance, a human resources officer can search for disparate information on employee performance across various departments from their familiar HR portal, or a scientist can search for information in an Electronic Lab Notebook (ELN) and a Laboratory Information System at the same time.
With data consolidation, you no longer have to manage multiple platforms or sites. The work is done for you.
Security & Reliability
Federated search can find and acquire information that may be hidden behind gated sources. This is possible by having the search query also send user credentials, which allow the user to see information that wasn’t formerly accessible from a typical web search.
Universities and institutions of higher learning are excellent federated search examples. They can deploy a federated search tool to provide students with secure access to subscription-based academic journals. Students can view the results from disparate sources as a combined list without logging in each time.
Also, if a user isn’t permitted to access information from a particular source, the results won’t be shown to them. Therefore, two users can access the same interface and still have different results based on their access permissions.
As you can see, features like security and reliability are central to this technology.
Improved Data Visibility
Federated search tools give the searcher the ability to weigh sources according to their relevance to the information they’re seeking. Consequently, they can adjust the results to provide searchable information that meets their particular needs.
Consider a researcher investigating a new medical device or procedure. Their search might include articles that appear in PubMed, which largely contains peer reviewed articles. But a federated search might also return results from a preprint server, which may be relevant but not yet as authoritative as articles from PubMed.
By improving data visibility, a company can request and gain access to a wealth of resources that can transform your service, product, and solutions.
AI-powered search (also known as intelligent search or cognitive search) can provide better, more comprehensive search results and can more effectively answer questions that are specific to a user’s needs.
Artificial intelligence provides the tools that offer the ability to:
Companies whose products are often the result of scientific experimentation generate an enormous amount of structured and unstructured content. This data is produced constantly and is frequently searched upon. Combined with external research sources such as academic publications, clinical trials, patents, regulatory and compliance data, and more, the ability for users to search these numerous sources simultaneously saves time and money, and yields better search results.
Federated search software, therefore, assists R&D-focused enterprises in the following ways:
In the words of one of our customers:
“The benefit, compared to other tools that we have, is that it searches simultaneously across multiple data sources. It's AI-enabled and it includes simple but useful visual analytics that allow you to drill down into the data... It hits that sweet spot.”
Customers span healthcare and life sciences to chemicals, material science, and consumer products. We offer a combined solution that incorporates federated search for publicly available databases such as clinical trials, academic research, and patents, as well as a search capability for internal data that can exist in any format - documents, video, audio, webinars, presentations, etc.
Our Foundation Scientific Discovery engine is regularly adding new data sources and continues to upgrade its tagging capabilities with new taxonomies and controlled vocabularies.
At Research Solutions, we focus on intelligence search to assist research-intensive organizations in using data to help make their next big discovery. We specialize in science - our data, machine learning, analytics, and data connection capabilities are focused on scientific research and development, from ideation to post market surveillance to pharmacovigilance.
Talk to our experts today about leveraging the power of more intelligent search.