Pick up your smartphone and ask it where the nearest place is to buy a cup of coffee. You will be presented with a map showing all of the nearby coffee shops. Choose one and your phone displays walking directions on a map with an arrow guiding your path. It’s amazing and getting better every day. This use of geographically specific information is now so commonplace that we take it for granted. Yet, not all information is so easily searched geographically – particularly the search for scholarly research.
Harnessing the Geography of Science
Access to scholarly literature has improved dramatically in recent years, and it is easier than ever to search across disciplines and sources to find useful references. However, the ability to find what is known about a specific place is still hindered by search technologies that primarily rely on keyword, topic, text, and author searching – concepts of cataloging and searching for published information that date back to the late 1800’s.
The problem is that keyword searches are an inadequate way to find relevant research for specific places. Consider the example of finding research studies from the Chihuahuan Desert of the southwestern U.S. We mapped the locations of more than 800 journal articles that were returned from a Web of Science™ search on “Chihuahuan Desert” (Figure 1a). Only a third of the search results were actually from our target area. Additionally, our keyword literature search missed any study in the area that didn’t use those two terms (Figure 1b).
We believe that adding map-based tools to searching for scientific literature based on the locations where studies were actually conducted can be a powerful new approach to finding relevant research - not only for an area of interest, but also for other similar areas. The importance of being able to search by location or on attributes that can be derived from a study’s location is most obvious for the natural sciences, but is equally important for many other fields such as epidemiology, microeconomics, and linguistics.
The ability to search for scientific literature geographically and thematically stands to not only improve the ease and accessibility of relevant research findings but also promote syntheses and meta-analyses, provide greater understanding of processes that create environmental patterns, enable evaluations of knowledge biases, and limit redundancy in conducting new studies.
The idea of mapping scholarly literature itself is not new. There are examples of geotagged bibliographies from many fields including natural resources and human infectious disease. Some publishers are now even providing interactive maps for articles accessed online (but generally lack geographic searching or the ability to view locations of multiple articles simultaneously). But, these efforts have been largely ad hoc with no way to search for literature by location, share, or analyze records outside of their systems, or integrate with other spatial databases that could be used to attribute the articles. This led us to create JournalMap.
A JournalMap for Scholarly Literature Discovery
JournalMap is a map-based scientific literature database and search engine (Figure 2). JournalMap uses study area descriptions from an article (not author affiliations) to map where the research was actually conducted. All articles in JournalMap are geotagged, either automatically using pattern recognition algorithms looking for geographic coordinates or manually from text-based descriptions. Each article record in JournalMap links directly to the publisher via the article’s DOI.
JournalMap makes it easy to search for literature from specific places through a simple map interface. Results of JournalMap searches can be exported in different formats or saved as a collection with a unique URL for a spatial bibliography on a topic, to showcase a set of articles from a journal, or for a georeferenced CV of an author’s papers (Figure 3).
For many topics, though, there has been little research done in many parts of the world. But, research conducted in areas with similar physical, environmental, cultural or political contexts can, in many cases, be relevant to these understudies regions. JournalMap includes search filters for similarity-based searching with layers such as climate, soils, elevation and land cover. We are adding additional filters for attributes like population density, culture, language and infrastructure.
JournalMap’s content comes from several sources. For working with publishers, JournalMap can directly import article XML in industry-standard NLM and JATS formats. Authors and researchers can also contribute articles on their own directly through the JournalMap website – needing only the article DOI (or citation information) and study locations.
Challenges and Opportunities
Our goal with JournalMap is to make geographic-based literature searching commonplace in scientific research. Yet, the information about where a study was conducted is locked up in the text and figures of scholarly articles, and in myriad forms that are not easily searchable.
To make our goal a reality, three challenges need to be addressed. The first is developing ways to more efficiently geotag previously-published articles. This is a large and complex task, but can be addressed through a combination of approaches like intelligent text-mining and crowdsourcing. The second challenge is achieving standards for reporting locations in scholarly literature, capturing that location information at article submission, and encoding it in a machine-readable format in article metadata. The final challenge is developing robust and interconnected geographic search and analysis tools for scientific literature.
JournalMap is working on all three of these fronts, but our efforts alone will not be sufficient to get the job done. We would like to invite the publishing industry as well as journal editorial boards to work with us to develop and implement standards for better location reporting and encoding in articles. Additionally, we encourage authors and researchers to visit JournalMap.org and contribute articles to help grow the database and prove the concept. We believe the time is right for the idea of geographic-based science discovery to take hold and transform scientific knowledge discovery and application.