JournalMap: Discovering location-relevant knowledge from published studies for sustainable land use, preventing degradation, and restoring landscapes

TitleJournalMap: Discovering location-relevant knowledge from published studies for sustainable land use, preventing degradation, and restoring landscapes
Publication TypeConference Paper
Year of Publication2015
AuthorsKarl J, Herrick JE, Gillan JK
Conference NameUNCCD 3rd Scientific Conference Book of Abstracts
Date Published03/2015
Conference LocationCancun, MX
ARIS Log Number320436

Finding relevant knowledge and information to prevent land degradation and support restoration has historically involved researchers working from their own knowledge, querying people they know, and tediously searching topical literature reviews. Over the past two decades, vast quantities of knowledge and information have been made accessible, but finding that which is relevant often remains difficult and inefficient. The relevance of knowledge is determined by how closely the context in which it was created matches a given situation (Karl et al. 2012). In land stewardship and restoration, context includes both patterns of the biophysical (e.g., soils, climate, landform) and human environment. However, the ability to determine what is known about a land use or restoration practice in a particular landscape is hindered by current search technologies because they still rely primarily on key word, topic, text, and author searching – concepts of cataloging and searching for published information that have changed little since the late 1800s. With the addition of geographic filters and the locations of where studies have occurred, search results could be limited to specific areas and searches could be extended to contextually-similar areas across the globe.  Methods: To address this need we created JournalMap (, a map-based scientific literature database and search engine (Karl et al. 2013b). 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. Article content in JournalMap comes from partnerships with publishers (e.g., Taylor & Francis, Pensoft, IOP) and research organizations, existing literature georeferencing efforts, and crowdsourcing from JournalMap’s users.  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. 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 (See Figure). JournalMap currently allows users to search for literature based on a few existing spatial layers including geology, soils, vegetation, through a simple overlay analysis of existing spatial data layers.  Results: JournalMap's literature database currently contains records for over 20,000 articles on a diversity of topics, and new content is being added continually. We have found that across knowledge domains approximately 85% of published studies are attributable to a mapable location, and around two-thirds of modern studies report geographic coordinate values that can be automatically extracted. Automated mapping of scientific knowledge could be improved by the adoption of standards for location reporting. In addition to map- and similarity-based searching, Journal Map data has been used to look at the distribution and spread of knowledge on topics over time like species conservation and to evaluate bias in the location and distribution of knowledge. To illustrate the potential for JournalMap to identify relevant knowledge for an given area, we examined research studies from the Chihuahuan Desert of the southwestern United States. We mapped the locations of more than 800 journal articles that were returned from a Web of Science™ search on “Chihuahuan Desert”. Only a third of the search results were actually from the target area. Additionally, the keyword literature search missed any study in the area that didn’t use those two terms. In JournalMap’s existing database, we found over 100 articles in the target area that were not included in the keyword search. Outcomes:  JournalMap’s ability to search for ecological and agricultural literature thematically and geographically improves the ease of accessibility of potentially relevant research findings, promote syntheses and meta-analyses, provide mechanistic understanding to environmental patterns and causes of land degradation, facilitate evaluations of bias in ecological knowledge, and limit redundancy in conducting new studies (Karl et al. 2013a). JournalMap’s database could be easily extended to include governmental reports on land degradation and restoration, providing a powerful tool for discovering and using the “dark data” that is often hidden in these documents because they are not easily discoverable.  Additionally, through a publically available application programming interface (API) JournalMap’s geographic search capabilities and georeferenced literature database can easily be combined with other databases (Karl and Herrick 2013) of land use practices (e.g., WOCAT), conservation projects, and site-based assessments of land potential (e.g., Land Potential Knowledge System).