Wildbook™ is an open source software framework to support collaborative mark-recapture, molecular ecology, and social ecology studies, especially where citizen science data needs to be incorporated and managed. It is developed by the non-profit Wild Me and is the data management layer of the broader IBEIS Project.
The biological and statistical communities already support a number of excellent tools, such as Program MARK,GenAlEx, and SOCPROG for use in analyzing wildlife data. Wildbook is a complementary software application that:
provides a scalable and collaborative platform for intelligent wildlife data storage and management, including advanced, consolidated searching
provides an easy-to-use software suite of functionality that can be extended to meet the needs of wildlife projects, especially where individual identification is used
provides an API to support the easy export of data to cross-disciplinary analysis applications (e.g., GenePop ) and other software (e.g., Google Earth)
provides a platform that supports the exposure of data in biodiversity databases (e.g., GBIF and OBIS)
provides a platform for animal biometrics that supports easy data access and facilitates matching application deployment for multiple species
Wildbook is the data management layer for the Image-Based Ecological Information System (IBEIS). IBEIS computer vision components pull data from Wildbook servers to detect features in images and identify individual animals. IBEIS brings massive-scale computer vision to wildlife research for the first time.
Images have become the most abundant, available and cheap source of data. The explosive growth in the use of digital cameras, together with rapid innovations in storage technology and automatic image analysis software, makes this vision possible particularly for large animals with distinctive striped, spotted, wrinkled or notched markings, such as elephants, giraffes and zebras. This large number of collected images must be analyzed automatically to produce a database that records who the animals are, where they are, and when they were photographed. Combining this with geographic, environmental, behavioral and climate data would enable the determination of what the animals are doing, and why they are doing it. This is our vision of IBEIS: an Image-Based Ecological Information System.Learn more.
Jason Holmberg is the Information Architect for Wildbook. Jon Van Oast and Drew Blount are the primary software developers. Together we bring a wealth of professional programming experience in data management, computer vision, and machine learning to the project.
Dr. Scott Baker of Oregon State University designed the DNA-related components within the software and remains an active adviser on the project.
Please email “services [at] wildme [dot] org” to receive access credentials for the demo site, which refreshes itself periodically, allowing you to run real world tests of Wildbook.
Wildbook 6.0 beta testing has begun. We anticipate an August release. Flukebook.org is featuring the new code, which will also be migrated to other Wildbooks quickly. Wildbook 6 merges the IBEIS.org and Wildbook.org projects into a single project re-using the name “Wildbook”!
Check out the new humpback fluke matcher developed with Wildbook under the IBEIS.org project! This is one of two matchers we have coming out.
Wildbook 5.5 has been released!
New features and fixes in Wildbook 5.5 include:
MOD: Standardization of PostgreSQL as the required database for Wildbook and removal of Derby and other database support. While Wildbook can technically support a wide array of databases and J2EE servers, we're standardizing on Tomcat and PostgreSQL for Wildbook 5.5 and all versions moving forward. We are also now highly recommending running Wildbook on Ubuntu Linux servers in Amazon's EC2 service. This also means that PostgreSQL must be installed and preconfigured for Wildbook to run.
FIX/MOD: Broad database connection improvements and fixes to better manage and close multiple database threads under higher usage.
FIX: Switch to full support of Encounter.individualID as NULL (upgrade fix script required for previous Wildbooks)
NEW: Make Google Map on main landing page (index.jsp) fully responsive for better mobile display
MOD: Remove automatic date filtering on Encounter Search default display
FIX: Better exception handling in spot matching grid
FIX: Make email templates more generic (remove project-specific branding) for reuse across projects
MOD: Persistence layer upgrade to DataNucleus 4.2
FIX: Improve sub-object REST/JSON display for typed Collections
NEW: Google reCAPTCHA integrated to prevent spurious data submission (upgrade requires getting Google key for your web site)
MOD: Switch to wildbook_data_dir as default data directory (check your configuration on upgrade)
MOD: change default username and password for database connections (now wildbook/wildbook)
MOD: Set logging directory relative to POM artifact to help prevent startup log errors
NEW: Add alternateID support for top bar Site Search of MarkedIndividuals
Wildbook is designed to produce successful, reproducible collaborations between biologists, biostatisticians, computer scientists, and citizen scientists by providing a Web-based software platform for collaboration.
Is Wildbook right for you?
If you answer yes to any of these questions, Wildbook may be a very good choice for your research.
Are you trying to track individual animals in a wildlife population using natural markings or genetic identifiers?
Are you collecting biological samples from a wildlife population and performing genetic or chemical analyses (e.g., stable isotope measurements, haplotype determination, etc.)?
Are you looking to increase wildlife data collection through citizen science?
Are you looking to build a collaborative, distributed research network for a species?
Are you looking to develop a new animal biometrics solution (e.g., pattern matching from photos) for one or more species?
Are you collecting behavioral and/or social data for a wildlife study population?
The framework is open source and meant for you to extend it for your specific project! If it doesn't have the feature you need, use some simple Java programming and create it. Some things we have used it to do on whaleshark.org are:
Quickly generate open and closed capture history files for population modeling in statistical packages, such as U-CARE, CloseTest, and Program MARK
Generate statistical reports
Rely on spam filters to block spurious data submission
The development of additional functionality is currently underway.
You can help move Wildbook forward by making a donation! Your donation is tax deductible in the United States.
Please send feedback to jason at whaleshark dot org. Your ideas to improve Wildbook are most welcome!
Wildbook was started by Jason Holmberg as the software behind the Wildbook for Whale Sharks, which is a multiuser, web-based, research application for studying whale sharks (Rhincodon typus). The aim of WIldbook for Whale Sharks is to prevent individual “silos” of whale shark data and to promote a global, cooperative approach to whale shark research using the Web as a communications and research platform. The Library went on-line and began collecting whale shark encounter data from the web in January 2003. In early 2004, the pattern-recognition system that allows the Library to distinguish between individual whale sharks using natural spot patterning was integrated. Since its first line of code, this Wildbook has seen continuous feature additions, bug fixes, and performance enhancements. Our work to maintain and enhance the Library is ongoing and requires knowledge of Java, J2EE, JDO, PHP , Flash/Flex, HTML , XML , RSS , a wee bit of Python, and CSS .
The following publications have resulted from Wildbook-related work:
Michener WK, Jones MB. Ecoinformatics: supporting ecology as a data-intensive science. Trends Ecol Evol. 2012 Jan.;27(2).
Schwarz, C. J. (2009). Migration and movement – the next stage. Pages 325-350 in Modeling Demographic Processes in Marked Populations Series: Environmental and Ecological Statistics , Vol. 3. Thomson, David L.;Cooch, Evan G.; Conroy, Michael J. (Eds.). Springer, New York.
Williams BK, Nichols JD, Conroy MJ (2002) Analysis and management of animal populations. Academic Press, San Diego, CA.
White GC, Burnham KP (1999) Program MARK: Survival estimation from populations of marked animals. Bird Study 46:120. 138.
Whitehead, H. Analyzing Animal Societies: Quantitative Methods for Vertebrate Social Analysis (University of Chicago Press, 2008).