NSF and other organizations have strongly invested in a new generation of information technologies for scientific research. This includes prototypes such as those developed by the NSF-funded projects “Science Environment for Ecological Knowledge” (SEEK), “Webs on the Web: Internet Database, Analysis and Visualization of Ecological Networks” (WoW), and “Semantic Prototypes in Research Ecoinformatics” (SPiRE). These projects have created new technological foundations for enhanced ecological research. However, those foundations have yet to support several of the most important integrative activities that they were designed to support. For example, while a wide array of WWW-based ecological databases continue to be developed and used by thousands of researchers, researchers typically need to first learn each user interface and then manually explore whether each database contains useful data. When found, analyses typically need to be designed from scratch (often reinventing the wheel), and data needs to be manually extracted and converted to a specific format.

Here, we propose to extend, integrate, and automate access to and analysis of ecological data by developing and implementing proven and emerging information technologies, particularly those related to the Semantic Web. This will be done “horizontally” by developing integrative web services somewhat similar to “mashups” for several large ecological databases and by developing graphical user interfaces enabled by these services to access disparate types of data, seamlessly feed the data into workflow systems, and conduct integrated analyses in an automatically documented manner. These activities will be integrated so that users can easily access a wide variety of ecological data and analyses based on concepts such as taxonomy, habitat, geography, and trophic relations. For example, our proposed graphical user interfaces would allow seamless access to and integrated analysis of data related to plant-herbivore dynamics by drawing on plant abundance data from surveys in the SALVIAS database, identifying associated local herbivores and their body sizes from an augmented WoW database, and analyzing contemporaneous time series of those herbivores drawn from the Global Population Dynamics Database. This project will transform biology by creating new technologies used to introduce deeply functional informatic “mashups” that synergize existing informatic resources using more user-friendly integrative UIs.

Achieving such advances will require us to deliver on several of the most important yet largely unfulfilled promises of the Semantic Web by developing new degrees of interoperability and reasoning among scientific ontologies and the instances (e.g., observations and concepts) that they organize. Within the context of this proposal, this requires synthesis of several fundamental types of ecological data (species’ identities, traits, abundances, and locations) underlying many research topics including three we focus on here: functional traits, population dynamics, and relative abundance. Integration across the multiple types of data and research topics will be achieved via three central tasks: Task 1:Design and implement new information architectures that increase the functionality and performance of ecoinformatic software on the Semantic Web; Task 2:Design and implement new client tools with graphical interfaces aimed at end users, including tools used in educational and curricular modules; and Task 3: Extend ontologies and increase content.