Next Wednesday, I’ll be making a presentation to the Ontario Association for Remote Sensing (OARS). The details are available online. As you can see from the abstract,

Incorporating Feature-Based Annotations into Automatically Generated Knowledge Representations

Earth Science Markup Language (ESML) is efficient and effective in representing scientific data in an XML-based formalism. However, features of the data being represented are not accounted for in ESML. Such features might derive from events (e.g., a gap in data collection due to instrument servicing), identifications (e.g., a scientifically interesting object in an image), or some other source. In order to account for features in an ESML context, consideration is given from the perspective of annotation, i.e., the addition of information to existing documents without changing the originals. Although it is possible to extend ESML to incorporate feature-based annotations internally (e.g., by extending the XML schema for ESML), there are a number of complicating factors that are identified. Rather than pursuing the ESML-extension approach, attention focuses on an external representation for feature-based annotations via XML Pointer Language (XPointer). In previous work, it has been shown that it is possible to extract relationships from ESML-based representations, and capture the results in the Resource Description Format (RDF). Thus attention focuses here on exploring and reporting on this same requirement for XPointer-based annotations of ESML representations. Earth Science examples allow for illustration of this approach for introducing annotations into automatically generated knowledge representations.

my intention is to emphsize some of my recent research into annotation. Most of this work is being done in collaboration with Jerusha Lederman and Keith Aldridge of York University.

The above abstract very closely resembles a submission that was recently accepted for the Fall Meeting of the American Geophysical Union (AGU). I’ll be blogging more on that soon.