What a difference a day makes!
Yesterday I learned that my paper on semantic platforms was rejected.
Today, however, the news was better as a manuscript on annotation modeling was
accepted for publication.
It’s been a long road for this paper:
- Its conception dates back to a presentation I gave at the 2006 Fall Meeting of the AGU.
- The paper was submitted as a contribution for Computers
& Geosciences Special Issue on Geoscience Knowledge Representation in
- The initial reviews called for major revisions. With tremendous support from my co-authors, the paper was significantly revised, and re-submitted.
- After some additional interactions, I just learned that the paper was finally accepted for publication.
The abstract of the paper is as follows:
Annotation Modeling with Formal Ontologies:
Implications for Informal Ontologies
L. I. Lumb, J. R. Freemantle, J. I. Lederman & K. D.
 Computing and Network Services, York University, 4700 Keele Street,
Toronto, Ontario, M3J 1P3, Canada
 Earth & Space Science and Engineering, York University, 4700 Keele
Street, Toronto, Ontario, M3J 1P3, Canada
Knowledge representation is increasingly recognized as an important component of any cyberinfrastructure (CI). In order to expediently address scientiﬁc needs, geoscientists continue to leverage the standards and implementations emerging from the World Wide Web Consortium’s (W3C) Semantic Web effort. In an ongoing investigation, previous efforts have been aimed towards the development of a semantic framework for the Global Geodynamics Project (GGP). In contrast to other efforts, the approach taken has emphasized the development of informal ontologies, i.e., ontologies that are derived from the successive extraction of Resource Description Format (RDF) representations from eXtensible Markup Language (XML), and then Web Ontology Language (OWL) from RDF. To better understand the challenges and opportunities for incorporating annotations into the emerging semantic framework, the present effort focuses on knowledge-representation modeling involving formal ontologies. Although OWL’s internal mechanism for annotation is constrained to ensure computational completeness and decidability, externally originating annotations based on the XML Pointer Language (XPointer) can easily violate these constraints. Thus the effort of modeling with formal ontologies allows for recommendations applicable to the case of incorporating annotations into informal ontologies.
I expect the whole paper will be made available in the not-too-distant future …
In a previous post, I referred to Earth Science Informatics as a discipline-in-the-making.
To support this claim, I cited a number of data points. And of these data points, the 2006 Fall Meeting of the American Geophysical Union (AGU) stands out as a key enabler.
With 22 sessions posted, the 2007 Fall Meeting of the AGU is well primed to further enable the development of this discipline.
Because I’m a passionate advocate of this intersection between the Earth Sciences and Informatics, I’m involved in convening three of the 22 Earth and Space Science Informatics sessions:
- Ontology Integration: A Pressing Challenge for Earth and Space Science Informatics
- Grid Technologies and Associated Infrastructures
- Putting Ontologies to Work: Real-World Applications in the Earth and Space Sciences
I encourage you to take a moment to review the calls for participation for these three, as well as the other 19, sessions in Earth and Space Science Informatics at the 2007 Fall Meeting of the AGU.
From the purely scientific (ozone-column mapping, imaging hydrometeors in clouds) to commercial (on-board detection of clear air turbulence, CAT), my exposure to LIDAR applications has been primarily atmospheric.
Of course, other applications of LIDAR technology exist, and one of these is Digital Terrain Mapping (DTM).
Terra Remote Sensing Inc. is a leader in LIDAR-based DTM. Particularly impressive is their ability to perform surface DTM in areas of dense vegetation. As I learned at a very recent meeting of the Ontario Association of Remote Sensing (OARS), Terra has already found a number of very practical applications for LIDAR-based DTM.
Some additional applications that come to mind are:
- DTM of urban canopies for atmospheric experiments – Terra has already mapped buildings for various purposes. The same approach could be used to better ground (sorry 😉 atmospheric experiments. For example, the boundary-layer modeling that was conducted for Joint Urban 2003 (JU03) employed a digitization of Oklahoma City. A LIDAR-based DTM would’ve made this an even-more realistic effort.
- Monitoring the progress of Global Change in the Arctic – In addition to LIDAR-based DTM, Terra is also having some success characterizing surfaces based on LIDAR intensity measurements. Because open water and a glacier would be expected to have different DTM and intensity characteristics, Terra should also be able to monitor Global Change as nunataks are progressively transformed into traditional islands (land isolated and surrounded by open water). With the Arctic as a bellwether for Global Change, it’s not surprising that the nunatak-to-island transformation is getting attention.
Although my additional examples are (once again) atmospheric in nature, as Terra is demonstrating, there are numerous applications for LIDAR-based technologies.
Working with co-authors Jerusha Lederman, Jim Freemantle and Keith Aldridge, a written version of the recent AGU presentation has been prepared and submitted to the HPCS 2007 event. The abstract is as follows:
Semantically Enabling the Global Geodynamics Project:
Incorporating Feature-Based Annotations via XML Pointer Language (XPointer)
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, identifications, or some other source. In order to account for features in an ESML context, they are considered from the perspective of annotation. Although it is possible to extend ESML to incorporate feature-based annotations internally, there are complicating factors identified that apply to ESML and most XML dialects. Rather than pursue the ESML-extension approach, an external representation for feature-based annotations via XML Pointer Language (XPointer) is developed. 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). Application of this same requirement to XPointer-based annotations of ESML representations results in a revised semantic framework for the Global Geodynamics Project (GGP).
Once the paper is accepted, I’ll make a pre-submission version available online.
Because the AGU session I participated in has also issued a call for papers, I’ll be extending the HPCS 2007 submission in various interesting ways.
And finally, thoughts are starting to gel on how annotations may be worked into the emerging notions I’ve been having on knowledge-based heuristics.
I’m still reading Cloninger’s book, and just read a section on Generative Software (GS) – software used by contemporary designers to “… automate an increasingly large portion of the creative process.” As implied by the name, GS can produce a tremendous amount of output. It’s then up to the designer to be creatively stimulated as they sift through the GS output.
As I was reading Cloninger’s description, I couldn’t help but make my own connections with Genetic Algorithms (GAs). I’ve seen GAs applied in the physical sciences. For example, GAs can be used to generate models to fit data. The scientist provides an ancestor (a starting model), and then variations are derived through genetic processes such as mutation. Only the models with appropriate levels of fitness survive subsequent generations. Ultimately, what results is the best (i.e., most fit) model that explains the data according to the GA process.
In an analogous way, this is also what happens with the output from GS. Of course, in the GS case, it is the designer her/himself who determines what survives according to their own criteria.
The GS-GA connection is even stronger than my own association may cause you to believe.
At one point, you talked about creating software that would parse through the output of your generative software and select the iterations you were most likely to choose.
That’s something [programmer] Branden Hall and I worked on called Genetic Aesthetic. It uses a neural network and genetic algorithms to create a “hot or not” situation. It says, “Rate this composition I generated on a scale from 1 to 10.” If I give it a 1, it says, “This isn’t beautiful. I should look at what kind of numbers were generated in this iteration and record those as unfavorable.” You have to train the software. Because the process is based on variables and numbers, over a very short period of time it’s able to learn what numbers are unsatisfactory and what numbers are satisfactory to that individual human critic. It changes per individual.
That certainly makes the GS-GA connection explicit and poetic, Genetic Aesthetic – I like that!
I’ve never worked with GAs. However, I did lead a project at KelResearch where our objective was to classify hydrometeors (i.e., raindrops, snowflakes, etc.). The hydrometeors were observed in situ by a sensor deployed on the wing of an airplane. Data was collected as the plane flew through winter storms. (Many of these campaigns were spearheaded by Prof. R. E. Stewart.) What we attempted to do was automate the classification of the hydrometeors on the basis of their shape. More specifically, we attempted to estimate the fractal dimension of each observed hydrometeor in the hopes of providing at automated classification scheme. Although this was feasible in principle, the resolution offered by the sensor made this impractical. Nonetheless, it was a interesting opportunity for me to personally explore the natural Genetic Aesthetics afforded by Canadian winter storms!
Perhaps two years ago, it was a challenge to find appropriate sessions at the American Geophysical Union Fall Meeting for submissions that addressed the intersection between geophysics and knowledge representation.
A year ago, there were quite a few to choose from.
This year, I was almost overwhelmed by choice.
I ended up selecting the “Earth and Space Science Cyberinfrastructure: Application and Theory of Knowledge Representation” session in the “Earth and Space Science Informatics” section. The work I intend to present, co-authored with Jerusha Lederman and Keith Aldridge also of York University, is described via an abstract elsewhere. I’ll need to prepare well as I’m presenting in good company and have only 15 minutes!
The makings for a productive and stimulating meeting are clearly present.
And for a Canadian in December, it’s pretty difficult not to enjoy the Bay Area!