Pedro Szekely
Craig A. Knoblock
Shubham Gupta
ABSTRACT
Using today's GIS tools, users without programming expertise are unable to fully exploit the growing amount of geospatial data becoming available because today's tools limit them to displaying data as layers for a region on a map. Fusing the data in more complex ways requires the ability to invoke processing algorithms and to combine the data these algorithms produce in sophisticated ways. Our approach, implemented in a tool called Karma, encapsulates these algorithms as Web services described using semantic models that not only specify the data types for the inputs and outputs, but also specify the relationships between them. Karma semi-automatically builds these models from sample data and then uses these models to provide an easy to use interface that lets users seamlessly implement workflows that combine and process the data in sophisticated ways.
- Chen, C. C., Knoblock, C. A., Shahabi, C.: Automatically and accurately conflating raster maps with orthoimagery. Geoinformatica 12, 377--410 (2008) Google Scholar
Digital Library
- Chiang, Y. Y., Knoblock, C. A., Shahabi, C., Chen, C. C.: Automatic and accurate extraction of road intersections from raster maps. Geoinformatica 13(2), 121--157 (2008), http://dx.doi.org/10.1007/s10707-008-0046-3 Google ScholarDigital Library
- Di, L., Zhao, P., Yang, W., Yue, P.: Ontology-driven automatic geospatial-processing modeling based on web-service chaining. In: Proceedings of the Sixth Annual NASA Earth Science Technology Conference (2006)Google Scholar
- Goel, A., Knoblock, C. A., Lerman, K.: Using conditional random fields to exploit token structure and labels for accurate semantic annotation. In: Proceedings of AAAI 2011 (2011)Google Scholar
- Gonzalez, H., Halevy, A., Jensen, C. S., Langen, A., Madhavan, J., Shapley, R., Shen, W.: Google fusion tables: data management, integration and collaboration in the cloud. In: Proceedings of the 1st ACM symposium on Cloud computing. pp. 175--180. SoCC '10, ACM, New York, NY, USA (2010) Google ScholarDigital Library
- Gupta, S., Knoblock, C. A.: A framework for integrating and reasoning about geospatial data. In: Extended Abstracts of the Sixth International Conference on Geographic Information Science (GIScience) (2010)Google Scholar
- Huynh, D., Mazzocchi, S.: Goole refine. http://code.google.com/p/google-refine/Google Scholar
- Knoblock, C. A., Chen, C. C., Chiang, Y. Y., Goel, A., Michelson, M., Shahabi, C.: A general approach to discovering, registering, and extracting features from raster maps. In: Proceedings of the Conference on Document Recognition and Retrieval XVII of SPIE-IS and T Electronic Imaging. vol. 7534 (2010)Google ScholarCross Ref
- Knoblock, C. A., Lerman, K., Minton, S., Muslea, I.: Accurately and reliably extracting data from the web: A machine learning approach. In: Szczepaniak, P. S., Segovia, J., Kacprzyk, J., Zadeh, L. A. (eds.) Intelligent Exploration of the Web, pp. 275--287. Springer-Verlag, Berkeley, CA (2003) Google ScholarDigital Library
- Knoblock, C. A., Szekely, P., Ambite, J. L., Gupta, S., Goel, A., Muslea, M., Lerman, K., Mallick, P.: Interactively mapping data sources into the semantic web. In: Proceedings of the Workshop on Linked Science (Submitted for review) (2011)Google Scholar
- Krummenacher, R., Norton, B., Marte, A.: Towards linked open services and processes. In: Proceedings of the Third future internet conference on Future internet. pp. 68--77. FIS'10, Springer-Verlag, Berlin, Heidelberg (2010) Google ScholarDigital Library
- Lieberman, H.: Your Wish is My Command: Programming by Example. Morgan Kaufmann, San Francisco (2001)Google Scholar
- Michalowski, M., Knoblock, C. A.: A constraint satisfaction approach to geospatial reasoning. In: Proceedings of the Twentieth National Conference on Artificial Intelligence (AAAI-05) (2005) Google ScholarDigital Library
- Norton, B., Krummenacher, R.: Geospatial linked open services. In: Proceedings of the Workshop Towards Digital Earth: Search, Discover and Share Geospatial Data 2010 (2010)Google Scholar
- Shahabi, C., Banaei-Kashani, F., Khoshgozaran, A., Nocera, L., Xing, S.: Geodec: A framework to visualize and query geospatial data for decision-making. Multimedia, IEEE 17(3), 14--23 (july-september 2010) Google ScholarDigital Library
- Studer, R., Grimm, S., Abecker, A. (eds.): Semantic Web Services: Concepts, Technologies, and Applications. Springer, Berlin, Heidelberg (2007) Google ScholarDigital Library
- Tanasescu, V., Gugliotta, A., Domingue, J., Villarias, L. G., Davies, R., Rowlatt, M., Richardson, M., Stincic, S.: Geospatial data integration with semantic web services: The emerges approach. In: Scharl, A., Tochtermann, K. (eds.) The Geospatial Web, pp. 247--256. Advanced Information and Knowledge Processing, Springer London (2007)Google Scholar
- Tuchinda, R., Szekely, P., Knoblock, C. A.: Building mashups by example. In: Proceedings of the 2008 International Conference on Intelligent User Interface (2008) Google ScholarDigital Library
- Tuchinda, R., Knoblock, C. A., Szekely, P.: Building mashups by demonstration. ACM Transactions on the Web (TWEB) (2011), to appear Google ScholarDigital Library
- Yue, P., Di, L., Yang, W., Yu, G., Zhao, P.: Semantics-based automatic composition of geospatial web service chains. Computers and Geosciences 33(5), 649--665 (2007) Google ScholarDigital Library
- Yue, P., Gong, J., Di, L.: Augmenting geospatial data provenance through metadata tracking in geospatial service chaining. Computers and Geosciences 36(3), 270--281 (2010) Google ScholarDigital Library
- Zhou, Q. Y., Neumann, U.: Fast and extensible building modeling from airborne lidar data. In: Proceedings of the 16th ACM SIGSPATIAL international conference on Advances in geographic information systems. pp. 7:1--7:8. GIS '08, ACM, New York, NY, USA (2008) Google ScholarDigital Library
Index Terms
- Exploiting semantics of web services for geospatial data fusion
Recommendations
A semantic approach to retrieving, linking, and integrating heterogeneous geospatial data
AIIP '13: Joint Proceedings of the Workshop on AI Problems and Approaches for Intelligent Environments and Workshop on Semantic CitiesThere is a tremendous amount of geospatial data available, and there are numerous methods for extracting, processing and integrating geospatial sources. However, end-users' ability to retrieve, combine, and integrate heterogeneous geospatial data is ...
Learning the semantics of structured data sources
Information sources such as relational databases, spreadsheets, XML, JSON, and Web APIs contain a tremendous amount of structured data that can be leveraged to build and augment knowledge graphs. However, they rarely provide a semantic model to describe ...
Enriching the semantics of variational geometric constraint data with ontology
Lack of explicit semantics in the product data to be exchanged among product development systems is a major problem for existing product data exchange standards. To solve this problem, the semantics of product data should be enriched to form a basis for ...
Comments