Using Open Geographic Data to Generate Natural Language Descriptions for Hydrological Sensor Networks

Providing descriptions of isolated sensors and sensor networks in natural language, understandable by the general public, is useful to help users find relevant sensors and analyze sensor data. In this paper, we discuss the feasibility of using geographic knowledge from public databases available on the Web (such as OpenStreetMap, Geonames, or DBpedia) to automatically construct such descriptions. We present a general method that uses such information to generate sensor descriptions in natural language. The results of the evaluation of our method in a hydrologic national sensor network showed that this approach is feasible and capable of generating adequate sensor descriptions with a lower development effort compared to other approaches. In the paper we also analyze certain problems that we found in public databases (e.g., heterogeneity, non-standard use of labels, or rigid search methods) and their impact in the generation of sensor descriptions.

[1]  Jim Hunter,et al.  Choosing words in computer-generated weather forecasts , 2005, Artif. Intell..

[2]  Martin Molina,et al.  Modeling Sensor Knowledge of a National Hydrologic Information System , 2010, SSW.

[3]  Michael Strube,et al.  Modeling Spatial Knowledge for Generating Verbal and Visual Route Directions , 2011, KES.

[4]  Albert Gatt,et al.  Using Natural Language Generation Technology to Improve Information Flows in Intensive Care Units , 2008, ECAI.

[5]  Ehud Reiter,et al.  Generating Approximate Geographic Descriptions , 2009, ENLG.

[6]  John D. Kelleher,et al.  A Context-dependent Algorithm for Generating Locative Expressions in Physically Situated Environments , 2005, ENLG.

[7]  Claire Gardent,et al.  Generating Minimal Definite Descriptions , 2002, ACL.

[8]  John Nerbonne,et al.  Reference to Locations , 1989, ACL.

[9]  Ehud Reiter,et al.  Book Reviews: Building Natural Language Generation Systems , 2000, CL.

[10]  Anette Frank,et al.  A NLG-based Application for Walking Directions , 2009, ACL/IJCNLP.

[11]  Douglas E. Appelt,et al.  A Computational Model of Referring , 1987, IJCAI.

[12]  References , 1971 .

[13]  Tim Berners-Lee,et al.  Linked Data - The Story So Far , 2009, Int. J. Semantic Web Inf. Syst..

[14]  Martin Molina,et al.  GENERATING TEXT DESCRIPTIONS FOR GEOGRAPHICALLY DISTRIBUTED SENSORS , 2011 .

[15]  Asunción Gómez-Pérez,et al.  GeoLinked data and INSPIRE through an application case , 2010, GIS '10.

[16]  Robert Dale,et al.  Computational Interpretations of the Gricean Maxims in the Generation of Referring Expressions , 1995, Cogn. Sci..

[17]  Martin Molina,et al.  Generating multimedia presentations that summarize the behavior of dynamic systems using a model-based approach , 2012, Expert Syst. Appl..

[18]  Martin Molina,et al.  Simulating Data Journalism to Communicate Hydrological Information from Sensor Networks , 2012, IBERAMIA.

[19]  Douglas E. Appelt,et al.  Planning English Referring Expressions , 1985, Artif. Intell..

[20]  John Davidson,et al.  Ogc® sensor web enablement:overview and high level achhitecture. , 2007, 2007 IEEE Autotestcon.

[21]  George Percivall,et al.  Ogc® sensor web enablement:overview and high level achhitecture. , 2007 .

[22]  Emiel Krahmer,et al.  Graph-Based Generation of Referring Expressions , 2003, CL.