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

Molina M, Sanchez-Soriano J, Corcho O - Sensors (Basel) (2015)

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: Department of Artificial Intelligence, Technical University of Madrid, Campus de Montegancedo S/N, 28660 Boadilla del Monte, Madrid, Spain. martin.molina@upm.es.

ABSTRACT
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.

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Related in: MedlinePlus

Generated text describing a hydrologic situation (translated from Figure 2).
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sensors-15-16009-f003: Generated text describing a hydrologic situation (translated from Figure 2).

Mentions: Figure 2 shows an example of a presentation generated by the VSAIH system (in Spanish) and Figure 3 shows the text translation. The presentation includes a journalistic text description with a headline and body text along with some interactive graphics (maps, charts, animations, etc.). The practical evaluation of VSAIH [11] showed that these type of descriptions are able to facilitate decision-making and save critical time in special emergency scenarios.


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

Molina M, Sanchez-Soriano J, Corcho O - Sensors (Basel) (2015)

Generated text describing a hydrologic situation (translated from Figure 2).
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4541865&req=5

sensors-15-16009-f003: Generated text describing a hydrologic situation (translated from Figure 2).
Mentions: Figure 2 shows an example of a presentation generated by the VSAIH system (in Spanish) and Figure 3 shows the text translation. The presentation includes a journalistic text description with a headline and body text along with some interactive graphics (maps, charts, animations, etc.). The practical evaluation of VSAIH [11] showed that these type of descriptions are able to facilitate decision-making and save critical time in special emergency scenarios.

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: Department of Artificial Intelligence, Technical University of Madrid, Campus de Montegancedo S/N, 28660 Boadilla del Monte, Madrid, Spain. martin.molina@upm.es.

ABSTRACT
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.

No MeSH data available.


Related in: MedlinePlus