Smart Technologies for Emergency Response and Disaster Management by Zhi Liu Kaoru Ota

Author:Zhi Liu,Kaoru Ota
Language: eng
Format: epub
Publisher: IGI Global

Table 3. DQ diamensions

Intrinsic

dimensions Contextual

Dimensions Representational

Dimensions Accessibility

Dimensions

Believability

Accuracy

Objectivity

Reputation Value-added

Relevance

Completeness

Timeliness

Appropriate amount

of data Interpretability

Ease of

understanding

Representational

Consistency

Concise

representation Accessibility

Access security

In our research, we are analysing prominent frameworks and develop a DQ assessment technique and reconciliation concept for emergency information. This allows us to assign numerical or categorical values to DQ criteria for information and then subsequently select and prioritise information accordingly to the specific emergency situation. The assessment of the quality of the content in social media adds a significant layer of complexity over traditional DQ assessment frameworks. Challenges arise in timing issues and evaluating the trustworthiness, completeness and accuracy of the quality of content that has been created by users from different backgrounds, in different situations and for different domains.

5.6. Data Visualization for Emergency Decision Support

There are several kinds of visualization techniques25 for complex – or even SM datasets: simple lists, spatial and temporal representations or charts and graph-based visualizations. The high-level visualization applies very restrictive filters to keep the amount of data as small as possible. The low-level visualization provides a more detailed view on the data.

In our ongoing research project we are tackling aforesaid concerns, with the help of the proposed IT-system the connection between citizens and emergency Services will be enhanced.

6. CONCLUSION

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