Information value mapping for fusion architectures

Peterson, T.W.; Sundareshan, Malur K.

doi:10.1109/ific.2000.862471

Cited by 2 publications

(2 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Eight papers were identified as applying data value to sensor deployment or communication and monitoring systems. Topics discussed include a sensing system for earth sciences like satellites [61], environmental monitoring such as lake water quality [53], livestock production [88], sensor fusion architectures [58] and vehicular networks [51]. Many of the papers make use of the Value of Information (VoI) measure discussed above.…”

Section: ) Sensors and Monitoringmentioning

confidence: 99%

“…Thus, utility-based VoI models dominate. However, for monitoring system deployment scenarios [61], [25], [88] economic benefits are also important as the decision is a longer term one about investment rather than short-term automated decision about mobile sensor movement [69], data stream selection [58], message transmission [51], or data storage [87].…”

Section: ) Sensors and Monitoringmentioning

confidence: 99%

See 1 more Smart Citation

A Systematic Survey of Data Value: Models, Metrics, Applications and Research Challenges

Bendechache,

Attard,

Ebiele

et al. 2023

IEEE Access

View full text Add to dashboard Cite

Data is central to modern decision making and value creation. Society creates, consumes and collects data at an increasing pace. Despite advances in processing power, data is expensive to maintain and curate. So, it is imperative to have methods and tools to distinguish between data based on its value. Yet, there is no consensus on what characterises the value of data or how this data value should be assessed. This results in heterogeneous data value models and inconsistent measurement techniques that are siloed in specific application domains. This limits the formalisation and exploitation of these concepts. We present in this paper a methodical literature analysis that discusses data value models, assessment metrics and current applications. We also highlight challenges hindering the development and exploitation of data value as concept. This leads to the identification of a set of research questions to help researchers contribute to this emerging field. The aim of this article is to stimulate further research and deployment of quantitative data value models and value-driven applications.

show abstract