Exploring Equivalence Metrics to Analyze Behavior in a Naked Mole Rat Colony.

Many statistical and data mining techniques have been used to analyze the deluge of data generated by computerized, sensing devices. Behavioral psychologists traditionally have relied on low-tech methodologies for observing animal behavior in the wild and the laboratory. These methods are time intensive and laborious. When the observed animal is a colony animal, with many individuals to observe, traditional methods fail We inject RFID passive transponders under the skin of our study animal, the Naked Mole-rat (NMR). RFID readers are placed throughout the housing environment, allowing us to track animal movements as they move through these areas, with sub-second resolution for long periods of time. This methodology generates huge amounts of data requiring Big Data analytical techniques. In this paper, we investigate equivalence metrics, specifically the Pearson Correlation Coefficient and Hamming Distance, to analyze behavior changes in the social network structure of a naked mole rat colony. Our results showed that a Pearson Correlation was sufficient to detect equipment error and Hamming Distance could detect changes in colony behavior.