Hi Mark,
For the NAB competition we're looking for real-world data only. This is
specified in the first line of the dataset category description:
DATASET CATEGORY
To enter the Dataset category, you must submit real-world, time-series data
with labeled anomalies. Deliverables include:
* Data file(s) in CSV format
* one header row
* fields for "timestamp" (time at the end of the metric collection
window) and "value" (the metric as either float or integer)
* Anomaly labels - timestamps at which the anomalies start
* Description of the data and anomalies
We will evaluate your dataset against the following characteristics:
* meeting the requirements described above
* interesting types of anomalies
* relevance to real applications
* accuracy/quality of anomaly labels
* good challenges for detection algorithms
* quantity of data - the more files in your submission the better
* feasibility for algorithms to detect anomalies
* We can not expect noisy data without temporal patterns to be valuable
in evaluating algorithms, and thus this type of data will not be useful in NAB.
Best,
Alex
