Graphic depicting a data gap.

Hidden Data – The Ownership Gap in Hydrometry

A globally diverse group of hydrometric practitioners is forming for an open discussion around the question of hidden hydrometric data. If you would like to be part of this conversation please sign up on the post ‘Closing the Gap in Hydrometric Data.’

Many of the responses to the post are focused on standards and technological barriers to data sharing. However, it is entirely possible that emerging technology will do little to change the volume of hydrometric data that is searchable, discoverable, and accessible.

Technology will only help if the owners of the data are motivated to share but lack the means to do so.

This is the way things played out with geospatial data where recent advances in standards and enabling technologies resulted in incredible increase in the relevance and utility of geospatial data across a broad spectrum of social, environmental, and economic need.

I am not so sure that the many and various owners of ‘hidden’ hydrometric data are at all motivated to share. Furthermore, these owners are at arm’s length from the enabling technologies. Unlike the model of success provided by sharing of geospatial data, a substantial portion of hidden hydrometric data is distributed under a ‘heavy tail.’

Hydrometric data owners in the head of the distribution are primarily government agencies that are funded by the public and hence public good oriented. Data owners in the tail of the distribution tend to be either profit-oriented or risk-oriented. Once the opportunity to either generate profit or avoid risk has passed, they are not motivated nor rewarded for sharing that data to contribute to a greater public good by making it available for re-use.

Heavy tail data owners typically have expertise in a domain other than hydrology.

By way of example, the core competency of the mining industry is in turning selected portions of the earth’s crust into dust from which minerals can be extracted. Every aspect of their business model involves water. Therefore they need water data to be profitable and they need water data to avoid risk.

There is no motivation to contribute to a public good by sharing their data. Arguably, data sharing can hurt profitability by exposing the operational risks being taken to maximize quarterly profits to both regulators and shareholders.

Precisely because hydrology is not their core competency, companies typically outsource the data collection to private contractors. These contractors have the skill and ability to use emergent standards and technologies to enable data sharing, but their hands are tied because they do not own the data. These contractors are also profit-oriented and hence have little motivation to promote a data sharing ethic amongst their clients. If client ‘A’ shares their data then client ‘B’ gets it for free, hence will not pay the contractor for gauging the same stream twice.

Rather than mining I could have used hydro, transportation, water supply, agriculture, forestry, oil and gas, or fisheries as an example of how the disconnect between ownership and production of hydrometric data is the real barrier to exposing hidden hydrometric data, not the availability of standards and technologies.

I hope I am wrong.

Whether you agree with me or not, I would like to hear from you about the potential for expanding the global hydrometric data pool of assets.

How can organizations in the long tail be rewarded or motivated to share their water data? Read ‘Closing the Gap in Hydrometric Data.’

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