391
33. NASA VIIRS/Night-Lights
34. NASA GRACE Water Storage Anomalies v1
35. USDA NASS Food Cold Storage Reserves
36. WRI Aqueduct
37. US Data.gov
38. US Library of Congress
14.4 Privacy and Ethics Principles for FEW Data
FAIR data management principles are intended primarily for application to public
data, so they must be carefully translated and qualified (but not discarded) for application to private and sensitive data that are only ethically made accessible to a
specific group of qualified users. If data = information = knowledge = power, and if
FEW systems can be manipulated to gain power over people (as they often are!),
then data concerning people’s critical FEW infrastructures and lifelines is both
powerful and dangerous in the wrong hands. There is a great deal of very clear risk,
whereas the benefits of releasing this data are often unclear—or are very clearly not
worth the risk. As a result, in the USA and most other countries the government and
census data repositories containing FEW systems data err on the side of caution by
releasing only heavily aggregated and redacted FEW systems data, or none at all,
and regulations often prevent private companies and nongovernmental organizations from releasing this data. In many other cases, private entities elect not to
release private data unless they are strongly incentivized to do so. This is an ethically defensible, practical, and precautionary choice, but a deeply frustrating one for
FEW systems researchers. Because privacy and ethics are such central considerations in FEW systems data accessibility and research, the student or researcher
must have a grasp of the logic behind these obstacles in order to successfully navigate the metaphorical data landscape.
Data Ethics concerns the determination of right and wrong data practices, especially for sensitive and private data. The conversation on Data Ethics concerns the
ownership of data, transparency over how it is to be used, consent to how it will be
used, privacy and control over privacy of some data, value of the data and knowledge of data transactions, and accessibility of specific types of datasets by specific
types of people or algorithms. Important questions include, for instance, “Who
owns the data on my food, energy, and water use?” “Can I control who knows my
food, energy, and water use and sources?” “If I tell you my food, energy, and water
use, are you allowed to tell others without asking me?” and “Do I have a right to
know how you are using my food, energy, and water data?” Imagine a future where
data science is capable of measuring and predicting almost anything about a person’s needs, choices, and behavior. Should we use that data-driven foresight to prevent people from making harmful choices, or should we allow people to exercise
their own free will for better or worse? And who, if anyone, should possess that
foresight? These are critical questions for the twenty-first century—and for the
twenty-first century’s critical food, energy, and water systems.
14 Data
33. NASA VIIRS/Night-Lights
34. NASA GRACE Water Storage Anomalies v1
35. USDA NASS Food Cold Storage Reserves
36. WRI Aqueduct
37. US Data.gov
38. US Library of Congress
14.4 Privacy and Ethics Principles for FEW Data
FAIR data management principles are intended primarily for application to public
data, so they must be carefully translated and qualified (but not discarded) for application to private and sensitive data that are only ethically made accessible to a
specific group of qualified users. If data = information = knowledge = power, and if
FEW systems can be manipulated to gain power over people (as they often are!),
then data concerning people’s critical FEW infrastructures and lifelines is both
powerful and dangerous in the wrong hands. There is a great deal of very clear risk,
whereas the benefits of releasing this data are often unclear—or are very clearly not
worth the risk. As a result, in the USA and most other countries the government and
census data repositories containing FEW systems data err on the side of caution by
releasing only heavily aggregated and redacted FEW systems data, or none at all,
and regulations often prevent private companies and nongovernmental organizations from releasing this data. In many other cases, private entities elect not to
release private data unless they are strongly incentivized to do so. This is an ethically defensible, practical, and precautionary choice, but a deeply frustrating one for
FEW systems researchers. Because privacy and ethics are such central considerations in FEW systems data accessibility and research, the student or researcher
must have a grasp of the logic behind these obstacles in order to successfully navigate the metaphorical data landscape.
Data Ethics concerns the determination of right and wrong data practices, especially for sensitive and private data. The conversation on Data Ethics concerns the
ownership of data, transparency over how it is to be used, consent to how it will be
used, privacy and control over privacy of some data, value of the data and knowledge of data transactions, and accessibility of specific types of datasets by specific
types of people or algorithms. Important questions include, for instance, “Who
owns the data on my food, energy, and water use?” “Can I control who knows my
food, energy, and water use and sources?” “If I tell you my food, energy, and water
use, are you allowed to tell others without asking me?” and “Do I have a right to
know how you are using my food, energy, and water data?” Imagine a future where
data science is capable of measuring and predicting almost anything about a person’s needs, choices, and behavior. Should we use that data-driven foresight to prevent people from making harmful choices, or should we allow people to exercise
their own free will for better or worse? And who, if anyone, should possess that
foresight? These are critical questions for the twenty-first century—and for the
twenty-first century’s critical food, energy, and water systems.
14 Data