Oleksii @ stock.adobe.com
A tool that enables the sharing of information derived from a data set rather than sharing the actual data itself, thus protecting users' privacy. This technology is a potential solution to make data available to the public while reducing the risk of data misuse, thus becoming a model for providing secure remote access to sensitive data. Data enclave provides a confidential, protected environment in which authorized users could access sensitive data remotely while providing a secure dissemination platform. It is implemented as a cloud-based platform that replaces on-premise infrastructure and provides both the safe storage of datasets and scalable computing resources that operate on data by separating the data from the user's physical desktop computer.
By valuing the privacy of each individual, data enclaves ensure a higher rate of data adaption to machine learning and research, thus improving datasets and allowing deep insights without compromising individuality. This is useful to separate the personal identity from the data itself, which allows institutions from healthcare to educational and social sectors to maintain secure access to highly sensitive datasets while also helping centralize geographically dispersed teams.
Gender research involves complex social-economic concepts that might challenge the employment of usual big data approaches.
There are real ethical risks associated with making small scale data too widely accessible, to the extent that the people concerned in any data set can be recognized and tracked down.
Promote awareness about sensitive data privacy and security laws through a safety network among governments, institutions, collectives, and local communities.
Integrate gender research perspectives into big data opportunities.
Unlock new and smarter ways of understanding the causes of gender inequality and of identifying ways to address it by harnessing the potential of big data.