The strategy involves creating sandbox datasets and researching privacy-preserving technologies. The first part focuses on building and evaluating sandbox datasets. This includes identifying key data attributes, collecting raw data, anonymizing it to protect privacy, and filling gaps with synthetic data. For example, raw data from social media can be anonymized and supplemented with synthetic data to ensure privacy.
The second part of the strategy involves implementing and testing privacy-preserving technologies. This starts with identifying leading technologies, collaborating with experts, and selecting appropriate ones for your datasets. These technologies are then rigorously tested in controlled environments. Feedback is gathered and utilized to refine these technologies, ensuring their effectiveness.
The final part focuses on researching and developing new methodologies. This includes conducting a literature review, identifying gaps, formulating new models, and collaborating with industry experts. Prototypes are developed and tested, and findings are published to contribute to the academic and professional community. For instance, new anonymization techniques might be developed and validated in sandbox environments before being applied to real-world data.
The strategies
⛳️ Strategy 1: Build and evaluate sandbox datasets
- Identify key data attributes for sandbox datasets
- Collect raw data from diverse sources
- Anonymise data using established privacy techniques
- Create synthetic data to fill gaps in raw data
- Validate the accuracy and utility of the synthetic data
- Develop metrics to evaluate dataset privacy and utility
- Implement regular reviews to ensure data currency
- Collaborate with experts for dataset validation
- Document data sources and anonymisation processes
- Make sandbox datasets accessible to researchers
⛳️ Strategy 2: Implement and test privacy-preserving technologies
- Identify leading privacy-preserving technologies in the field
- Collaborate with tech experts to understand these technologies
- Select appropriate technologies for your datasets
- Implement chosen technologies in controlled environments
- Conduct rigorous testing to evaluate effectiveness
- Gather feedback from users and stakeholders
- Update and refine technologies based on feedback
- Document the testing process and outcomes
- Provide training to team members on these technologies
- Present findings in professional forums and conferences
⛳️ Strategy 3: Research and develop new privacy-preserving methodologies
- Conduct a literature review on existing methodologies
- Identify gaps and areas needing innovation
- Formulate hypothetical models for new methodologies
- Collaborate with academic and industry experts
- Seek funding for exploratory research
- Develop prototypes of the new methodologies
- Test and validate prototypes in sandbox environments
- Gather and analyse data from real-world scenarios
- Publish findings in academic journals
- Continue iterative development based on research outcomes
Bringing accountability to your strategy
It's one thing to have a plan, it's another to stick to it. We hope that the examples above will help you get started with your own strategy, but we also know that it's easy to get lost in the day-to-day effort.
That's why we built Tability: to help you track your progress, keep your team aligned, and make sure you're always moving in the right direction.
Give it a try and see how it can help you bring accountability to your strategy.
