RESPONSIBLE DATA GUIDELINES: Managing Privacy and Personally Identifiable Information

Data can be either useful or perfectly anonymous, but never both...” Paul Ohm – UCLA Law review 2010 57 UCLA L. Rev. 1701).

 

The CGIAR (the world's largest global agricultural innovation network) Team has published Responsible Data GUIDELINES: Managing Privacy and Personally Identifiable Information in the Research Project Data Lifecycle  intended to assist agricultural researchers handle privacy and PII (personally identifiable information) in the research project data lifecycle

These Guidelines are voluntary and aspirational in nature, intended as an aid for responsible decision making, not as a substitute for it. Agricultural Researchers need to be pragmatic in striking a balance between privacy protection and open data in order to maximize the benefits in agronomy and international development offered by the ‘big data revolution’, while minimizing the potential for social or personal harm.

RESPONSIBLE DATA MANAGEMENT ON THE CGIAR PLATFORM FOR BIG DATA IN AGRICULTURE 

The CGIAR Platform for Big Data in Agriculture:

  • advocates open data for agricultural research for development and considers that opening up research data (on a FAIR basis; making data findable, accessible, interoperable and reusable) for scrutiny and reuse confers significant benefits to society. FAIR principles does not mean all research data should open since a broad range of legitimate circumstances may require data to be restricted;
  • promotes responsible data management through the entire research data lifecycle from planning, collecting, storing, disclosing or publishing, transferring, discovery and archiving. This requires ongoing due diligence regarding legal, ethical and regulatory frameworks and disciplinary norms, in ways that maximize data trust and value, while minimizing risk.

To become familiar with key concepts around responsible data management such as:

  • Personally identifiable information (PII)
  • Research ethics
  • Informed Consent
  • Compliance
  • Privacy by design and data minimization
  • Privacy protection and data security
  • Data subject rights

as welll as with 10 Guiding Principles designed to assist researchers throughout the Research Project Data Lifecycle and with do’s and don’ts concerning PII in the context of the Research Project Data Lifecycle that includes: 

  • PLANNING AND APPROVAL
  • COLLECTION
  • STORAGE & ANALYSIS
  • REUSE / TRANSFER 
  • ARCHIVING / DISCARDING 
  • PUBLISHING & DISCOVERY 

and real use-cases from Ag Data Transparent, The UK Anonymisation Decision-making Framework, Tool to Anonymize Data Containing Personally Identifiable Information available on CRAN repository, Building Ethics into Privacy Frameworks for Big Data and AI (Global Pulse), 

YOU ARE INVITED TO ACCESS

CGIAR Responsible Data Guidelines: Managing Privacy and Personally Identifiable Information in the Research Project Data Lifecycle.

These Guidelines are not meant to be exhaustive; so if you have other tips, resources, comments to add, please send comments to bigdata@cgiar.org.

RESEARCH DATA- RELATED: 

From debate about FAIR and Open Data to greater exploratory research, constructive discussions and solutions based on interoperable data in the agri-food and related sectors (highlights of the RDA IGAD outputs/recommendations)

You are invited to Sign up for AIMS News, follow @AIMS_Community on Twitter... And, thanks again for your interest! 


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