Developing an organizational data strategy that aligns with your mission requires thinking about how different people interact with data over time.

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The lifecycle of digital data is iterative and cyclical not linear. Click below to see details for each stage of the data lifecycle.
Collect

Data Lifecycle Decisions: Collection

Technology

  • Are the data being collected passively or actively (through crowdsourcing, e.g.)?
  • Are they being collected through structured mechanisms such as surveys or interviews?
  • When do OS defaults need to be changed (location, ID numbers, etc.)?

Governance

  • Are the sources of the data giving active consent to have their information gathered?
  • What rights are contained within that consent?
  • If information is being collected passively, what rights do people have to correct or remove their data?
  • Under what circumstances is Personally Identifiable Information (PII) collected?

Management

  • Communicate and implement data ownership and confidentiality conditions
Analyze

Data Lifecycle Decisions: Analysis

Technology

  • Where is the analysis done and how is it done?
  • Will the raw data be shared for additional external analysis?

Governance

  • If expertise will be required for analysis, how will this expertise be determined?
  • Will the raw data be shared for additional external analysis?

Management

  • How will analysis be shared?
Store

Data Lifecycle Decisions: Storage

Technology

  • Where will data be stored – In the cloud? Onsite?
  • What security/encryption protections are needed?
  • With iterations of data, how often are the data stores updated?
  • Are multiple datasets required for data protection/anonymization?
  • Will they be stored separately?

Governance

  • What types of data need to be redacted, anonymized, removed?
  • Is encryption needed?

Management

  • How will redactions/anonymization choices influence data use, validity, and sharing?
  • How will these decisions be communicated during collection process?
Access

Data Lifecycle Decisions: Access and Sharing

Technology

  • What security/firewall systems are necessary for providing external access to data?

Governance

  • Will users have free access to raw data? To analysis?
  • If there is a price how will it be determined and charged?
  • Are there licenses needed?
  • Will data be shared with full rights to manipulate and re-share?
  • What liability protections are in place regarding external use/analysis
  • Are data accessible all the time or only one-time?

Management

  • Who will manage licensing process and monitor use/analysis/external use?
Secure

Data Lifecycle Decisions: Security

Technology

  • How will data be protected – from what and where?
  • What backup process will be used for which data sets?

Governance

  • Are all data sets protected under same guidelines?
  • When are exceptions made?
  • What steps are in place in case of data breaches?

Management

  • Determine protection level required and implement appropriate steps.
Destroy

Data Lifecycle Decisions: Destruction

Technology

  • What systems are necessary to ensure data destruction?

Governance

  • How do retention/destruction policies align with mission and perceived risks?

Management

  • Implement necessary timelines for data destruction and communicate these as part of data collection/analysis process.

Information experts and specialists, like librarians, know a lot about managing information and data. Here’s a simplified version of the many steps involved in a professional process.

At each step in the lifecycle there are several layers of decisions and decision makers:

  • Technology
  • Governance (including communications)
  • Management