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Introduction to data management, part 1

Nau mai, haere mai and welcome to the second in the series of e-learnings about data and its management. This e-learning is focused on the management of data via a plan.

Learning outcomes

  • Learn what a data management plan (DMP) is and why it is important.
  • Understand the lifecycle of a dataset and where a DMP fits in.
  • Learn the parts of a good DMP by completing your own one.

This e-learning is available as an interactive PDF file and in HTML (below).

Introduction to data management, part 1 e-learning [PDF 1.2 MB]

How long it will take will depend on your own level of knowledge, but put aside about 30 minutes to work through the e-learning and then between 1-4 hours to complete your data management plan. There is no assessment attached.

 

Am I in the right place?

The intended audience for this e-learning is:

  • NZ government departments
  • NZ not-for-profit organisations
  • iwi and Māori organisations.

The content is for those who are new to data management.

It is assumed you understand basic data terms. If you are unsure, please look at the Introduction to data e-learning.

Introduction to data (e-learning)

There is no assessment at the end of this e-learning.

What can I expect from this e-learning?

This e-learning will help you:

  • understand the lifecycle of a dataset
  • learn what a data management plan (DMP) is and why it is important
  • learn the parts of a good data management plan
  • complete your own basic plan
  • know where to go next for more information or help.

What is the lifecycle of data?

Data has a lifecycle: collect > describe > store short-term > analyse and check > use > save or destroy.

Data management is a way of (positively) influencing how your data moves through this cycle.

A data management plan documents all the information and decisions made about the data. 

The components of the data lifecycle.

Why manage data?

Demand: the increased demand for evidence-based decision-making has increased the demand for data. The uses for data are also rapidly changing, requiring more versatility.

Transparency and security: if people are going to continue to provide data, they need to know organisations are taking good care of it.

Use and re-use: data has the potential to be used more than once, and not just for one purpose. This means the ‘metadata’ (which describes and gives the context for the data) is as important as the actual data.

Legislative requirements: the Public Records Act (2005) requires that all data collected as part of government business is managed, until it is archived or destroyed.

Data management is like running a library

Data management plan (DMP): provides the big picture view and records how a dataset moves through its lifecycle.
This is like the library's architectural plans and its strategy.

Datasets: the building blocks that will create statistics, maps, mobile apps etc.
This is like the books in the library.

Metadata: the description of and information about the datasets.
This is like the library's catalogue entries.

Statistics: the interpretation of the data. These results will be different if any of the parts are altered.
This is like the creativity, knowledge, and development that comes from reading the book.

What do I need to know about DMPs?

A good data management plan (DMP):

  • manages the dataset as well as describes (give information about) it
  • is a gateway to everything to do with the dataset. It must be clearly linked to the dataset, the metadata and any other relevant documents/ records. If the dataset is small, the plan may even contain the metadata about the dataset.
  • should always be put in place, even if sometimes this means adding it in order to manage data retrieved from a long-existing system, like a taxation one
  • can apply to more than one dataset if the datasets’ governance and related documentation are the same
  • shows that the data is being handled safely and securely
  • identifies any legislative or contractual requirements for accessing or using the data.

What are the parts of a good DMP?

  • Governance and access
    • Governance
    • Access and security
  • Discovery, use, and re-use
    • Data documentation
    • Data formats, volume, and storage
  • Retention, preservation, and disposal. 

Governance and access

Governance

Governance is about properly looking after the dataset, and applies to both individuals and organisations.

An individual is accountable for their datasets: knowing how to access them, how to keep them secure and how the datasets contribute value inside and outside their organisation.

An organisation is accountable for how it manages its data assets, so they are accessible, secure, usable and re-usable. 

Responsibilities for data management begin with the data creators/collectors. They need to be sure, for example:

  • who will be responsible for the dataset
  • how informed consent will be handled
  • that legislative requirements will be met
  • that relevant principles/frameworks are followed
  • that documents regarding decisions are stored securely and are discoverable and accessible.

The easiest way to make sense of a data management plan is to create one on your own. Open the data management plan template then save the document to your own system. 

Data management plan template [Word 1MB] (Opens new window)

>> Read the instructions on page 1 and then work through the section called Governance (page 3). Once you have finished that section, come back to this e-learning.

Access and security

Access and security are important to those who provide data. We need to be transparent about the openness of data we collect, including access limits:

  • How will we manage security?
  • How will we make sure the data remains uncorrupted?
  • What barriers might there be that would stop sharing?

>> Go back to your plan. Work through the section called Access and Security (page 5) and then come back to this e-learning.

Discovery, use, and re-use

Data documentation

  • Describe how the dataset was extracted or created.
  • Enable use and re-use by explaining what the data items mean.
  • Use consistent names to identify the data through its lifecycle (such as raw, processed, final).

>> Go back to your plan. Work through the section called Data documentation (page 6) and then come back to this e-learning.

The users of any particular dataset do not usually have the opportunity to talk with the creators. So describing the dataset is vital: it means the data can be discovered, used, and potentially re-used.

Data formats, volume, and storage

  • What form will the dataset be kept in?
  • What software is needed to use the dataset?
  • Where is the dataset stored?
  • What is the size of the dataset?

>> Go back to your plan. Work through the section called Data formats, volume and storage (page 7) and then come back to this e-learning.

Retention, preservation, and disposal

Managing datasets well means both creators and users know that the data is being looked after. For example, they know:

  • how long datasets will be kept and how long-term access will be managed
  • how decisions will be made about disposal
  • reviews are scheduled in the data life cycle
  • the final archived data is read-only.

>> Go back to your plan. Work through the section called Retention, Preservation and Disposal (page 8) and then come back to this e-learning.

How do you practically implement a DMP?

Make sure that your data management plan (DMP) is:

  • easily accessible
  • user-friendly
  • easy to maintain.

If your organisation does not have a DMP template, you can use the one in this e-learning, or our Excel-based example.

Data management plan template [Word 1MB]

Data management plan template [Excel 40 KB]

You can find other simple Word or Excel versions online and even software programmes that collect data, put it into a database and create interactive reports.

Where should a DMP live?

All your DMPs should be stored together in a shared location.

Each DMP should clearly link to its datasets, relevant documents, and shared drives as appropriate.

How can I learn more?

  • The Digital Curation Centre at University of Edinburgh provides a good guideline for data management if you would like to explore data management plans more. (Please note, it is research-data focused.) You’ll need to create an account, but it's worth it.

Digital Curation Centre

  • The next introductory module on this website will be Introduction to data management part 2. Keep an eye out!
  • Explore the data.govt.nz website further.
  • Email datalead@stats.govt.nz if you have any questions or feedback.

 


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