Hello

Who are you?
What do you do?
What was your first experience of open data?
What do you hope to get out of the training?

Open Data in a Day

Dr David Tarrant | Benjamin Cave · @davetaz | @cave_ben

Today

Introducing Open Data
Law, licensing and best practice
Making open data work for you

Aim: Introducing open data

Provide a good foundation in the principals of open data and key examples of impact.

Outcomes

Define open data
Describe a number of key open data stories
Evaluate the challenges facing open data
Understand the future of open data globally

Exercise

What is Data?

5 minutes

Definition of Data (1)

A collection of facts, information and statistics that can be analysed to develop new knowledge

Definition of Data (2)

A collection of numbers assigned as values to quantitative variables and/or characters assigned as values to qualitative variables

Definition of Data (3)

The lowest level of abstraction from which information and then knowledge are derived.

Data: Information without context

Exercise

What is Open Data?

3 minutes

Definition of Open (OKF)

A piece of data or content is open if anyone is free to use, reuse, and redistribute it - subject only, at most, to the requirement to attribute and/or share-alike.

- Summary of Open Definition (v1.0)

Retired August 2014

ODI (Version 1)

Open data is information that is available for anyone to use, for any purpose, at no cost.

- Open Data Institute FAQ

Retired November 2014

Summary definition of Open (OKF)

Open means anyone can freely access, use, modify, and share for any purpose (subject, at most, to requirements that preserve provenance and openness).

- Summary of Open Definition (v2.0)

Introduced August 2014

The ODI

DOpen data is data that is made available by organisations, businesses and individuals for anyone to can access, use and share.

- Open Data Institute FAQ

data.gov.uk

Open data is data that is published in an open format, is machine readable and is published under a license that allows for free reuse.

- data.gov.uk

Outcomes

Define open data
Describe a number of key open data stories
Evaluate the challenges facing open data
Understand the future of open data globally

Data is the raw material of the new industrial revolution
- Francis Maude, UK MP

Justifications

Left wing	Right wing
Trust and Transparency	Enabling the economy

Key Stories

Enabling transparency
Creating an income stream
Cutting costs
Improving services
Saving our planet

Exercise

Enabling transparency
Creating an income stream
Cutting costs
Improving services
Saving our planet

In your groups, list your favorite open data stories.

Bonus points for one in each area!

What can open data do for you? from Open Data Institute on Vimeo.

Enabling transparency

Income

Cutting costs

Open Data found a £200m saving in the NHS budget

Improving services

trains Helps us get from A to B quicker

Open data can help make decision that affect our safety

Show quote

Impact and communication

OpenStreetMap - Project Haiti from ItoWorld on Vimeo.

Saving our planet

Outcomes

Define open data
Describe a number of key open data stories
Evaluate the challenges facing open data
Understand the future of open data globally

Govlab: What's in a name?

Credit: Thomas Levine

Credit: Thomas Levine

Credit: Thomas Levine

Exercise

What are the 3 main challenges in your organisation?

5 minutes

Challenges and Risks

Image Credit: Ulrich Atz

There is often confusion about the relationship between big data, open data, and personal data. This slide helps clarify the following points: all three topics are related but only partially overlap. For example, if we look at all the data sets that could be classified as big data, only some of them will have an open license. Similarly, if we think about the intersection of open and personal data, most of the personal data will not be available under an open license. To be really clear about this, I could choose to publish some of my personal data under an open license, but this will probably always be the exception. To restate that in simple terms, most open data will not be personal, and most personal data will not be open. Similarly, most big data will not be personal, and most personal data will not be big. However, over time there will likely be more and more personal data sets that are so big they justify the label of big data, for example, there is a trend known as the quantified self, where people increasingly capture data about themselves and their lives. If some of these big and personal data sets were published under an open license then they would occupy this central area of the Venn diagram.

Types of personal data

Open personal data

Data about people, not a person.

Available to anyone

Has been anonymised

e.g. number of people attending an event, gender split, age ranges. Bigger numbers are better.

Available personal data

Data about a person

Available to the person only!

Often known as MiData

e.g. credit scores, energy consumption and spending.

Closed personal data

Data about a person which is neither open or available

Might belong to you or be collected by a company