Open Data Flashcards
Define Open Data
Open Data is data that is made available by organisations, businesses and individuals for anyone to access, use and share, without restrictions from copyright, patents or other mechanisms of control.
Paradoxically, the growth of the open data movement is paralleled by a rise in intellectual property rights.
Aiming for transparency and collaboration.
‘Good’ Open Data must be published so that it:
- can be linked to, so it is easily shared and discussed
- is in standard, structured format, so easily processed
- guaranteed availability and consistency over time
- so that others can rely on it
- is traceable, rightback to where it originates
- so others can work out whether to trust it
Open Data & Governments
To maximise the visibility of Open Data, governments (like the EU) have created portals, where Open Data from different agencies are collated for access:
- http://data.europa.eu/euodp/en/data/
In 2011, the EU estimated that Open Data publication could add €40 billion per year to the economy.
Several laws and policies have been introduced since.
Is Open Data in conflict with profits?
- In the Digital Age, economic data depends on data and BI
- data that has been collated, processed and analysed, and sometimes used to create additional new data sources, metrics, or services.
- To be sustainable, organisations need to be able to profitfrom their activities
- this can be achieved through selling proprietary (owned) data in the digital economy
Reasons for organisations to publish open data
Publishing your own Open Data externally (outbound).
- Outbound experimentation: Let potential collaborators or customers experiment with your data, to explore a partnership with you.
- Legal Transparency: Publishing Open Data can address regulatory requirements
- CSR: Supply NGOs and charities with access to your Open Data to assist their missions.
- Support start-ups: free data useful for them.
- ‘Freemium’ opportunities: Free access to your Open Data to attract customers. May charge them if they decide to make heavy/frequent downloads of your data or use ‘value added’ features.
- Low cost growth: Use collaborators with access to your Open Data to develop new apps or websites with no or limited expense to you. They can then pass web traffic and customers directly to you, in exchange for a fee, or pay per click.
- Internationalisation: As above, to attract overseas customers.
Reasons to use Open Data
Using an external organisation’s Open Data (inbound).
- Innovate: Create new products and services using novel Open Data sources
- Reduce costs: Use free Open Data instead of buying proprietary data
- Organisational efficiency: benchmark your own KPIs and drive internal change
- Experimentation: Develop new potential products
3 benefits to public bodies using Open Data
Achieving common goals: Publishing Open Data and sharing municipal data with other public or private organisations can support all stakeholders in reaching their common aims, e.g. in becoming a smart city
Efficiency: Savings can be achieved by sharing Open Data across government agencies, at local, regional and country levels.
- avoids agencies collecting or purchasing data
- reduces data replication
- potentially enhances services
Complementary outsourcing: Government agencies often have limited budgets. Non-public organisations can use open data to help develop new services and apps for citizens.
TfL Open Data - Case Study
Benefits
Citymapper and other apps can use the rea-time data to save time.
- Saved time for passengers.
- Better routes, more updates
- Creates commercial opportunities for third party developers.
- Leveraging value and savings from partnerships. TfLreceives back significant data on areas it does not itself collect data (e.g. crowdsourced traffic data). This allows TfLto get an even better understanding of journeys in London and improve its operations.
Open Data & Start-ups
Benefits
- Low cost/free resource
- Flexibility and innovation
- Agile startups can experiment and pivot with new products that use Open Data.
- Collaboration
- Small businesses can grow by working with other Open Data organisations.
- Some publishers of Open Data look to SMEs and start-ups to become affiliates
Challegenes
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Absorptive capacity:
- limitations in obtaining the skills and knowledge to understand the context of Open Data sources and to integrate it into their products and services.
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Competitors:
- may imitate your products and services by accessing the same Open Data
Open Data & Big Organisations
Benefits
Save money and innovate:
- Open Data is free and can be used for new ideas.
‘Freemium’ promotions:
- Corporates are able to use Open Data as a trial or promotional strategy.
One-off projects:
- Data may be used in consultancy projects that provide new insights
Benchmarking:
- Benchmark KPIs against competitors using Open Data
Transparency, Compliance:
- Publishing Open Data can address regulatory requirements
Challenges
Agility:
- Larger businesses are usually less flexible than start-ups
- Hence, less capable to do entirely new practices based on Open Data
Cultural barriers:
- Established organisations often find opening their data to all external users daunting
- Many business made a business around selling proprietary data, don’t understand benefits of Open Data
- Open Data may require substantial changes to the business
Open Data & Social Enterprises
Low cost:
- helps them to create innovative apps and services which generate income for use in the creation of social value
Civic innovation:
- Social enterprises can improve government agency transparency through the development of new citizen-friendly apps and services
Benchmarking and one off projects
- KPIs comparison
- Open Data for research and campaign for change
Open Transport Net
Turn your open geospatial data into insights and easy-to-read, visually appealing maps. Help your city or business to solve transport related challenges by applying innovative insights and co-creating new services together with developers, data providers community representatives.
Evaluating sources of Open Data
Licensing:
- Open Data source licensed?
- Can you use it to meet your needs?
Provenance:
- Who is the publisher of the data source? Trust?
- Do you expect the organisation to be in existence in the next week, month or year?
Publication frequency:
- Is the data source published on a regular basis?
- Last publishing?
- Punctuality of publishing?
Data analysis:
- Do basic statistical checks.
- Are all the fields in the dataset complete?
- Are there any outliers?
- Is the dataset clean?
- Is the data formatting consistent?
Proprietary back-ups:
- Is there a proprietary dataset you could purchase as a back-up in case the Open Data source is discontinued?
Cleaning costs:
- Sometimes Open Data needs ‘cleaning’.
- This may undermine the case for using Open Data
Licensing and Open Data
Open Data licenses tell you what the data can be used for.
- Sometimes only requires referencing the source when using the data
- Some dont allow data modifications, or use it commercially.
- Can have legal consequences…