Is just repackaging and selling open data viable? Or should businesses be more sophisticated, aggregating and adding valuable insights to the data?

Some data sets are switching from OGL to restricted licences – like the ratings list. That has stopped some uncomfortable commercial uses – but killed some academic uses as well. The OS polygon data has been problematic because the co-ordinates can’t be republished. That’s been tightened up in a way that makes them completely useful commercially, because of wording that encapsulates all “benefitting” from the data.

We’re still missing some open data infrastructure and tools – including tools for non-technical users. There’s no real funding for that, so it’s being done in people’s spare time right now. There is a difference between open and shared data, largely that open data licences don’t create a contractual relationships. Now, in theory the open data user could create a separate contract with the provider – but there’s little evidence of that happening. Is there an argument for open data plus – a paid commitment to continue providing open data?

The Supplier Relationship

Traditional businesses manage supplier relationships – why shouldn’t open data businesses? The information that have could benefit the supplier. There’s benefits for both. The data publishers often don’t know who is using their data – and how.

One American provider makes the data available for free – but changes for bandwidth, which allows for heavy users cost management.

Competition is an issue. You build a product on open data, and your competitors can copy it quickly -0 there’s no play as access to the data is negotiated. The answer? Built value added services or insights into your product, which is harder to replicate. It comes down to innovation.

There are many challenges around continuity of supply. Crowd-sourcing is no guarantee that there won’t be a single point of failure that leads to a break in supply. Sometimes government bodies withdraw data products.

We need to push for commitments to maintenance when people publish data. The ODI certificates scheme was designed to aid in this.

There has been some friction between the public and private sectors. The public sector is still uncomfortable with people making money off “their” data – even though it is owned by the public. And some public bodies are still trying to sell access to our data.

Engagement is more than just making the data available – it’s a conversation and an ongoing process. One way of addressing changes to, say, licence or location, is to stick it in the metadata.

SWOT analysis of the open data ecosystem

Strengths

• The strength of an open data business is that it has access to a free, rich source of data they’d have had to pay for previous.
• Technology companies can concentrate on the technology, not the business of lawyers and contracts.
• It’s specialised – some people are scared of data, so you’re unlocking something the general public can’t otherwise access. * There’s a great community around open data, which can help you solve problems.
• It’s global – or, at least, European.
• It makes people think about how data links together.
• You can get the providers to tell you what went into creating the data. Private providers are much more cagey about that.

Weaknesses

• Capricious changes of license or availability.
• Data not being updated.
• It can’t be a unique selling point.
• It collects private businesses to collect their own, hidden data as a competitive advantage.
• The data hygiene part can be time consuming.
• Open data businesses aren’t making their code open source – because it’s their advantage.
• It changes the dynamic of first mover advantage – you end up just advertising to others how it can be done, and they can copy you.
• If you work in the open, and you make a mistake, there can be reputation issue.
• There’s lots of competition: NGOs, research organisation, who have different funding models.
• There’s a huge dependency chain with a single point of failure: the data.
• You can’t demand changes from your supplier.

Opportunities

• You have to work harder with the data – so it builds your understanding, as you seek your angle and value add.
• Open data quality is so messy, and there are so many sources, being able to find it is an competitive advantage.
• There’s endless duplication of effort as people download and clean it. Can we reward people for sharing better versions of the data?
• Could open data businesses start generating data as well as consuming it?
• Could you turn data into a public utility?
• Can you use open data to drive innovation?
• As funding declines in government are their partnership opportunities in delivering the data?
• You can expand quickly – start with a specific product, test that, and then expand by adding data sets.
• Free brain power – you’re crowd-sourcing brainpower
• Data is not subject to the tragedy of the commons. It’s a change of culture in running your business – because the data gets more valuable as it’s used. It’s the network effect.
• Leveraging the enthusiastic community.

Threats

• The perennial threat of privatisation of government services. We lost a bunch of data when British Waterways was privatised.
• A change in political attitudes to open data.
• Brexit – and data sets collected for Europe.
• Misattribution of flow.
• The funding crisis leading to pull back of open data initiates in local government.
• Some local authorities lack the skills tp publish open data.
• The time it takes to build a body of advocacy for open data – and people’s patience for a proved case.