PubTech Radar is a directory of companies, projects, platforms, initiatives, experiments, services that relate to academic publishing. You’ll also find things about open science, journalism, book publishing, writing, researcher workflow, library technology… anything I’ve come across and thought ‘that looks interesting’. It was developed by Helen King. It’s not funded, developed in partnership or sponsored by anyone.

What problem is PubTech Radar trying to solve?

PubTech Radar attempts to solve the following problems:

  • help publishers identify alternative suppliers, particularly suppliers who may not have worked with academic publishers before or who are not based in the UK/USA.
  • provide an evidence base so that when someone says we should build [this fantastic new thing] it’s much easier to say there are 5 companies already working on [this fantastic new thing], so perhaps we should think about working with them rather than building something new?
  • act as a memory aide to help with landscaping work on emerging technology themes

Why is so much data missing?

There is a lot of missing data, the data will be updated when I get time.

How accurate is the data?

The data is reasonably accurate. Most of the data has been manually typed so expect the usual errors. The ‘founded’ dates are probably the most problematic in terms of accuracy because different dates often appear in different places for the same company (think website v LinkedIn, company founded data v product launch date, etc.)

Why is company X included but not company Y that does the same thing?

It will be an oversight rather than a deliberate decision! The spreadsheet was started as a way to track to new startups/projects and information about more established/well-known companies is often missing/minimal because I can remember who they are. Tools that are very widely used, such as Google Docs, generally aren’t included in this database.

Doesn’t this website replicate the 101 Innovations in scholarly communications dataset?

Partially. There’s more on the degree of overlap between  other datasets here.

The taxonomy/classification is a bit weird

Yes it is. It grew ‘organically’.  If something is really bothering you get in touch and I can make a change.

Is there a bias towards Western/English speaking companies?

Yes. Feel free to add or suggest additions.

Can I get a copy of the data in a spreadsheet?

Yes. Drop me an email.