Liberating links between datasets using lightweight data publishing: an example using IPNI and the taxonomic literature

I've written a short paper entitled "Liberating links between datasets using lightweight data publishing: an example using plant names and the taxonomic literature" (phew) and put a preprint on bioRxiv (https://doi.org/10.1101/343996) while I figure out where to publish it. Here's the abstract:

Constructing a biodiversity knowledge graph will require making millions of cross links between diversity entities in different datasets. Researchers trying to bootstrap the growth of the biodiversity knowledge graph by constructing databases of links between these entities lack obvious ways to publish these sets of links. One appealing and lightweight approach is to create a "datasette", a database that is wrapped together with a simple web server that enables users to query the data. Datasettes can be packaged into Docker containers and hosted online with minimal effort. This approach is illustrated using a dataset of links between globally unique identifiers for plant taxonomic names, and identifiers for the taxonomic articles that published those names.

In some ways the paper is simply a record of me trying to figure out how to publish a project that I've been working on for several years, namely linking names from BioNames. The preprint discusses various options, before settling on "datasettes", which is a nice method developed by Simon Willison (@simonw) to wrap up simple databases with their own web server and query API and make them accessible on the web. These can run on a local machine, or be packaged up as a Docker container, which is what I've done. You play with the database here: https://ipni.sloppy.zone. If this link is offline, then you can grab the container here https://hub.docker.com/r/rdmpage/ipni/ and run it yourself. If, like me, you're new to Docker, then I recommend grabbing a copy of Kitematic.

The datasette interface is simple but gives you lots of freedom to explore the data.

For example, you have ability to query the data using SQL, e.g.:

One advantage of this approach is that the data is more accessible. I could just dump the database somewhere but then you'd have to download a large file and figure out how query it. This way, you can play with it straight away. It also means people can make use of it before I make up my mind how best to package it (for example, as part of a larger database of eukaryote names). This is one of the main motivations behind the paper, how to avoid the trap of spending years cleaning and augmenting data and not making it available to others because of the overhead of building a web site around the data. I may look at liberating some other datasets using this approach.

Towards a biodiversity token: Bitcoin, FinTech, and a radical suggestion for the GBIF Challenge

First off, let me say that what follows is a lot of arm waving to try and obscure how little I understand what I'm talking about. I'm going to sketch out what I think is a "radical" idea for a GBIF Challenge entry.

TL;DR GBIF should issue it's own cryptocurrency and use that to fund the development of the GBIF network by charging for downloading cleaned, processed data (original provider data remains free). People can buy subscriptions to get access to data, and/or purchase GBIF currency as a contribution or investment. Proceeds from the purchase of cleaned data are divided between GBIF (to fund the portal), the data providers (to reward them making data available) and the GBIF nodes in countries included in the geographic coverage of the data (to help them build their biodiversity infrastructure). The challenge entry would involve modelling this idea and conducting simulations to test it's efficacy.

The motivation for this idea comes from several sources:

1. GBIF is (under-)funded by direct contributions from governments, hence each year it essentially "begs" for money. Several rich countries (such as the United Kingdom) struggle to pay the fairly paltry sums involved. Part of the problem is that they are taking something of demonstrable value (money) and giving it to an organisation (GBIF) which has no demonstrable financial value. Hence the argument for funding GBIF is basically "it's the right thing to do". This is not really a tenable or sustainable model.

2. Many web sites provide information for "free" in that the visitor doesn't pay any money. Instead the visitor views ads and, whether they are aware if it or not, are handing over large amounts of data about themselves and their behaviour (think the recent scandal involving Facebook).

3. Some people are rebelling against the "free with ads" by seeking other ways to fund the web. For example, the Brave web browser enables you to buy BATS (Basic Attention Tokens, based on Ethereum). You can choose to send BATS to web sites that you visit (and hence find valuable). Those sites don't need to harvest tyour data or bombard you with ads to receive an income.

4. Cryptocurrency is being widely explored as a way to raise funding for new ventures. Many of these are tech-based, but there are some interesting developments in conservation and climate change, such as Veridium which offsets carbon emissions. There are links between efforts like Veridium and carbon offset programmes such as the Rimba Raya Biodiversity Reserve, so you can go from cryptocurrency to trees.

5. The rather ugly, somewhat patronising furore that erupted when Rwanda decided that the best way to increase its foreign currency earnings (as a step towards ultimately freeing itself from dependency on development aid) was to sign a sponsorship deal with Arsenal football club.

Now, imagine a situation where GBIF has a cryptocurrency token (e.g., the "GBIF coin"). Anyone, whether a country, an organisation, or an individual can buy GBIF coins. If you want to download GBIF data, you will need to pay in GBIF coins, either per-download or via a monthly subscription. The proceeds from each download are split in a way that supports the GBIF network as a whole. For example, imagine GBIF itself gets 30% (like Apple's App Store). The remaining 70% gets' split between (a) the data providers and (b) the GBIF nodes in countries included in the data download. For example, almost all the data on a country such as Rwanda does not come from Rwanda itself, but from other countries. You want to reward anyone who makes data available, but you also want to support the development of a biodiversity data infrastructure in Rwanda (or any other country), so part of the proceeds go to the GBIF node in Rwanda.

Now, an immediate issue (apart from the merits or otherwise of blockchains and cryptocurrency) is that I'm advocating charging for access to data, which seems antithetical to open access. To be clear, I think open access is crucial. I'm suggesting that we distinguish between two classes of data. The first is the data as it is provided to GBIF. That is almost always open data under a CC0 license, and that remains free. But if you ant it for free it is served as it is received. In other words, for free access to data GBIF is essentially a dumb repository (like, say, Dryad). The data is there, you can search the metadata for each dataset, so essentially you get something like the current dataset search.

The other thing GBIF does is that it processes the data, cleaning it, reconciling names and locations, and indexing it, so that if you want to search for a given species, GBIF summarises the data across all the datasets and (often) presents you with a better result that if you'd downloaded all the original data and simply merged it together yourself. This is a valuable service, and its one of the reasons why GBIF costs money to run. So imagine that we do something like this:

1. It is free to browse GBIF as a person and explore the data
2. It is free to download the raw data provided by any data publisher.
3. It costs to download cleaned data that corresponds to a specific query, e.g. all records for a particular taxon, geographic area, etc.
4. Payment for access to cleaned data is via the GBIF coin.
5. The cost is small, on the scale of buying a music track or subscribing to Spotify.

Now, I don't expect GBIF to embrace this idea anytime soon. By nature it's a conservative, risk-averse organisation. But I think something like this idea deserves serious attention, ideally from people with much better understanding of the issues that my own "I saw this on Twitter therefore it must be cool" level. One way to move forward would be to model how such a system would work, based for example on data on web site visits and data downloads on the current GBIF portal. I suspect models could be built to give some idea of whether such an approach would be financially viable. It occurs to me that something like this would make a great GBIF Challenge entry, particularly as it is gives a license for thinking the unthinkable with no risk to GBIF itself.