At Science Online 09 and at the Smi Electronic Laboratory Notebook meeting in London later in January I talked about how laboratory notebooks might evolve. At Science Online 09 the session was about Open Notebook Science and here I wanted to take the idea of what a “web native” lab record could look like and show that if you go down this road you will get the most out if you are open. At the ELN meeting which was aimed mainly at traditional database backed ELN systems for industry I wanted to show the potential of a web native way of looking at the laboratory record, and in passing to show that these approaches work best when they are open, before beating a retreat back to the position of “but if you’re really paranoid you can implement all of this behind your firewall” so as not to scare them off too much. The talks are quite similar in outline and content and I wanted to work through some of the ideas here.The central premise is one that is similar to that of many web-service start ups: “The traditional paper notebook is to the fully integrated web based lab record as a card index is to Google”. Or to put it another way, if you think in a “web-native” way then you can look to leverage the power of interlinked networks, tagging, social network effects, and other things that don’t exist on a piece of paper, or indeed in most databases. This means stripping back the lab record to basics and re-imagining it as thought it were built around web based functionality.

So what is a lab notebook? At core it is a journal of events, a record of what has happened. Very similar to a Blog in many ways. An episodic record containing dates, times, bits and pieces of often disparate material, cut and pasted into a paper notebook. It is interesting that in fact most people who use online notebooks based on existing services use Wikis rather than blogs. This is for a number of reasons; better user interfaces, sometimes better services and functionality, proper versioning, or just personal preference. But there is one thing that Wikis tend to do very badly that I feel is crucial to thinking about the lab record in a web native way; they generate at best very ropey RSS feeds. Wikis are well suited to report writing and formalising and sharing procedures but they don’t make very good diaries. At the end of the day it ought to possible to do clever things with a single back end database being presented as both blog and wiki but I’ve yet to see anything really impressive in this space so for the moment I am going to stick with the idea of blog as lab notebook because I want to focus on feeds.

So we have the idea of a blog as the record – a minute to minute and day to day record. We will assume we have a wonderful backend and API and a wide range of clients that suit different approaches to writing things down and different situations where this is being done. Witness the plethora of clients for Twittering in every circumstance and mode of interaction for instance. We’ll assume tagging functionality as well as key value pairs that are exposed as microformats and RDF as appropriate. Widgets for ontology look up and autocompleton if it is desired and the ability to automatically generate input forms from any formal description of what an experiment should look like. But above all, this will be exposed in a rich machine readable format in an RSS/Atom feed.What we don’t need is the ability to upload data. Why not? Because we’re thinking web native. On a blog you don’t generally upload images and video directly, you host them on an appropriate service and embed them on the blog page. All of the issues are handled for you and a nice viewer is put in place. The hosting service is optimised for handling the kind of content you need; Flickr for photos, YouTube (Viddler, Bioscreencast) for video, Slideshare for presentations etc. In a properly built ecosystem there would be a data hosting service, ideally one optimised for your type of data, that would provide cut and paste embed codes providing the appropiate visualisations. The lab notebook only needs to point at the data; doesn’t need to know anything much about that data beyond the fact that it is related to the stuff going on around it and that it comes with some html code to embed a visualisation of some sort.

That pointing is the next thing we need to think about. In the way I use the Chemtools LaBLog I use a one post, one item system. This means that every object gets its own post. Each sample, each bottle of material, should have its own post and its own identity. This creates a network of posts that I have written about before. What it also means is that it is possible to apply page rank style algorithms and link analysis more generally in looking at large quantities of posts. Most importantly it encodes the relationship between objects, samples, procedures, data, and analysis in the way the web is tooled up to understand: the relationships are encoded in links. This is a lightweight way of starting to build up a web of data – it doesn’t matter so much to start with whether this is in hardcore RDF as long as there is enough contextual data to make it useful. Some tagging or key-value pairs would be a good start. Most importantly it means that it doesn’t matter at all where our data files are as long as we can point at them with sufficient precision.

But if we’re moving the datafiles off the main record then what about the information about samples? Wouldn’t it be better to use the existing Laboratory Information Management System, or sample management system or database? Well again, as long as you can point at each sample independently with the precision you need then it doesn’t matter. You can use a GoogleSpreadsheet if you want to – you can give URL for each cell, there is a powerful API that would let you build services to make putting the links in easy. We use the LaBLog to keep information on our samples because we have such a wide variety of different materials put to different uses, that the flexibility of using that system rather than a database with a defined schema is important for our way of working. But for other people this may not be the case. It might even be better to use multiple different systems, a database for oligonucleotides, a spreadsheet for environmental samples, and a full blown LIMS for barcoding and following the samples through preparation for sequencing. As long; as it can be pointed at, it can be used. Similar to the data case, it is best to use the system that is best suited to the specific samples. These systems are better developed than they are for data – but many of the existing systems don’t allow a good way of pointing at specific samples from an external document – and very few make it possible to do this via a simple http compliant URL.

So we’ve passed off the data, we’ve passed off the sample management. What we’re left with is the procedures which after all is the core of the record, right? Well no. Procedures are also just documents. Maybe they are text documents, but perhaps they are better expressed as spreadsheets or workflows (or rather the record of running a workflow). Again these may well be better handled by external services, be they word processors, spreadsheets, or specialist services. They just need to be somewhere where we can point at them.

What we are left with is the links themselves, arranged along a timeline. The laboratory record is reduced to a feed which describes the relationships between samples, procedures, and data. This could be a simple feed containing links or a sophisticated and rich XML feed which points out in turn to one or more formal vocabularies to describe the semantic relationship between items. It can all be wired together, some parts less tightly coupled than others, but in principle it can at least be connected. And that takes us one significant step towards wiring up the data web that many of us dream of

The beauty of this approach is that it doesn’t require users to shift from the applications and services that they are already using, like, and understand. What it does require is intelligent and specific repositories for the objects they generate that know enough about the object type to provide useful information and context. What it also requires is good plugins, applications, and services to help people generate the lab record feed. It also requires a minimal and arbitrarily extensible way of describing the relationships. This could be as simple html links with tagging of the objects (once you know an object is a sample and it is linked to a procedure you know a lot about what is going on) but there is a logic in having a minimal vocabulary that describes relationships (what you don’t know explicitly in the tagging version is whether the sample is an input or an output). But it can also be fully semantic if that is what people want. And while the loosely tagged material won’t be easily and tightly coupled to the fully semantic material the connections will at least be there. A combination of both is not perfect, but it’s a step on the way towards the global data graph.