DISSCO ARCHITECTURE

‖ That poses a dilemma: If DiSSCo intends to build trust in the reliability and solidity of its data, some components of its data architecture must remain the same over time, even beyond the research infrastructure’s lifecycle. On the other hand, it is only natural that future technologies or user needs will affect how DiSSCo’s infrastructure evolve. In other words: changes will be needed at some point. The question therefore is how to find a balance between what stays and what goes.

‖ The evolutionary architecture approach gives us a way of eating the cake and having it too, so to speak. It acknowledges the inevitable evolution of things but at the same time shields some essential components of the architecture by granting them protected status. Those protected components, being “futureproof”, will stay the same in the long term.

We will deal with some of those components, such as the FAIRness of data or the centrality of the Digital Specimen later. If you want to take a look at the whole list, go here

‖ FAIR is about making data increasingly findable, accessible, interoperable and reusable both for humans and machines. The “and machines” bit is crucial because, given today’s information tsunami, we will have no option but to rely on them to be able to manage, exchange and extract meaning out of huge amounts of combined data from different sources.

‖ FAIR principles are the best way of ensuring proper stewardship of data but let’s admit it: they are a bit abstract, so you might wonder: How is data made FAIR? Is it about writing code or what? The answer to that is not difficult but it is long to explain, so let’s see a couple of examples that will probably help you grasp all this.

□ Example 1: If you want your data to be Findable, the FAIR guiding principles recommend that, among other things, you give your data a globally unique and persistent identifier, that is, a sort of ID code that will belong to your data -and your data only- forever. We’ll get to that later, don’t worry.

□ Example 2: If you want your data to be Reusable, the FAIR guiding principles recommend that, among other things, your data and metadata be released with a clear and accessible data usage license.

‖ There are a bunch of other criteria that you can apply to make your data FAIR. Find them and much more about the FAIR Guiding Principles here and here.

(warning: long paragraph!)

‖ Ok, in the case of DiSSCo, we should rather say that they are specific types of FAIR Digital Objects, given DiSSCo’s alignment to the FAIR principles. DS and DC are not the only types of digital objects, of course, just the two that are more closely related to NSCs.

‖ “FAIR Digital Object” and “Digital Specimen” are the concepts that you will probably hear more often, so let’s give each of them a paragraph. 

‖ In essence, a FAIR Digital Object (FDO)  is a digital object that follows the FAIR principles. If a Digital Object is a sequence (or sequences) of bits “structured in a way that is interpretable by one or more of the computational facilities and having as an essential element an associated unique persistent identifier” (DONA Foundation), then a FDO is the same, only FAIR.

‖ And why do FDOs makes sense? At the end of the day, FAIR was not part of the original DO idea, right? Well, it turns out that there are fundamental elements in the DO nature that make it compatible with the FAIR principles. In fact, DOs make FAIR implementation with other systems possible in a much more granular and interoperable fashion. So they do make sense.

‖ As stated above, a Digital Specimen is a specific type of digital object. You will usually find it described in DiSSCo documents as a “surrogate” or a “digital twin” of a physical specimen. You can have a specimen of a butterfly in your hand and its digital twin on the screen of your computer.

‖ But the butterfly on the screen is not just a visual representation of the one in your hand. That digital image is just the “cover photo” of an online package that brings together FAIR data from different sources (taxonomic, genomic, biochemical, you name it), all referring to the same physical specimen.

‖ Besides -and this is the best bit- this online package that contains all the data related to the butterfly is not static in the same way as the information written on the tag of a physical specimens is. Instead, the data anchored by the digital specimen is dynamic, actionable. In other words: you can work on it and transform it (e.g. by annotating it or applying DiSSCo services to it). Remember the mantra: “DiSSCo aims at turning static records about specimens into dynamic, actionable objects that will evolve with science itself”? Here it is.