 So yeah, good now. OK, thank you. Thanks, Alex. So yes, I'm Alexander Prent. And on behalf of Marta Klocking from Göttingen University and the whole team behind this effort, I'm giving this presentation. Now, the initiative here is co-funded by the European Union as a project ran by the Committee on Data from the International Science Council and also co-funded by OSCOPE. It is really the one geochemistry initiative and that's aiming to bring together international groups around geochemistry, so the analysis of rocks and the chemistry of rocks. Here are very aptly named the title, specifying locally and harmonizing globally in terms of development of vocabularies. So what does a local community need and how can we make that interoperable in terms of a global system? Well, geochemical data is very relevant to society and particularly applies to six of the sustainable development goals in terms of clean water, affordable energy, clean energy, decent work, industry innovation, infrastructure, climate action, life on land. There are six of the main direct sustainable development goals that geochemistry has an impact on and really has an impact on most or not all. So as you can imagine standardizing such data is of great importance that we can do much more with it. And when we lost and we can reuse it, we can find it. Here's an example of that Stuart actually helped write in last year where an example of not having standardized units leads to disaster. And the Mars orbiter that was meant to orbit Mars never did. It crashed because some teams had used metric units and some other teams had used imperial units. So a loss of multiple years of effort and hundreds of millions of dollars. So if we were to speak the same language, we would have completed the Tower of Babel and therefore standardization and vocabulary is so important. Now geochemical data in itself is very specific. People analyze one or two isotopes and they spend a lifetime doing so. Now if you get those isotopes and the values analyzed in a list or a table, you can fill not even a USB thumb drive with the lifetimes of work. So these long till data, they can be on a computer. You can work with them on a computer. So there's no real need of super organized data storage as with astronomy or climate and physics. They need powerful computers to do the data reduction. So you need natural to organize that a bit better when you have shared funds needed to do that science. So it's very specialized, low volume, difficult to find, collected by a lot of people. And this may not be the result of having so many societies and unions, but it's definite that there are a lot of different geochemical societies and unions and national organizations. And therefore it'd be great to harmonize the efforts around data through a more organized initiative, collaborate, and coordinate that better. So we got together with a group of enthusiasts from the E-POS birth plate observatory system in Europe, EarthCAM, Astromat in the US, DGSG ROC in Germany, and Australia with Leslie, myself, and Kirsten Elger in Germany again at the GFZ Data Services and also one partner from NFDI for Earth in this case. So just like the NFDI for CAM as Stuart mentioned just now. And this initiative is really aiming to facilitate better science or generation and acceleration of generation of new knowledge in geochemistry and discoveries. So very important to us is that we know where the data comes from, how it's been generated, and therefore we can trust and interpret and reuse data. So with that comes how to do that. And as we have a community that's very diverse and quite fragmented, how do you get them together? Now the first thing would be indeed to speak the same language, to communicate, and therefore control vocabularies would be fantastic to have, enabling the real interoperability of all these fragmented data systems and repositories and groups of people. So what do we need is an overview. Where do we start? So getting together in one geochemistry was already a great start. So georock, pet-DB, they've got massive amounts of geochemical analyses, and astromat, and the AGM, the Oscope Geochemistry Network, are working together in getting a vocabulary registered with research vocabularies Australia. Part of that is to have a vocabulary about samples. How do you describe this sample? What's necessary? What concepts do we have and make a full sample description? Because that's the core identity used to generate data around. And everything is hopefully linked to that sample. It's geospatial location. Then looking at the analysis, going to the analytical methods. And in the sample description, we've worked with Mindat. They've got a fantastic description of all minerals and lithologies you can basically imagine. And they're working on that to make machine actionable, machine readable. So you can look at that again in a different way. So components of a vocabulary would be the sample and the analysis. And then we have looked at how they have these commonalities. Analysis would analyze the lithology. A sample would be containing information about the lithology of that sample. For example, the description of the rock is lithology in this case. So there you see a couple of components of a vocabulary and how we are aiming to have separate vocabularies that are connected. So a vocabulary for a sample consisting of a vocabulary of a location, a vocabulary or terms and definitions about that location and the specimen. Now you can look at that in a different way again. What components do we want to address? So what's the feature of interest here on the right? And how is the geological information is used in that feature of interest? What's been observed? And what's sensor and sampler and actuator have we used? And what kind of initiatives have been busy with describing these things or providing vocabularies and terminologies for all these components? Now here, I think it's very apt to hear about the drum and the initiative, Simon Cox. And of course, the IUPAC, what's been going on there. Geochemistry is really a geology and chemistry combined. So being maybe at that knife edge in the middle, we never got ourselves organized to be either fully involved in chemistry or in geology. So never really developing these glossaries. But combining what's already out there can bring much more organization to this community. So hence, working together with them is really important. And we already do through the bigger project, the World Fair project, the CoData project. What else has been done in the geochemistry domain? There's a lot of papers out there that describe best practices. And we've been collating these efforts. And the aim is to make these best practices in more machine-actionable best practices and terminologies. So here's one, two, three, four, five, six, seven. And in the middle is that gray paper that was produced by the Geological Society of America. And there was a call to ask the community, can we please provide standards and recommendations for all these various techniques that we use in geochemistry? And there's quite a many. Here I listed 11. You might be able to read that. But other efforts in NASA and space analyses have listed up to 70 instruments that produce different data and basically different data up to 140 data types. So you can imagine the diversity. Now, I talked a little bit about Minda and how they've got that fantastic store of hierarchical lithologies, completely described, easy to find. And they're making their platform into a machine-actionable platform. And like you discussed short, where we have to go away from or create machine-actionable PDFs or make sure that the PDFs we have and the glossaries we have become machine-actionable. And that's something Minda has got funded for. And through the AGN in Australia, they've been collaborating with Minda to use that hierarchical list of lithologies, so rock descriptions and mineral names in their platforms describing and storing geochemical data. Now, not all of these terms are needed. So subsets can be made of those terms and descriptions. And sometimes international groups will need different rock names. For example, Australia has a very particular weathering of its surface. And that's described by a very particular name. So that can be additions to Minda's vocabulary when they have it online. That can be added. And together with EarthCamp, GeoRock, and AGN Astromat, we are working on producing vocabulary on research vocabularies Australia. And each of these vocabularies will be registered as a fair enabling resource, which brings me to our project that is funded by the European Union. And it's not our project. Geochemistry is here and little part of it. One of 11 case studies in the CoData RAN World Fair project. And the World Fair project has set up this real interoperability or cross-domain interoperability target. And one way to do that is through the fair implementation profiles, which basically list technologies that platforms use to bring data in the public domain and to make it machine actionable. Now that exercise is pretty complicated. And on purpose, it's a bit small here on the right. This fair enabling implementation profile asks questions about a repository and the technologies that the repository use to make data fair. And you can see here on the left how fair is not just findable, actionable, interoperable, and reusable. But it's pretty complicated. Each letter of the acronym has multiple components. And if you address that, you can come to a convergence. And this is going on. I should discuss this first. Sorry, where Earthchem and, for example, Georock, they both fill out this fair implementation profile. And we get to know the fair enabling resources for each of the projects. And this is basically showing the technology on the left and the technology on the right. And then with that knowledge, we can create how these two technologies can interoperate, how they can work together. And with that, we can really come to convergence. And another way to come to convergence is just simply to sit around the table and say, OK, you've got a big database. I've got a big database. Then let's talk about making the vocabulary that describes these databases the same. And that's been going on in the last couple of months with these two large databases, Georock and Petty B. And together they have 39 million single data values. And I guess, Alex, 15 minutes. OK, I guess if you look at that, that's a large amount of data that has the same language. And I always compare that a little bit to language in general. If a lot of people speak English as we do, it's quite attractive to learn that language. So 1Goo Chemistry will become a co-data working group that will bring together 2Goo Chemistry Community around data organization and via collaboration with existing initiatives such as the DRUM, IUPEC, 1Goo Chemistry, and really working with groups that have reinvented the wheel, not reinventing the wheel. So with that, we're going towards a fair geochemical data ecosystem. Now get involved. Scan the QR code to get into the Slack channel. And I'm happy for you to contact me at this email address, Alexander at oscope.org.au. And you can always have a look at the web page, 1Goo Chemistry web page there on the left. Thanks.