 So I am working on harmonizing the conceptualization of observation parameters. I would like to introduce me a little bit. I'm a semantic analyst and data manager at the Environmental Agency of Austria. I had been co-developing CERON. This is a social ecological research and observation ontology in 2009 until 2011. This ontology has not been used so much because we had no money left to continue the research on that. But we continued to work on vocabularies and we developed ENFTES, which was based on the CERON findings. I am the coordinator of ENFTES. ENFTES is a vocabulary used by research infrastructure called long-term ecosystem research. There is the International, the Ilter and the Elter Europe and I am coordinating it for Europe. There is also the Worldwide Elter. The Ilter is the international one. In the US, they are using another vocabulary, which is compatible to ENFTES. We helped each other and in the ongoing months, we are going to extend each other's vocabulary. This will be very compatible for researchers working with different data sets. Now I am involved in ENFTES. ENFTES is a project dealing with a lot of different research infrastructures and environmental research infrastructures. I am involved in the data scene where I also developed a reference model with other researchers for ENFTES and I am also coordinating the provenance task there. ENFTES is now going to terminate in April next year, but it will be followed up by ENFTES Fears, another four years of project, going as a building on the research done so far. I am also involved in the RDIA, Research Data Alliance, which is an international community, targeting to enable open sharing and reuse of data. I am also involved in the WISIC, the Vocabulary and Semantic Service Interest Group, led by Simon Cox and others. This WISIC Interest Group is organized in different task groups, and one of these task groups started at the beginning of this year. I was interested to bring together different people with the same objective, which is the harmonization of measurement parameters. I do this together with Michael Diebenbroek, who is working in Pangea. This is a rather large group of stakeholders involved, so we have different research infrastructure representatives. So long-term ecosystem research, that's me, Alessandro O'Johnny and Philippe Tambev. Then we have the ILTA, from the ILTA Network, Christian Vanderbilt, and I'm invited in October to speak also in California. Sorry, I made an error. It is not ILTA, it is USELTA. It's the US Long-Term Ecosystem Research Network there, and I'm invited to talk to them and to harmonize these different approaches also with them. Then ICOS is involved, ANARI, Life Watch, Aquadiva. These are all different research infrastructure dealing with different domains in the environment research. And lots of people, who are also partly involved in every plus, others not like those from Aquadiva. And we are also working together with data centers like Pangea, which is led by Michael Diebenbroek, with BODC, C-DataNet, with Alexander Kokinaki, probably you know her, GFBio, Naul Karam, so different data centers. And we are also working together with different representatives of technologies, ontologies. So, BioPortal, John Graybeal, and Envo. So, Pierre-Louis G. Putriag is also interested to join this effort, and Chris Mangel, and also EPIK with Ulrich Schwadmann. And also with Markus Stokker, I'm not sure if he has joined us. Do you see if he is there? I don't think he has joined Barbara, but Simon Cox has, he's joining us. And just to point out to other people, John Graybeal has presented in this forum before. And what we see here is quite a small community, I think, because I and certainly Simon and you, Barbara, know quite a few of the people that are listed on this slide here. So this community of ours with vocabulary workings on is not enormous, at least environmental vocabulary is not enormous. No, no, but for that, that we started this year to work together, I think it's a good starting point. So, and we are completely interested to enlarge this group and also to invite you to join this effort or to see how we can learn from each other. So, but for me, it was really interesting to see that the interest grows on it. Because it seems that there are lots of approaches, but not everything is solved yet. So that's what we found out so far. So what we intend to do in this task group is to develop best practices and generally accepted model for scientific observation and measurement parameters, including also if possible measurement methods and devices by using agreed core terminologies. So it is because we want to annotate research data with these vocabularies and to at the end be able to improve interoperability for data discovery and data integration. So the challenge is we want to analyze ecological phenomena across geographic temporal biological scales. And this requires a lot of variety of existing data sets which might derive from different data centers. So we are dealing with observational data, which is often represented in tabular form. And this data differs in a number of attributes and the relationships implied between the attributes and the coding conventions used for representing information within data sets. So that's not that trivial it might seem in the beginning. Because although there are already a lot of different schemas trying to solve this issue, the schemas are different, very different in scale and incompatible to each other. They capture the data semantics in different complexity. So they describe the complexity in different ways. And sometimes they say at a very rough level. They provide semantics for specific domains and for each domain there are different approaches. They indicate the admitted value of attributes sometimes very vaguely and they account or not for the specification of units. So most schemas capture insufficiently data semantics by conflating associated attributes and thus are not suitable to correctly describe unambiguously complex parameters. And I will show it only on a few parameters or on a few examples. So this is how we always have to deal with, we have to deal with observational data. They come along as a tabular information with columns indicating different attributes. It's not always sure what the abbreviation means or researchers have very often to do to interpret and compare and try to find out what is really meant. Sorry I'm at home and I have a dog and sometimes he barks and I'm sorry about that. So it is not always easy to understand what is meant by the different columns. But to come to the point what we mean with conceptualization is that there's a monitor property which could be described in a sentence like monthly mean desolved lead in that's pavilion in water taken from the river Thames by sampling. And so using the Nomenclature we would say that we could differentiate between a feature and observable property in the process. And in this case the features or the object in nature which has location would be X and Y coordinates would be the river Thames. The observable property the monthly mean desolved lead in water and the process would be sampling by sampling. And this could be done more specified. But the issue which makes it more difficult is to try to decompose the middle element here the observable property in atomic elements. So for example we could say what is meant monthly mean here what is desolved lead concentration the BPP water. So how can we call them and what are these elements. And we can see that this is dealt very differently in the different approaches. For example in Cervante or Coa which I was developing with my LTR team is not going into detail what is really when we talk about this atomization. So what we have here is that we have in the middle the value set which is the observation more or less and which has an investigation object we are observing. And the parameter method is a complex element which has a parameter and has a method. But how this parameter itself is composed here it is not clear it is it lets it open. And if you look at oboe for example. Then which is used by aqua diva and by an eye we can find out that the model identifies entities or objects being observed and the observation of entities and their corresponding measurements. And for each measurement there is the value of a characteristic of the entity according to a measurement standard or a protocol and the context assumed by each measurement and observation. But it is not really clear how this characteristic should be as or what it is about yeah this characteristic and I make this a bit more clear. Here I am trying to describe this example tree diameter at breast height and you could say that the observation has an entity in this case tree and the measurement on that tree would be using an element characteristic which is the diameter at breast height. And this measurement has a value and uses a standard but we could also say nobody would hinder us using oboe that the characteristic in this case is diameter and the protocol would be measured at breast height. So it is up to the researcher then to decide which how he describes it within oboe and we can see that in the different research infrastructures as we have in our group an eye and aqua diva that they use it differently. So if we then try to describe more complex parameters like concentration of nitrate in soil water we find that oboe is limited because the characteristic in that case is the nitrate concentration. So you have then to bring together two concepts or two elements together in one concept but you could also say that it might be important to differentiate between concentration and nitrate. So it's just to make this clear and also soil water which is the entity could be split in soil and water because you are observing the nitric concentration in the water of the matrix soil and this is not depicted here. And if you look at the observation measurements of Simon Cox then you see that we talk here about observed properties about the phenomenon but we are not going into detail what this phenomenon could be. But there are extensions of this and I will go soon explaining this but I just wanted to compare on the oboe and this is more or less a rather simple to compare. There could be some not that I think that rather clear how that they could be compared that I tried it here so but still when it comes to properties. They both don't have a real good solution because when I come across lead pattern for them they use the extension of on them and say that the observable property and the phenomenon types could be better described if they are split into two. Different other concepts like object of interest and property but also matrix and statistical measures and so on so they go for the approach to atomize this observable property and different other elements. And in end this I try to follow this scheme and say okay if we are looking at the concentration of sulfur in soil water we can atomize this description in different elements and say concentration would be the property, sulfate would be the object of interest, the per unit volume unit and soil water would be the matrix and listen to the device for example. And in end this we have also the compound concept used by the scientists which would be then the parameter. The parameter is then compound description of what could be then split in different elements atomic concepts. So you would find both levels of descriptions. And for simplicity reasons we would not have concentration of sulfur in soil water but on but concentration of sulfur, which is not. I'm not sure if this is the best way to do it because it's always a compromise between what is used by the scientists and what would be sensible to use for consistency reasons. So end test is not finished. So this is in continuous evolvement and it should also be like that. And probably we will come up with different solutions so that we could have concentration of sulfur and then as a parent and then differentiate it where this concentration of sulfur could be to have other parameter. Specifications. Yeah, but this is not really decided. But the status is that we have concentration of sulfur as a parameter. And what could also, so if you are interested to know more about end test we can also talk about that afterwards because I am more expert as I can more explain you on that. End test and on the other models presented here. Then in Pangaea they also try to describe the different parameters depending on the complexity. And there are some approaches proposed by Robert Hoover. But it is not fixed yet because they are Pangaea. As Michele Dieppenpreuk really looks for solutions which are then accepted not only for Pangaea, for Germany, but they want to use data from all the whole Europe and other parts of the world and then try to really find a common approach or a mapable approach. So they are still open to change this according to the outcome of this group. So this is all in discussion. And BODC, so this is also a data center in France which, at least we see data, we see data information and they seem also to follow this approach of automizing complex properties. And they have a composer for the description of parameters and to compose this description they use for each of these elements vocabularies. So for example for the measurement of the property they have the vocabularies 6 which are for example temperature, uptake, rate, abundance, concentration. The entity or object could be a biological entity or chemical entity or physical quantity and for each of them they have specific vocabularies they use. Or they have environmental matrix or compartment or the measurement matrix relationship which is helping to compose the sentence of the observation. So it seems but I'm not sure or I'm sure that we will find some inconsistencies also there with the approach I presented before. But it seems that goes in this direction and the same direction. So what we did so far we had six meetings where each of us presented our approach. We found out that we need to go into much more detail and really look for comparison, so describing complex use cases with our own approaches and analyze the real differences between the different approaches and then find out where is the gap. Is there a possibility to map it so that it is unknown because can we then find common approach or what can we do and this is not done just by presenting each other's approach this is done by doing a really working group out of it. So we decided to prepare a case statement to become a working group and this will then start in this autumn. So I cannot present here some news in that sense that we have invented already a new approach but there is a big intention to go in this direction. So this is not the roadmap because it has not been agreed so far but some ideas that we want to agree on core terms so that we if I say property everybody in the group understand what I mean by property that's not so sure because everybody has another connotation to this term. So we have to find our own language whatever then at the end stands there for a specific concept. For me it doesn't matter which name we use then. We have to agree on terminologies on already existing terminologies for core elements for example for chemical elements or whatever then choose good use cases with different complexity degrees. Then try to describe these specific use cases with each other's approaches we have in our communities and then compare them and find out the gaps differences and whatever come to a conclusion where we overlap. And out of that develop a common model or mapping scheme between all of these different approaches. And then produce guidelines publications and so on but for doing this yeah beneath also some some money a project behind and we are working hardly on getting some funding for for this work but I'm optimistic I'm sure we will find a way to work on this because. You really need to go on about this. So. For sure we are looking. To involve other important stakeholders. Yeah. I will also try to bring together the people after the long summer period again in autumn. Yeah and I invite also to join us. So that's what I wanted to tell you so if you have any questions please just go ahead. Thank you.