 Okay, then let's start and my name is Klaus. I'm glad to be here at DrupalCon. So, let's see if my, it's working, yes. So, it's a great pleasure for me to be here and to tell you something a little bit about digital humanities, and I'm glad to take you to a journey into the world of academics. And we are not so many people, so maybe that's the problem of humanities, but let's see. So, in concrete, I'll tell you something about what is digital humanities and how Drupal is used there in this field. But I'm also interested into how Drupal can help to support the ongoing efforts in the digital humanities community. So, I suppose that not so many of you are familiar with the term digital humanities. But I guess I will skip this part with, you can enter, if you want, we are not so many people, so I skip the slide or thing and ask you directly, so how many of you know about digital humanities before? Okay. Yeah. So, I guess no one is into digital humanities. Yeah. Okay. So, I start by telling you something about me. As it will give you first impressions, what digital humanities could be and it tells you something about the broadness of this idea of digital humanities. And I will use, as you can see, sometimes the abbreviation DH, because it's the short term and every time saying digital humanities is a little bit awkward. So, DH stands for digital humanities. So, currently I'm working at the Austrian Center for Digital Humanities, that's at the Austrian Academy of Sciences here in Vienna. You'll see the links. So, if you have time for sightseeing and if you're interested into Baroque architecture and paintings, then there's an insight deep for me, so the blanket hall of the Academy main building is a great thing to see. So, it's situated in the first district. Ask me afterwards for coordinates if you're interested. But at the Austrian Academy of Sciences at the Austrian Center for Digital Humanities, I work as a researcher and as a software developer. Our main projects are situated in the academic disciplines of history, literature studies, language studies, especially dialect research and archaeology. We are operating mainly on the level of academic research and in general digital humanities refers to academic projects, but it does not always the case. So, together with other Austrian digital humanities institutions, we run the website Digital Humanities AT. There you can get more information on events and projects. By the way, this website is a de-covered 2007, where I'm responsible for the back-end and my colleague, Christoph Hoffmann, created the front-end in Angular. And we are currently switching to 2008, but it takes us some time. Before I started to work at the ACDH, I worked at the Department of Theater, Film and Media Studies at the University of Vienna. I'm also trained as a theater-filmer-media scholar at this department. And then we did some projects that already give you some impressions, as I told you about digital humanities projects. So in 2006, we started by initiating a website where students of the department published reviews on movies that were shown at the Rienale, the Riena International Film Festival. For the research team of Professor Christian Schulte, I created a website in 2007, where publications, events and recordings of lectures are collected. So it's also about, you can see the videos, it's about research material and how movies are researched. I also did some other non-jubile projects there, as an example, a review platform for new publications in the field of theater-film and media studies. And internal tools to administer the media collections of the department that are needed for research and for study. So I guess that these are already some information that may help you to get a picture of digital humanities to summarize. It is about initiating and supporting the digital change in academic research, especially for disciplines that are collected under the umbrella of German humanities. This includes not only to digitize material, so that's also a big task to do in this field, digitize material for research. It's also about creating digital environments that helps to engage students and scholars. And it also has something to do with a better provision of research material. So to summarize, the general aim is to enable new or better research possibilities with the help of computing. It also implies to have a critical dispute on the usage of digital technologies, not only in research, but also in society. But that's a point I will not talk about in this session. I will go more further in detail on new developments that arise in the field of digital humanities. And that may be helpful for the Drupal community. That's not only in terms of digital humanities projects itself, but it's also, I guess, interesting in the general discussion on the progress of Drupal. So therefore I will not go into technical details and instead stay with general observations about the horizon, as this is the horizon track of digital humanities trends and possible interferences with Drupal. So that's about me. We can skip this as we didn't do the slides. So what's next on the agenda? I'll give you a more detailed explanation of digital humanities. I will introduce you to the fair principles. And at last I will point out some challenges of digital humanities for Drupal. So let's start with what is digital humanities. Once again. So here I give you more cornerstones. You can consult this website, whatistigitalhumanities.com. That's a really nice website where I put some of the quotes on the slides, but I guess they are hot. Should work. You can read it at the back here. So there are randomly based quotes. What is digital humanities? There are around 800 available. So to get an impression that it's not so easy to define digital humanities. And a reason is that some people see it as an acompany for academic disciplines. So more a support thing helping the humanities. Others see it already as a discipline by its own. So among humanities usually such disciplines are collected to deal with humans and their expressions in arts, culture, history. But also in reflecting on humankind. So that philosophy would be such a discipline. And often people distinguish between humanities, social sciences, natural sciences and so on. But all of these academic fields and disciplines have in common. They are confronted with changes in their practice by commuter methods. So you're not misguided if you see digital humanities as an incubator for implementing computing methods in the humanities. But also in academics generally. The age itself has also an own agenda by exploring new methods and views on research. As well as discussing the changes and challenges that are evolved by the digital turn for scholarship. The age identifies itself as an open field and has a growing community attracting scholars from various disciplines. But also librarians, students, developers, citizens, scientists and so on. As the quotes from what is digital humanities.com already shows you, there are many different definitions of the age. So it's important that there is not the one definition or approach of digital humanities. And that the following thoughts of mine are based on my experiences in this field. Therefore being one of many paths you can follow if you work in this wide field. So talking about projects in digital humanities. So there are rather small projects that it's important to note here because that's one of the reasons why the projects and ideas I talk about do not fit into the higher education industries distributions that are promoted on tuple.org as you see it. So put them away. So usually in a DH project you get funding for a short period of time about one or two years or if you're lucky three years or more. And within these limits a team of academics will do the research and ideally along this line of work a digital pre-sense is built up. Including also ideally steadily digital materials as a result of the research. But more often you have a website where the project is only is described and when the funding ends you put there a lot of data as you are able to do. When the project ends there is in many cases no more maintenance. And one reason for this is that humanist scholars seldom develop or maintain software by their own. More often a teaching assistant or technical assistant trained in coding will do the job. So we are constantly new requests by researchers that need to be addressed in such projects. But things are changing that's the good thing. More and more professional training is available. So even teaching digital methods gets more frequent in curricula of universities. Sustainability is becoming a big issue and is addressed. How can we ensure that research data gets not lost? Moreover how can we use it for new research? And that means new approaches not only in gathering research data but also in developing research platforms and workflows that enable to reuse data and support collaborative research. So these are long standing ideas but they come more and more in play with new technologies with experiences made so like the vanishing of old projects including the data and more funding. And that is probably the place where Tupel comes into play. So in principle the idea in the field of digital amenities is to build up and support a research data life cycle. You can see here one example of such a research data life cycle. That's the one from the United Kingdom data archive. You see the different steps and the idea is to have a circle. So you start with grading data, then you process data, analyze it, reserve it, give access to this data and the most important thing, reuse the data. And in theory the circle will now start again. So you take the data that were created and processed and put it in another project. So that research data is floating around and is steadily enhanced. So how can such a DH workflow look like? I take the example of a digital edition. A digital edition is a website where you put some information or text from our force, let's say. So the letters our force is writing to another people and you want to publish this and comment it. So you start by digitizing the material. You make an optical character recognition, OCR, converting the images you scan to text. You do corrections and you encode it. You encode it usually with TI, that's the text encoding initiative, that's a research community standard for working with text. And depending on your research question, you will encode the things you are interested in. And these things are called named entities. So that are persons, that are places, events and so on. Everything you can refer to another context. And you link these entities, these named entities with so-called authority files. And these authority files are databases with references to such entities available with unique identifiers. So I put two of them there. The one is GeoNames, this is used for geographic entities. So the idea is how can I differ between, let's say, Vienna as the city in Austria and all other Vienna's that exist in the world. So there is a Vienna in the United States and so on. And I want to clearly state that I, if I speak about Vienna, let's say in a dexter somewhere, I mean the Vienna in Austria. And therefore you have GeoNames where you find your place that you point to and you will get a unique identifier that you can then use in your data. So there are way more steps in this workflow. So in the end of a project you usually publish some papers and put on a website where the research results in a data is located. But you should also deposit this data into trusted data repositories. They are usually run by academic institutions, often libraries, where your data is hosted so that later on people can reuse this data or review your research results. So that is the theory, but in practice it's a troubling field. Different data formats, different data models or data models that are not comparable, missing data and meta data. So meta data is, frankly speaking, data about data. So it describes how this data is generated and so on, that would be meta data. Generally speaking, with agreed standards, a strong perspective on data quality and meta data quality and tools that support you, all of this will be a hopeless effort. So not necessarily for the research project itself, but for the follow-up projects or even if you try to work with your data later on. This issue frequently reduces researchers and technicians to despair. But there is a growing awareness that is expressed in guidelines and community discussions in standards and quality recommendations. As this needs to be a community effort, there are in the meantime specialized organizations that create such information resources. So one of them is Clarine, that's a European perspective here. It's a network on research on language studies. The website of them operates on 207, by the way. We have Daria, it's a digital research infrastructure for the arts and humanities. And there are other projects like Parthenos, it's a project I work in. They have a great acronym if you see it. It's pulling activities, resources and tools for heritage, e-research, networking, optimization and synergies. Parthenos, it's also a great goddess. And that's all efforts to build up DH infrastructures. And the fresh community outline is the so-called FAIR data principles. They are worked out by 411, that's a community of scholars. So coming to this FAIR data principles. FAIR is an acronym and it stands for Findable, Accessible, Interoperable and Reusable. And there are some key words that are important for sustainable digital research infrastructures. Next to FAIR, another important key factor is that research and research data should be open. Not only open access and open source, but also open data and even open science. So that's it, your data should not only be open, but also be FAIR. So I will briefly go through the FAIR principles, because they tell us something about what their websites or digital infrastructure for DH, for digital humanities, should be ideally support. And I will already put some references in there, how this can be targeted by TrueBall, more based on my experiences. So starting with the first Findable. So by the way, you see a link to this FAIR data principles here. They are on the website of 411. And generally spoken, FAIR is about knowledge discovery and sharing. So you may ask that Findable is easy to solve. But what I want to point out is that it's not so much about search engine optimization or some things. It's more about registering in domains or in domain specific resources. That means you need to know your community, you need to know where are the places, where data is stored or circulated and you will build interfaces to these websites so to share this data and put them into so-called harvesters. A good thing that happened is that since TrueBall 8 Core, the universally unique identifier inside the Core and are used, so that's a great step forward in respect to this Findable principle. Also the support of schema.org is a great step forward in respect to Findable. There's much more to say, but it's important that you have on your one hand metadata and that you on your other hand have really unique identifiers. So if you think about that your website vanishes, someone has to, there must be some place where you can refer to this data. The next point would be accessible. I guess TrueBall 8 API is a great benefit for this. Data principle. And I also guess that decoupled approaches will have a great impact on future DH projects. What is important here and what is a little bit missing is the sharing of license information, what is really a key factor for accessibility in this sense. Another big issue is the machine-to-machine communication. That means you want to have a semantic discovery of an API so that humans need to go there, understand the data model and so on. Instead, machines should get the information on the structure of the data that lies there. So a pointed out hydra, that's a W3C recommendation, could be a way to go in this direction. And that's a tricky one, interoperability. The question behind this is how to share a common language and a common language between different data pools, so to say. Coding the fair principles, fair also for machines as well as people, that would be the goal. And there's talk about ontologies and vocabulary. So that would need to talk about them, I guess, one hour or so. But the idea behind these ontologies and vocabulary is to create definitions or to describe the relations you do between the data that you created and the data coming from other sides. So I want to know if a person, where is the information of a person in a data set there, so to say. So it all leads to the semantic web. So the last one all comes to this re-usable. And some points here, metadata quality is important and user experience strategies are very important for this. Also this bi-directional API. So you also want to have possibilities to get data into your infrastructure, into your website. So that's, I guess, an issue that needs to be addressed in the future more. So coming to the roundup. Okay, I have one minute on my clock left. One minute, please, thanks. So we're talking about complex data models, we're talking about a sustainable workflow connecting websites, tools and methods. And I guess that's the place where Tupel comes into play also. It's more than content, it's about data and further usages. And what is really important is this out-of-box experience. The DH community needs to invest more into tailored Tupel modules, therefore. And as Theresa said yesterday, it's about ambitious digital experiences and in case of digital humanities, that's about complex and rich research data. And I guess Tupel is really a great tool for digital humanities. But we still need to find out where it's the best in the DH community. So thanks a lot and I hope it was, gave you some insights into this field and it was interesting for you. Thanks. It should work perfectly with, yeah, cool.