 Thank you for your interest in this talk. My name is Torsizio. I'm a knowledge representation manager at the Swiss Institute of Bifematics. CIB is a federation of bifematic research and service groups. I would like today to talk about how to boost your research with CIB semantic web of data on behalf of the CIB RDF group members. First I will give you an overview about the CIB databases, but the target audience of this talk are biologists and bifematicians. Here you can see actually a non-exhaustive list of the CIB database. They contain knowledge that spends several domains in life science, such as gene expression, protein, protein-protein interactions, metabolic networks. In the past years under the umbrella of CIB these resources have been working together to improve their interoperability at different levels, from cross-reference among resources to semantic search over them. Then during this collaboration between these different groups at the Swiss Institute of Bifematics we came from data silos for semantic web of data, especially the advanced semantic search is thanks to the fact that this database built and maintained a highly interlinked semantic web of data infrastructure actually. For example in the past these databases could only be carried individually if the user wanted to to answer research questions that needed more than one resource, like for example here in this illustration a question that would require like a BG, RIA, and Unicrot database but maybe also WIC data, it would require to carry them individually each database and for and then manually aggregate or combine these data from these multiple sources actually. This can be like a fastidious work and alternatively maybe to automate it, a Bifematician could call some script but with the higher cost of developing it and maybe it's not necessary would be straightforward or possible. Now with this semantic web of data of Sib it's possible for the user from one database such as here like Unicrot to carry not only its data but also the data of others Sib database including external ones such as WIC data and actually by doing that it results in integrated data retrieval from multiple data sources to answer a given questions of query of the user. For instance if we want to combine Unicrot and WIC data to answer this question what are the positions of the EPP gene in the human genome knowing that this gene is cause can cause a form of Alzheimer's disease, this information comes from Unicrot and to know the position in a given in the human genome we do require for example to carry to combine it and carry WIC data resulting in knowing that these genes is located in the 21 chromosome but also the exact position in different genome assemblies as you can see here in the table. Then now I will give you a technical overview how we federate these Sib databases in more details. Then what I have done to implement this semantic web of data at the system of mathematics is was to make them respect the same language to be able to carry those different database with the same technical query language and the query language chose was Sparkle. For that purpose what we have done it was each individual Sib database have developed their own Sparkle endpoint. What's a Sparkle endpoint? It's a point of presence on the web that's capable of receiving processing Sparkle protocol requests. Then by doing that we are able to carry the data of these multiple databases with the same exactly the same query language. Then currently we have the 12 Sparkle endpoints as you can also check more information about them at the Xpazee website. Here I provide you a list of the different web address of the Sparkle endpoints of Sib. Those links are available in the description of the YouTube video. Here you can find detailed information about the different documentations and tutorials of each Sib Sparkle endpoint that can be used as a source of information to know how to carry the different Sparkle endpoints but also how to build queries across those different resources. We also provide several examples of federated queries that are the queries that goes across several resources. These links are available in the YouTube description as well of this video. As final remarks I would like to invite you to check our latest published article in the Nucleic Ask the Research Journal entitled the Sibs with Tutorial by Informatics and Medical Web of Data. As a future work that actually we started working on it to give you a hint is that we are developing the Xpazee.org chat tip like searching team over those Sib Sparkle endpoints. It means that the user won't need to know how to write Sparkle queries to be able to answer the questions and retrieve the data that they are looking for from these different databases. Thank you very much for your attention. If you have any questions please feel free to contact us and our e-mail us. Thank you.