 Thank you everyone. I'm so glad to hear the speech. Vivian just talked about open source and open data. And now I'm going to talk about more specific about what is open source and open data technologies we are using to build a real product. Okay, so first thing I want to introduce about myself. I am from GNOME community. I found GNOME Asia in 2008. I'm a member of GNOME Foundation. And I have been served as a Foundation Board member in 2010. And now I have found open source alliance which is called Kaiyuan Shui in China. And also I have been working in SAM Oracle for eight years and now I'm working for Microsoft Open Technologies. Okay, so today I'm going to talk about the background of the government's open data and talk about the open standards which is of data and open source portal for open data which is SCAN. And I will go through the architectures of the open data platform. And also there are some showcase in China. Okay, so for the open data defined which makes public data broadly accessible and usable by human beings. I think this open data movement is quite popular these years and it created lots of opportunities for new startup and for the whole society and the economies. Here is the open data around the world. I think more than 180 governments have been used open data platform. For example, the Singapore government. So here we talk about the open source data portal platform, SCAN. So SCAN is an open source project developed by the Open Knowledge Foundation. And it is under the license AGPL. And there are some open data side examples. For example, the UK, the UK.gov and the USA data.gov. And I think the Singapore government have used another platform and solutions. I will be very interested to investigate more of Singapore government models. And so we talk about the open standards. And so for the open standards, all data we have to talk about. So opening data siders through all data protocol. And all data protocols have been approved by OSS. Currently it's a standard which is proposed by the Microsoft IBM and SAP and some other companies. And we talk about how we use open source projects like SCAN. And open standards, all data. And also cloud to build open data platform. So in China, the Microsoft of the technologies, we have been working on this. We contribute to the open source projects. For example, we have developed the OData plugin for SCAN. And now the code has been published to GitHub. And also we have created OData plugins like JDBC. And the OData producers for SuperCIMs. Those are already published in GitHub. And for the SCAN, which is open source projects, we have been uploading images to VM Depot. And VM Depot is a community gallery which contains lots of open source Linux images. And it is maintained by the community. And we have projects, we are doing projects with Chinese government. And also for Microsoft, it powered up Azure. And for the open data platform, ecosystem is really important. We have four research party companies, like Driegel, which is the tier one data providers. Now already support OData API. And we work closely with OData community. And also we are thinking about to encourage more people to develop useful applications for human beings using those open data. So a very useful way is to organize national open data context. Here is the open data platform architectures. Generally, there are three parts. On the left is the data input. In the middle is processed data. And output displays the data. So for the raw data, it can be the data on the paper. It can be Excel. It can be a dynamic data site and the static data website. So there are many ways we have to deal with this data. And also in the central, there are data processing. There are many modules there. And finally, we have to make those data visible to human beings. I'm not going to go through the details because I only have 10 minutes. Okay, here is some function review of the open data platform. That is like the data import. Just the three steps. We create data states. And we import data and then we complete data. So currently it supports micro documents format like Word, Excel, CSV, JPGs. Those are the popular format we use every day. And there are, for the functions, in the left hand, you can cure the data states in different categories. So you can search by the organization groups, tabs, attributions. And in the middle, you can click on the GUI to see the data states organizations and the groups. And also you can search. You can full text search and the fuzzing match. Okay, so data virtualization, how to make it visible to human being. We take the geography information size as an example. When data entry contains some geography information like latitudes and longitudes. So this open data platform, we are automating the generated map applications. Look at the left side. It's not clearly. So the left part is latitudes and the longitude down the right corner. And then in the right part, it will automatically generate map applications. So this open data platform supports basic charting tools like Power BI like Tabloon. Okay, so currently the Chinese government has been building some open data portals while working on this. This is going to be released in April. And we offer the platform solution to them. And also we're working with many third party companies to make applications based on those data. So I think that for the open data there are three big major parts. The first one is the source of the data, which is government openings. And then we need a solution to build the platform. And then how can we use those data? There is an ecosystem. There are developers from the communities. There are startups. There are console companies that are doing business in this part. So I think that these parties have lots of opportunities. Okay, so there are some useful things. And there is a team in MS Open Tech in China. And our teams are generally three parts. That's open standards and engineering and open source. So if you have any questions, if you want to know more about this open data platform, so please drop us an email. Okay, thank you. Thank you.