DATEXIS at the Beuth University is part of the following internationally recognized initiatives:
NOHATE: Overcoming crises in public communication about refugees, migration, foreigners (2018)
More and more frequently, discussions turn to so-called Hate Speech – offensive and hateful posts by individual users – when divisive issues come up in social media or online commentary sections. Without sufficient moderation, this hate speech can quickly lead to an escalation or inhibition of discussions. Therefore, operators of such platforms are advised to identify and moderate this hateful communication. However, due to the large amounts of data and rapidity of communication, this proves elusive. Especially the discussion about the accommodation of refugees since 2015 strengthened the assumption that hate speech in social media does not only pose a threat for individuals but also for society as a whole since hateful communication can be linked to the political advancement of right-wing extremist parties, political apathy, and racist crimes.
The three-year joint project NOHATE aims to analyse hateful communication on social media platforms, in online forums and commentary sections in order to identify underlying causes and dynamics as well as develop methods and software for (early) recognition of hateful communication and potential strategies for de-escalation. A case study will offer a multidimensional perspective on displacement and migration and provide data for software development.
The partners in the joint project are Freie Universität Berlin, Beuth University of Applied Sciences Berlin and VICO Research & Consulting. The project is funded by the Federal Ministry of Education and Research (BMBF) within the context of the funding initiative "Strengthening solidarity in times of crises and change".
You can find further information about the project here.
H2020: FashionBrain - Understanding Europe's Fashion Data Universe (2017-2019)
The primary goal of each retailer is to “understand your customers”. Our interviews with retailers show a primary demand from the retail industry for predicting a customer's next demand. Surprisingly , even a complete record of past purchases (and returns) is not sufficient to understand how items in a company's catalog do or do not connect with the customer's general tastes, lifestyle and aspirations. Moverover, from a business perspective, any efficiency gains in the logistics of supplier management, shipping and handling are rather minor, compared to the gains one could obtain from a better understanding of the customers’ personalities and habits. Given that the customer demands trigger proactive stocking and fashion production, this appears as a logical consequence.
In this project, we want to consolidate and extend existing European technologies in the area of database management, data mining, machine learning, image processing, information retrieval, and crowdsourcing to strengthen the positions of European fashion retailers among their world-wide competitors. Our choice for the fashion sector is a concise one: i) as a multi-billion euro industry, the fashion sector is extremely important for the European economy; ii) Europe already has a solid position in the world fashion stage, however, to maintain its position and keep up with the competitors, European fashion industry needs the help of advanced technology; and iii) European fashion industry provides an excellent exercise for new technologies, because it is a multi-sectorial by itself (i.e., imposes challenging data integration issues), it has a short life-cycle (i.e., requires timely reaction to the current events) and it involves diverse languages and cultures.
The main outcome of the FashionBrain project is the improvement of the fashion industry value chain obtained thanks to the creation of novel on-line shopping experiences, the detection of influencers, and the prediction of upcoming fashion trends. Tangible outcomes will include software, demonstrators, and novel algorithms for a data-driven fashion industry.
BITKOM: Excellence in Big Data (2016)
Germany's Industry and Government want to promote digitization in Germany and increase Germany's attractiveness for digital technologies. This means presenting Germany's expertise in key technology areas internationally. Bitkom, Smart Data Forum and Germany Trade & Invest have jointly presented the report "Germany – Excellence in Big Data", which aims to do this. The report is aimed at an international audience and presents more than 30 scientific organizations, over 60 technology vendors and more than 40 Big Data users with their research priorities, projects and strategies or products and services Industry overviews complete the picture. This report provides interested parties with the most comprehensive overview of the Big Data landscape in Germany.
The Data Science Group at Beuth University of Applied Sciences is featured in the list of individual researchers and research groups at universities who are working on Big Data.
Germany: Funding for MACSS in BMWi Smart Service World (2016-2018)
The research group DATEXIS acquired funding for one project in the Smart Service World programm.
Medical Allround-Care Service Solution (MACSS). Goal of MACSS is a protypical health plattform hosted with Charite Berlin. The plattform manages patient related data after a kidney surgery. Currently, this data is often still managed "on paper" and in silos. The MACSS plattform will integrate medical device indicators for vital data with text data from the patient's diary and the anamnesis. As a result, doctors at Charite but also in the field or medical staff in a kidney dialysis center might recieve a fresh and comprehensive picture about the patients conditions and can support the patient with asnychroneuous and prompt therapy adjustments. DATEXIS will focus on interactive text data management in a shared memory database in this project from 2016 till 2019. [More]
Germany: 2x Funding in Smart Data Program (BMWi) (2015-2018)
The research group DATEXIS acquired funding for two projects in the Smart Data programm.
Knowledge Web for the German Industry. The Smart Data Web project is lead by the DFKI Berlin (Hans Uszkoreit). This vision is to establish first a Knowledge Web, such as Freebase or DBPEDIA, but suitable for data value chains for Germans core industries, such as automotive, engineering and chemistry. Alexander Löser and Petra Sauer from the Beuth University are principal investigators in this prestigous project from 2015 to 2018 . DATEXIS focuses on scalable in-data-base text mining in a shared nothing data base
ExCELL - Improve B2B Logistics im German Cities with Data. The ExCELL project (lead by FeldM consulting) has the goal of optiimizing free logistic resources, in particluar for transporting goods and for small and medium sized carriers and customers. The team will analyze and unreavel common patterns in data from mobile devices, from communities and from public traffic sensors with the goal of providing new logistic services. Petra Sauer and Alexander Löser from the Beuth University are principal investigators in this prestigous project from 2015 to 2018.
Germany: Berlin Big Data Center (BMBF)
The Federal Ministry of Education and Research (BMBF) will establish new research on Big Data and IT security in Germany. The Technical University of Berlin (Prof. Volker Markl) leads one of the two competence centers founded by the BMBF.
The Beuth University of Applied Science is full member of this initiative called "Berlin Big Data Center (BBDC). It is the only University of Applied Sciences in Germany that was elected to participate in this highly visible initiative of the BMBF. [more information]