This lecture will cover the existing advanced Big Data architectures following a bottom-up approach. In this lecture, the important knowledge to design and architect scalable solutions for challenging problems will be introduced. The primary components in the architecture of such systems and their architectures will be presented and discussed including “inter alia distributed kernels” and cluster managers, distributed file systems and storage systems.
The LAMBDA project is delighted to announce the Big Data Analytics Summer School 2019, that will take place at the Mihajlo Pupin Institute in Belgrade from 18 to 20 June 2019. Please see the promotional video here.
The LAMBDA project is delighted to announce the Big Data Analytics Summer School 2020, which will be organized on 16 and 17 of June 2020.
Due to COVID-19, the event will be held ONLINE. The event will sustain the activities of the Big Data Analytics Summer School, Belgrade, Serbia, June 2019.
9th International Conference on Information Society and Techology will be held on Kopaonik, Serbia on Mar 10-13, 2018.
The ICIST Conference series is one of the top IT scientific events in Serbia and the region, with 70-100 papers presented each year, average of 200 participants per edition, attended also by the number of IT industry representatives in the region.
The ICIST Special Track on Semantic technologies for Big Data will raise discussion on:
Prof. Sanja Vraneš has been invited to participate in the newly established group for development of Artificial Intelligence Strategy for Serbia, see https://pcpress.rs/formirana-radna-grupa-za-izradu-strategije-razvoja-vestacke-inteligencije-u-srbiji/
The main goal of this ESWC research track is bringing together the communities relying on semantic approaches for representation, mining, analysis, and visualization of research outputs, such as papers, data, software, experiments, vocabularies, workflows, patents, and others, irrespective of the context of the research, whether academia, industry, or government. In broad terms, the themes of this Research of Research track are: (a) semantic representation of research outputs, i.e.
LAMBDA training materials will include different algorithms and tools related to Distributed Semantic Analytics, Semantic Question Answering, Structured Machine Learning, Deep Learning, Software Engineering for Data Science, Semantic Data Management, Knowledge Extraction and Validation.
LAMBDA training materials will include approaches for better supporting the variety dimension of Big Data comprising RDF, RDF-Schema and OWL knowledge representation formalisms, mapping standards such as R2RML, JSON-LD and CSVW, the SPARQL query language etc. Integrating semantic and Big Data technologies can help making Big Data architectures and applications more flexible, adaptive and their implementation more efficient.
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 809965.
