Distributed Semantic Analytics

Posted on: Fri, 06/18/2021 - 14:21 By: valentina.janev

This module will cover the needs and challenges of distributed analytics and then dive into the details of scalable semantic analytics stack (SANSA) used to scalable analytics for knowledge graphs. This module will cover the setup, Apis and different layer of SANSA. At the end of this module, the audience will be able to execute examples and create programs that use SANSA APIs.



Posted on: Wed, 05/12/2021 - 16:24 By: valentina.janev

U ovoj lekciji biće opisani principi funkcionisanja semantičkog veba. Definisaće se značenja ontologija, taksonomija I ostalih izraza koji se često koriste. Praktična upotreba ovih tehnologija biće pokazana korišćenjem alata GraphDB kompanije Ontotext. Kroz primate u alatu GraphDB biće objašnjeno kako se pišu upiti za pretraživanje informacija u bazama podataka korišćenjem jezika SPARQL. Grafovi znanja I povezani podaci biće objašnjeni korišćenjem ovog alata.

Using Semantic Web technologies in the public sector

Posted on: Wed, 05/12/2021 - 15:55 By: valentina.janev

The process of providing cross-border public services across EU Member States is complex, due to the heterogeneity of the actors, information and services of the different Member States. The complexity of exchanging data may lead to semantic interoperability conflicts. The Core Vocabularies can be used to reduce these semantic conflicts in two ways:

DBpedia and the Serbian Language Chapter

Posted on: Wed, 05/12/2021 - 15:46 By: valentina.janev

Linked Open Data is a pragmatic approach for realizing the Semantic Web vision of making the Web a global, distributed, semantics-based information system. Linked Data technology matured significantly in the past few years. Automatic linking, extraction, mapping, and visualization of RDF data became mainstream technology provided by mature open-source software components. A vast number of small and large Linked Data resources, including DBPedia, now amounts to over 50 billion triples in total.

DCAT Application profile

Posted on: Wed, 05/12/2021 - 15:38 By: valentina.janev

The aim of this work is to present the DCAT Application Profile (DCAT-AP) standard which in turn is derived from the W3C DCAT standard. DCAT is an RDF vocabulary designed to facilitate interoperability between data catalogs published on the Web and also represent a way to provide context or metadata for datasets.

Apache Hadoop

Posted on: Wed, 05/12/2021 - 15:05 By: valentina.janev

Ova lekcija opisuje softversko okruženje za obradu velikih količina podataka Apache Hadoop, njegove komponente koji upotpunjavaju i proširuju mogućnosti Hadoop-a, kao i njegovo korištenje u praksi. Da bismo u potpunosti razumeli prednosti Hadoop-a, potrebno je sagledati najpre razliku između paralelnog i distribuiranog računanja, načine čuvanja (HDFS arhitekturu), upravljanje resursima i procesiranja podataka, princip horizontalne skalabilnosti, itd.

Integrated Energy Value Chains - Overview of Technologies and Lessons Learned

Posted on: Mon, 04/26/2021 - 11:54 By: valentina.janev

The European electricity system undergoes significant changes driven by the European Union (EU) common rules for the internal market for electricity, as well as by the climate action agenda. The European Green Deal is also an opportunity for modernizing the energy system in order to make it competitive and sustainable with regard to the environment.

Cognitive Conversational Assistants

Posted on: Tue, 12/22/2020 - 09:02 By: valentina.janev

Artificial Intelligence (AI) is the pinnacle of digitalization; AI is revolutionizing how we work and live. We now have more data than ever about our business processes, and Deep Learning, in particular, gives us the tools to create real value from our data. With AI, we can improve our processes' efficiency; we can improve quality or do completely new things by creating new business models. With AI, computers can understand audio and text in natural language, allowing them to create new user experiences.

Survey on Big Data Tools

Posted on: Thu, 06/11/2020 - 09:53 By: valentina.janev

This introductory lecture discusses the Big Data processing pipeline and the Big Data Landscape from the following perspectives

  • Big Data Frameworks
  • NoSQL Platforms and Knowledge Graphs
  • Stream Processing Data Engines
  • Big Data Preprocessing
  • Big Data Analytics
  • Big Data Visualization Tools.
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