Belgrade BDA School (Sustainability Plan)

Posted on: Wed, 04/15/2020 - 20:45 By: valentina.janev

This report presents a plan for sustaining LAMBDA open education and training activities. One of the major knowledge transfer events of the LAMBDA project is the Belgrade Big Data Analytics Summer School, hence the activities necessary for organizing the next editions of the Belgrade Big Data Analytics Summer School are presented. Additionally, the efforts and investments needed for sustaining this event in the short and medium term (5-7 years) are presented.

 

Quality control, risk management and self-assessment (Report)

Posted on: Wed, 04/15/2020 - 20:42 By: valentina.janev

The LAMBDA project started in July 2018 with a primary objective to Strengthening the Human capital and Education, Research and Development capacities of “Mihajlo Pupin” Institute, the leading Serbian R&D institution in information and communication technologies in order to serve as a Big Data & Analytics HUB that connects and integrates scientists and professionals from the West Balkans and the entire region into the European Research Area.

Survey on Big Data Applications

Posted on: Wed, 04/01/2020 - 21:11 By: valentina.janev

The goal of this chapter is to shed light on different types of big data applications needed in various industries including healthcare, transportation, energy, banking and insurance, digital media and e-commerce, environment, safety and security, telecommunications, and manufacturing. In response to the problems of analyzing large-scale data, different tools, techniques, and technologies have bee developed and are available for experimentation.

SANSA - Scalable Semantic Analytics Stack

Posted on: Wed, 04/01/2020 - 20:59 By: valentina.janev

The size of knowledge graphs has reached the scale where centralised analytical approaches have become infeasible. Recent technological progress has enabled powerful distributed in-memory analytics that have been shown to work well on simple data structures. However, the application of such distributed analytics approaches on semantic knowledge graphs lags significantly behind. To advance both scalability and accuracy of large-scale knowledge graph analytics to a new level, foundational research on methods leveraging distributed in-memory computing and semantic technologies in combination w

Context-Based Entity Matching for Big Data

Posted on: Wed, 04/01/2020 - 20:55 By: valentina.janev

In the Big Data era, where variety is the most dominant dimension, the RDF data model enables the creation and integration of actionable knowledge from heterogeneous data sources. However, the RDF data model allows for describing entities under various contexts, e.g., people can be described from its demographic context, but as well from their professional contexts. Context-aware description poses challenges during entity matching of RDF datasets the match might not be valid in every context.

Data Lakes and Federated Query Processing

Posted on: Wed, 04/01/2020 - 20:54 By: valentina.janev

Big data plays a relevant role in promoting both manufacturing and scientific development through industrial digitization and emerging interdisciplinary research. Semantic web technologies have also experienced great progress, and scientific communities and practitioners have contributed to the problem of big data management with ontological models, controlled vocabularies, linked datasets, data models, query languages, as well as tools for transforming big data into knowledge from which decisions can be made.

Big Data Ecosystem

Posted on: Wed, 04/01/2020 - 20:44 By: valentina.janev

The rapid development of digital technologies, IoT products and connectivity platforms, social networking applications, video, audio and geolocation services has created opportunities for collecting/accumulating a large amount of data. While in the past corporations used to deal with static, centrally stored data collected from various sources, with the birth of the web and cloud services, cloud computing is rapidly overtaking the traditional in-house system as a reliable, scalable and cost-efective IT solution.

Subscribe to