The management and analysis of large-scale datasets -- described with the term Big Data -- involves the three classic dimensions volume, velocity and variety.
While the former two are well supported by a plethora of software components, the variety dimension is still rather neglected.
We present the BDE platform -- an easy-to-deploy, easy-to-use and adaptable (cluster-based and standalone) platform for the execution of big data components and tools like Hadoop, Spark, Flink.
The BDE platform was designed based upon the requirements gathered from the seven societal challenges put forward by the European Commission in the Horizon 2020 programme and targeted by the BigDataEurope pilots.
As a result, the BDE platform allows to perform a variety of Big Data flow tasks like message passing (Kafka, Flume), storage (Hive, Cassandra) or publishing (GeoTriples).
In order to facilitate the processing of heterogeneous data, a particular innovation of the platform is the semantic layer, which allows to directly process RDF data and to map and transform arbitrary data into RDF.
%0 Conference Paper
%1 Auer+ICWE-2017
%A Auer, Sören
%A Scerri, Simon
%A Versteden, Aad
%A Pauwels, Erika
%A Charalambidis, Angelos
%A Konstantopoulos, Stasinos
%A Lehmann, Jens
%A Jabeen, Hajira
%A Ermilov, Ivan
%A Sejdiu, Gezim
%A Ikonomopoulos, Andreas
%A Andronopoulos, Spyros
%A Vlachogiannis, Mandy
%A Pappas, Charalambos
%A Davettas, Athanasios
%A Klampanos, Iraklis A.
%A Grigoropoulos, Efstathios
%A Karkaletsis, Vangelis
%A de Boer, Victor
%A Siebes, Ronald
%A Mami, Mohamed Nadjib
%A Albani, Sergio
%A Lazzarini, Michele
%A Nunes, Paulo
%A Angiuli, Emanuele
%A Pittaras, Nikiforos
%A Giannakopoulos, George
%A Argyriou, Giorgos
%A Stamoulis, George
%A Papadakis, George
%A Koubarakis, Manolis
%A Karampiperis, Pythagoras
%A Ngomo, Axel-Cyrille Ngonga
%A Vidal, Maria-Esther
%B 17th International Conference on Web Engineering (ICWE2017)
%D 2017
%K 2017 MOLE auer bde group_aksw iermilov jabeen lehmann ngonga sejdiu
%T The BigDataEurope Platform - Supporting the Variety Dimension of Big Data
%U http://jens-lehmann.org/files/2017/icwe_bde.pdf
%X The management and analysis of large-scale datasets -- described with the term Big Data -- involves the three classic dimensions volume, velocity and variety.
While the former two are well supported by a plethora of software components, the variety dimension is still rather neglected.
We present the BDE platform -- an easy-to-deploy, easy-to-use and adaptable (cluster-based and standalone) platform for the execution of big data components and tools like Hadoop, Spark, Flink.
The BDE platform was designed based upon the requirements gathered from the seven societal challenges put forward by the European Commission in the Horizon 2020 programme and targeted by the BigDataEurope pilots.
As a result, the BDE platform allows to perform a variety of Big Data flow tasks like message passing (Kafka, Flume), storage (Hive, Cassandra) or publishing (GeoTriples).
In order to facilitate the processing of heterogeneous data, a particular innovation of the platform is the semantic layer, which allows to directly process RDF data and to map and transform arbitrary data into RDF.
@inproceedings{Auer+ICWE-2017,
abstract = {The management and analysis of large-scale datasets -- described with the term Big Data -- involves the three classic dimensions volume, velocity and variety.
While the former two are well supported by a plethora of software components, the variety dimension is still rather neglected.
We present the BDE platform -- an easy-to-deploy, easy-to-use and adaptable (cluster-based and standalone) platform for the execution of big data components and tools like Hadoop, Spark, Flink.
The BDE platform was designed based upon the requirements gathered from the seven societal challenges put forward by the European Commission in the Horizon 2020 programme and targeted by the BigDataEurope pilots.
As a result, the BDE platform allows to perform a variety of Big Data flow tasks like message passing (Kafka, Flume), storage (Hive, Cassandra) or publishing (GeoTriples).
In order to facilitate the processing of heterogeneous data, a particular innovation of the platform is the semantic layer, which allows to directly process RDF data and to map and transform arbitrary data into RDF.},
added-at = {2024-06-18T09:44:14.000+0200},
author = {Auer, S\"oren and Scerri, Simon and Versteden, Aad and Pauwels, Erika and Charalambidis, Angelos and Konstantopoulos, Stasinos and Lehmann, Jens and Jabeen, Hajira and Ermilov, Ivan and Sejdiu, Gezim and Ikonomopoulos, Andreas and Andronopoulos, Spyros and Vlachogiannis, Mandy and Pappas, Charalambos and Davettas, Athanasios and Klampanos, Iraklis A. and Grigoropoulos, Efstathios and Karkaletsis, Vangelis and de Boer, Victor and Siebes, Ronald and Mami, Mohamed Nadjib and Albani, Sergio and Lazzarini, Michele and Nunes, Paulo and Angiuli, Emanuele and Pittaras, Nikiforos and Giannakopoulos, George and Argyriou, Giorgos and Stamoulis, George and Papadakis, George and Koubarakis, Manolis and Karampiperis, Pythagoras and Ngomo, Axel-Cyrille Ngonga and Vidal, Maria-Esther},
bdsk-url-1 = {http://svn.aksw.org/lod2/Paper/ISWC2012-InUse_LOD2-Stack/public.pdf},
biburl = {https://www.bibsonomy.org/bibtex/2636db7e1eb2265f6409e63d200b80438/aksw},
booktitle = {17th International Conference on Web Engineering (ICWE2017)},
date-modified = {2012-12-02 12:25:29 +0000},
interhash = {35ebe3557a9ee8b815995f852dc9ebdb},
intrahash = {636db7e1eb2265f6409e63d200b80438},
keywords = {2017 MOLE auer bde group_aksw iermilov jabeen lehmann ngonga sejdiu},
timestamp = {2024-06-18T09:44:14.000+0200},
title = {{T}he {B}ig{D}ata{E}urope {P}latform - {S}upporting the {V}ariety {D}imension of {B}ig {D}ata},
url = {http://jens-lehmann.org/files/2017/icwe_bde.pdf},
year = 2017
}