Researcher
Enterprise Information Systems
Fraunhofer IAIS

Profiles: LinkedInGoogle ScholarDBLP, Website

Room B3-236
Schloss Birlinghoven, 53757 Sankt Augustin, Germany
m…@cs.uni-bonn.de (click to get the full email address)

Short CV


Mohamed Nadjib Mami is a Researcher at the Enterprise Information Systems of the Fraunhofer IAIS.

Research Interests


  • Big Data
  • Data Management
  • Heterogeneous Databases
  • Linked Data

Projects


  • Big Data Europe
  • Ontario

Publications


2017

  • S. Auer, S. Scerri, A. Versteden, E. Pauwels, A. Charalambidis, S. Konstantopoulos, J. Lehmann, H. Jabeen, I. Ermilov, G. Sejdiu, A. Ikonomopoulos, S. Andronopoulos, M. Vlachogiannis, C. Pappas, A. Davettas, I. A. Klampanos, E. Grigoropoulos, V. Karkaletsis, V. de Boer, R. Siebes, M. N. Mami, S. Albani, M. Lazzarini, P. Nunes, E. Angiuli, N. Pittaras, G. Giannakopoulos, G. Argyriou, G. Stamoulis, G. Papadakis, M. Koubarakis, P. Karampiperis, A. N. Ngomo, and M. Vidal, “The BigDataEurope Platform – Supporting the Variety Dimension of Big Data,” in 17th International Conference on Web Engineering (ICWE2017), 2017.
    [BibTeX] [Abstract] [Download PDF]
    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,
    Title = {{T}he {B}ig{D}ata{E}urope {P}latform - {S}upporting the {V}ariety {D}imension of {B}ig {D}ata},
    Author = {S\"oren Auer and Simon Scerri and Aad Versteden and Erika Pauwels and Angelos Charalambidis and Stasinos Konstantopoulos and Jens Lehmann and Hajira Jabeen and Ivan Ermilov and Gezim Sejdiu and Andreas Ikonomopoulos and Spyros Andronopoulos and Mandy Vlachogiannis and Charalambos Pappas and Athanasios Davettas and Iraklis A. Klampanos and Efstathios Grigoropoulos and Vangelis Karkaletsis and Victor de Boer and Ronald Siebes and Mohamed Nadjib Mami and Sergio Albani and Michele Lazzarini and Paulo Nunes and Emanuele Angiuli and Nikiforos Pittaras and George Giannakopoulos and Giorgos Argyriou and George Stamoulis and George Papadakis and Manolis Koubarakis and Pythagoras Karampiperis and Axel-Cyrille Ngonga Ngomo and Maria-Esther Vidal},
    Booktitle = {17th International Conference on Web Engineering (ICWE2017)},
    Year = {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.},
    Bdsk-url-1 = {http://svn.aksw.org/lod2/Paper/ISWC2012-InUse_LOD2-Stack/public.pdf},
    Date-modified = {2012-12-02 12:25:29 +0000},
    Keywords = {group_aksw sys:relevantFor:infai sys:relevantFor:bis 2017 auer iermilov ngonga lehmann bde MOLE},
    Url = {http://jens-lehmann.org/files/2017/icwe_bde.pdf}
    }

  • K. Endris, M. Galkin, I. Lytra, M. N. Mami, M. Vidal, and S. Auer, “MULDER: Querying the Linked Data Web by Bridging RDF Molecule Templates.” 2017.
    [BibTeX] [Download PDF]
    @InProceedings{Endris2017,
    Title = {MULDER: Querying the Linked Data Web by Bridging RDF Molecule Templates},
    Author = {Kemele Endris and Mikhail Galkin and Ioanna Lytra and Mohamed Nadjib Mami and Maria-Esther Vidal and S{\"{o}}ren Auer},
    Year = {2017},
    Bdsk-url-1 = {https://www.researchgate.net/publication/318362785_MULDER_Querying_the_Linked_Data_Web_by_Bridging_RDF_Molecule_Templates},
    Crossref = {DEXA2017-1},
    File = {https://github.com/EIS-Bonn/Papers/blob/master/2017/DEXA_Mulder/MulderDEXA2017_CR.pdf},
    Numpages = {15},
    Pubs = {mgalkin,ilytra,endris,auer,vidal},
    Timestamp = {2017.10.12},
    Url = {https://www.researchgate.net/publication/318362785_MULDER_Querying_the_Linked_Data_Web_by_Bridging_RDF_Molecule_Templates}
    }

2016

  • M. N. Mami, S. Scerri, S. Auer, and M. -, “Towards Semantification of Big Data Technology,” in Big Data Analytics and Knowledge Discovery – 18th International Conference, DaWaK 2016, Porto, Portugal, September 6-8, 2016, Proceedings, 2016, pp. 376-390. doi:10.1007/978-3-319-43946-4_25
    [BibTeX] [Download PDF]
    @InProceedings{Mami2016,
    Title = {Towards Semantification of Big Data Technology},
    Author = {Mohamed Nadjib Mami and Simon Scerri and S{\"{o}}ren Auer and Maria{-}Esther Vidal},
    Booktitle = {Big Data Analytics and Knowledge Discovery - 18th International Conference, DaWaK 2016, Porto, Portugal, September 6-8, 2016, Proceedings},
    Year = {2016},
    Pages = {376--390},
    Publisher = {Springer},
    Bibsource = {dblp computer science bibliography, http://dblp.org},
    Biburl = {http://dblp.uni-trier.de/rec/bib/conf/dawak/MamiSAV16},
    Crossref = {DBLP:conf/dawak/2016},
    Doi = {10.1007/978-3-319-43946-4_25},
    File = {https://github.com/EIS-Bonn/Papers/raw/65f5ed535a8f7035e088653113f456837b332a09/2015/Semantifying_Big_Data/SEMANTiCS_2015_Research_Track_submission_107.pdf},
    Pubs = {mami,vidal,scerri,auer},
    Timestamp = {Mon, 08 Aug 2016 14:53:45 +0200},
    Url = {http://dx.doi.org/10.1007/978-3-319-43946-4_25}
    }