Inspiring results at the HPI Hackathon 2019 about://social.good in Potsdam

Inspiring results at the HPI Hackathon 2019 about://social.good in Potsdam ( -- impressive prototypes generated in less than a day around IBM-sponsored challenges on fake news detection and visualizations of cross-border conflict. Had a great time sponsoring the event with Matthias Bracht & Frank Hamburger.

Hackathon results are here: with IBM challanges as follows:

  • Team "Unbounded" (Challenge cross-border conflict):
  • Team "Blackbox" (Challenge fake news)
  • Team "Refugee Movement: Cause and Effect" (Challenge cross-border conflict)
  • Team "Terror X Africa" (Challenge cross-border conflict)

Impressions from HackHPI 2019

BDSDST 2017 : 3rd International Workshop on Big Data, Smart Data and Semantic Technologies

Call for Papers: Consider submitting to the 3rd International Workshop on Big Data, Smart Data and Semantic Technologies, co-located with the INFORMATIK 2017 conference in Chemitz, Germany. The workshop proceedings are to be published in the (electronic) Lecture Notes in Informatics (LNI).

I am participating on the programme committee.

From the CfP:

The focus of the workshop BDSDST 2017 will be on the potential of Big Data, Smart Data and semantic technologies in different application areas. The workshop aims to bring together researchers and practitioners using Big and Smart Data in combination with semantic technologies or planning to enrich existing data processing infrastructures with semantic information.


The workshop covers diverse application areas of Big Data, Smart Data and semantic technologies, such as transport logistics, Supply Chain Management, Smart Factory, traffic flow, emission and energy consumption modelling, analytics, simulation and visualization, public transportation, complex event processing, machine learning, mobile information systems, geo-information systems, smart services and many more.

Special Issue on Stream Processing, Call for Papers

Another call for papers: the Journal of Web Semantics invites submissions to a special issue on Stream Processing to be edited by Monika Solanki and Jean-Paul Calbimonte. Submissions are due by 1st July 2015.

(I am on the Programme Committee.)

Important Dates and Submission Guidelines

From the call:

[...] we expect submissions on (but not restricted to) the following topics.

Processing RDF Data Streams
    Producing and consuming streams of RDF graphs
    Modelling streams of structured data
    Theoretical modelling of RDF streams
    Automatic annotation of raw data streams
    Processing noisy data, uncertainty, incomplete information
    Semantic mining of RDF data streams
    Mechanisms for integrating historical data with streaming data
    Publishing Linked Stream Data
Querying semantic streams of data
    Extensions to SPARQL for data streams
    Complex event processing on semantic data
    Ontology-based data access to data streams
    Data dynamics, update, and synchronization
    Optimisation of stream query processing
    Correctness of stream query processing
    Synthetic RDF streams and benchmarking
Reasoning with data streams
    New stream reasoning algorithms
    Incremental reasoning on dynamic ontologies
    Temporal logics for reasoning over Semantic streams
    Multicore scalable stream reasoning
Applications of stream processing
    Semantic sensor networks
    Social network streams and microposts
    Stream processing in the Internet of Things
    Smart cities
    Activity streams

Workshop on Situation Recognition (SIREMTI2015)

UPDATE 2: The deadline for submissions was extended to 30th September, 2015.

UPDATE: The workshop was relocated to MobiCASE2015 conference in November 2015, Berlin, Germany. The deadline for submissions is currently 11th September 2015.

(I am on the Programme Committee.)

Important dates and submission information: Workshop Homepage

From the CfP:

This workshop aims at merging research works relevant to mining temporal information from any kind of data with a special focus on (but not limited to) the following methods:

  • Trend Mining
  • Temporal Data Mining
  • Topic Mining and Mining of Users Posts
  • Data-based Situation Recognition
  • Intelligent Situation Recognition
  • Wireless Data Mining
  • Signal Detection and Analysis
  • Complex Event Processing and Messaging Analytics
  • Semantic Complex Event Processing
  • Data Stream Processing
  • Data Mining on Streaming Data
  • Semantic Technologies for Situation Recognition

Streaming System Benchmarks

Streaming systems are complex; apart from correct functionality (which might differ between implementations and vendors) many non-functional aspects can be benchmarked such as memory comsumption, latency, and throughput. For RDF Stream Processing several benchmarks exist, shown as follows. From data stream management, older benchmarks exist which are not specific to RDF data but might be adapted. Some are listed below.

RDF Stream Benchmarks

Other Stream or CEP Benchmarks

  • BEAST 4
  • NEXMark 5
  • Linear Road 6
  • BiCEP 7 - a benchmarking framework
  • Fast Flower Delivery (FFD) 8 - a functional benchmarking scenario

  1. Zhang, Y.; Duc, P.; Corcho, O. & Calbimonte, J.-P. SRBench: A Streaming RDF/SPARQL Benchmark The Semantic Web –- ISWC 2012, Springer Berlin Heidelberg, 2012, 7649, 641-657 ↩︎

  2. Dell’Aglio, D.; Calbimonte, J.-P.; Balduini, M.; Corcho, O. & Della Valle, E. On Correctness in RDF Stream Processor Benchmarking. The Semantic Web – ISWC 2013, Springer Berlin Heidelberg, 2013, 8219, 326-342 ↩︎

  3. Le-Phuoc, D.; Dao-Tran, M.; Pham, M.-D.; Boncz, P.; Eiter, T. & Fink, M. Linked Stream Data Processing Engines: Facts and Figures. The Semantic Web – ISWC 2012, Springer Berlin Heidelberg, 2012, 7650, 300-312 ↩︎

  4. Geppert, A.; Berndtsson, M.; Lieuwen, D. & Roncancio, C. Performance evaluation of object-oriented active database systems using the BEAST benchmark. Theor. Pract. Object Syst., John Wiley & Sons, Inc., 1998, 4, 135-149 ↩︎

  5. Tucker, P.; Tufte, K.; Papadimos, V. & Maier, D. NEXMark - A benchmark for querying data streams. Oregon Health & Sciences University, 2002 ↩︎

  6. Arasu, A.; Cherniack, M.; Galvez, E.; Maier, D.; Maskey, A. S.; Ryvkina, E.; Stonebraker, M. & Tibbetts, R. Linear road: a stream data management benchmark. VLDB '04: Proceedings of the Thirtieth international conference on Very large data bases, VLDB Endowment, 2004, 480-491 ↩︎

  7. Bizarro, P. BiCEP - Benchmarking Complex Event Processing Systems Event Processing, Internationales Begegnungs- und Forschungszentrum für Informatik (IBFI), Schloss Dagstuhl, Germany, 2007 ↩︎

  8. Etzion, O. & Niblett, P. Event Processing in Action Manning Publications Co., 2010 ↩︎