Contents on www.roland-stuehmer.de

Efficiently unlock secondary KeePass databases when working with shared password safes

Tue, 28 Nov 2023 20:35:16 +0100

Keepass can open multiple databases simultaneously on tabs. This is useful e.g. when maintaining one personal database and one or more further databases e.g. shared with different teams or projects. When auto-typing passwords or using browser plugins, all open databases are searched, thus passwords can reside in their original database without having to be duplicated.

When unlocking multiple databases you can avoid typing several passwords for several databases: you can store one entry for each shared database in your first database which you will unlock first. Keepass Triggers can then automatically unlock the shared databases on tabs with their paths and passwords from the first database. All securely encrypted. Field references are used to get the data from the first database into the triggers without hardcoding the triggers.

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

Thu, 20 Jun 2019 21:15:00 +0200

Inspiring results at the HPI Hackathon 2019 about://social.good in Potsdam (https://hackhpi.org) – 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: https://hackhpi2019.devpost.com/ with IBM challanges as follows:

Team “Unbounded” (Challenge cross-border conflict): https://devpost.com/software/unbounded-8atfvy
Team “Blackbox” (Challenge fake news) https://devpost.com/software/blackbox-f39vit
Team “Refugee Movement: Cause and Effect” (Challenge cross-border conflict) https://devpost.com/software/refugee-movement-cause-and-effect
Team “Terror X Africa” (Challenge cross-border conflict) https://devpost.com/software/hackhpi-ibm-crossborder

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

Mon, 27 Feb 2017 14:44:10 +0100

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).

Workshop homepage: https://informatik2017.de/ws27-bdsdst-2017/
WikiCfP call for papers: http://www.wikicfp.com/cfp/servlet/event.showcfp?eventid=60851

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

Mon, 08 Jun 2015 23:26:54 +0200

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
    Gamification

Workshop on Situation Recognition (SIREMTI2015)

Fri, 10 Apr 2015 14:04:50 +0200

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

Wed, 01 Apr 2015 19:36:43 +0200

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

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 ↩︎
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 ↩︎
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 ↩︎
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 ↩︎
Tucker, P.; Tufte, K.; Papadimos, V. & Maier, D. NEXMark - A benchmark for querying data streams. Oregon Health & Sciences University, 2002 ↩︎
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 ↩︎
Bizarro, P. BiCEP - Benchmarking Complex Event Processing Systems Event Processing, Internationales Begegnungs- und Forschungszentrum für Informatik (IBFI), Schloss Dagstuhl, Germany, 2007 ↩︎
Etzion, O. & Niblett, P. Event Processing in Action Manning Publications Co., 2010 ↩︎

RDF Stream Processing Workshop at ESWC2015, Call for Papers

Fri, 23 Jan 2015 15:18:04 +0100

In conjunction with the 12th Extended Semantic Web Conference (ESWC 2015). May 31th, 2015 in Portoroz, Slovenia.

From the Call for Papers:

The goal of this workshop is to bring together interested members of the community to:

Demonstrate their latest advances in stream processing systems for RDF.

Foster discussion for agreeing on a core model and query language for RDF streams.

Involve and attract people from related research areas to actively participate in the RSP Community Group.

I am on the Programme Committee.

An RDF Model for Events

Fri, 12 Dec 2014 13:22:34 +0100

Why do we need an event model? Many RDF streaming systems discussed have little or no model for the real-time data they ingest. These systems make the lowest common assumptions about the structure of the data, i.e. that the data consist of a stream of RDF triples. Thus, each piece of real-time data (event) is one triple. One triple, however, cannot hold a lot of information. For example: flexibility in timstamping (one vs. two timestamps or application time vs. system time) is only possible if timstamps can be attached to event structure. Flat triples cannot do that. Another example is when typing data, the triple <myInstance> rdf:type <MyClass> can introduce a type, but the event (one triple) is “full”. This means that any structure in the data must be inferred from more than one event. However, consumers cannot make assumptions about events which are not yet received: Events occur spontaneously and event consumers are often decoupled from the senders (cf. publish/subscribe systems). Therefore, structure is needed in individual events.

RDF Access Control

Thu, 02 Oct 2014 15:39:50 +0200

There are several approaches to modelling access control using RDF. The approaches use RDF as a modelling language for permissions linking users with user’s rights on the one hand and on the other hand are used on RDF data granting access to users (linking permissions with data). All approaches grant access to RDF resources while assuming what is not granted is forbidden.

The S4AC Vocabulary Specification 0.2¹ defines access rights tailored towards RDF query answering, i.e. SPARQL processing. The vocabulary defines access rights Create, Read, Update and Delete. The model is very expressive by allowing fine-grained access condition modelled as contextual queries against arbitrary context data to check. However, the integration with SPARQL is not applicable for our system as not all operations require a query such as a plain subscription to a stream.

Real-time Web

Thu, 02 Oct 2014 15:08:35 +0200

Behind the idea of the Real-time Web is the motivation of the Web being situation-aware and in real-time. This idea was developed as a grand challenge ¹ for the field of event processing. The purpose of this challenge is “to identify a single, though broad challenge that impacts society and at the same time measures the progress of research” ¹. The challenge is to create a decentralized, global, Internet-like infrastructure, built upon widely-accepted open standards ¹.

Definition of "Event" for Event Processing

Wed, 01 Oct 2014 17:12:27 +0200

I collected some definitions of event from the view of event processing research and practise. The emphasis is mine:

(Etzion & Niblett 2010) ¹ wrote:

An event is an occurrence within a particular system or domain; it is something that has happened, or is contemplated as having happened in that domain. The word event is also used to mean a programming entity that represents such an occurrence in a computing system.
(Luckham & Schulte 2011) ² wrote:

Anything that happens, or is contemplated as happening. Or: An object that represents, encodes, or records an event, generally for the purpose of computer processing.
(Gupta and Jain 2011) ³ wrote:

Events are first-class objects which means a fundamental information unit which can be stored, queried and merged with other events
(Hinze & Voisard 2002) ⁴ wrote:

An event is the occurrence of a state transition at a certain point in time.
(Michelson 2006) ⁵ wrote:

A notable thing that happens inside or outside your business.
(Mühl et al. 2006) ⁶ wrote:

Any happening of interest that can be observed from within a computer is considered an event. […] A notification is a datum that reifies an event, i.e., it contains data describing the event.

Immutability and Event Derivation in RDF

Wed, 01 Oct 2014 16:54:13 +0200

“In many event processing systems […] events are immutable” ¹. This stems from the definition of what an event is: “An event is an occurrence within a particular system or domain; it is something that has happened, or is contemplated as having happened […]” ². So events cannot be made to unhappen.

Open Question: Does this apply to all systems/applications/usecases or just to “many” as stated above?

I made immutability a general assumption in my work³. It is very useful for building systems (distributed systems, consistency, …).

Stream Punctuation and RDF Stream Processing

Wed, 01 Oct 2014 16:44:19 +0200

Definition by Tucker et al. ¹ and Maier et al. ²:

‘‘A punctuation is a pattern p inserted into the data stream with the meaning that no data item i matching p will occur further on in the stream.’’

For event processing systems, events are the fundamental unit of information ³. This means each event is processed atomically, i.e. completely or not at all. For RDF stream processing systems this can cause problems if events are modelled as graphs consisting of multiple quadruples: How can a receiver of an event know that all quadruples pertaining to the event are transmitted in order to start processing the event?

Highlights from Research Project PLAY

Sun, 08 Dec 2013 20:05:53 +0100

My research project PLAY has had its final review meeting on Tuesday, November 26th, 2013.

Notable highlights from the project are:

Use of open Web Standards for event modelling, pattern modelling, access control for real-time/streaming data
Integrated Prototype (delivering a runnable architecture with all Open Source components)
Contribution to Open Source community, e.g. continued maintenance of RDF2Go, MultiActive objects for ProActive

Benefits PLAY can provide as a semantics-based event-driven platform for a use case of nuclear crisis management:

Tutorial on Complex Event Processing

Thu, 12 Jan 2012 11:54:18 +0100

I gave a tutorial about Complex Event Processing and more specifically the PLAY semantic event format and query language at the Winter School on Knowledge Technologies for Complex Business Environments in Ljubljana on December 2, 2011 at the Faculty of Mechanical Engineering (FME).

https://videolectures.net/videos/coinplanetdataschool2011_stuehmer_cep

Abstract:

Real-time has become one of the crucial characteristics of modern applications and is completely changing the game in the data processing. Due to its capability to support continual monitoring, real-time data processing has become a very important mechanism in many application areas: traffic management, logistics, eHealth, smart grids, to name but a few. In this talk we present technologies to deal with real-time data on-the-fly, challenges and possible solutions to deal with these challenges such as using Web-friendly standards to create open and extensible systems for real-time data.

Contents on www.roland-stuehmer.de

Efficiently unlock secondary KeePass databases when working with shared password safes

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

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

Special Issue on Stream Processing, Call for Papers

Workshop on Situation Recognition (SIREMTI2015)

Streaming System Benchmarks

RDF Stream Benchmarks

Other Stream or CEP Benchmarks

RDF Stream Processing Workshop at ESWC2015, Call for Papers

An RDF Model for Events

RDF Access Control

Related Work

Real-time Web

Definition of "Event" for Event Processing

Immutability and Event Derivation in RDF

Stream Punctuation and RDF Stream Processing

Highlights from Research Project PLAY

Tutorial on Complex Event Processing

Abstract: