larkc

LarKC’s Botari wins the 2011 Semantic Web Challenge

Fri, 28 Oct 2011 14:57:08 +0000

The Botari application from the LarKC project has won the Open Track of the Semantic Web Challenge.

Botari is a LarKC workflow running on servers in Seoul, plus a user frontend that runs on a Galaxy Tab.

The workflow combines open data from the city of Seoul (Open Street Map, POI’s) with twitter traffic and combines stream processing, machine learning and querying over RDF datasets and streams to give personalised restaurant information and recommendations, presented in an augmented reality interface on the Galaxy Tab.

For more info on Botari, see either the website, or the demo movie or the slide deck or the paper.

Another speed record for OWL Horst inference

Mon, 19 Sep 2011 09:18:26 +0000

If you liked WebPIE, you’ll also like QueryPIE

WebPIE performed forward inference over up to 100 billion triples (yes, that’s 10^11). Our about-to-be-published QueryPIE can do on the fly backward-chaining inference at query-time, over a billion triples, in milliseconds, on just 8 parallel machines.

Last year, Jacopo Urbani and co-authors from the LarKC team broke the speed record for forward chaining inference over OWL-Horst. Computing the complete closure over 100 billion of triples in a number of hours using a MapReduce/Hadoop implementation on a medium-sized cluster. The performance of WebPie [see conference and journal paper] is:

1 billion FactForge triples in 1.5 hours on 32 compute nodes
24 billion Bio2RDF triples in 10 hours on 32 compute nodes
100 billion LUBM triples in 15 hours on 64 compute notes
deriving anywhere between 150K-650K triples per second, depending on the dataset
runtime growing linearly with number of triples
speedup growing linearly the number of compute nodes

Now, a year later, we’re breaking another speed record, but this time for “backward chaining“: not doing all inferencing up front, but doing the inferencing “on the fly”, at query time, as and when they are needed.

Until now, backward-chaining was considered to be unfeasible on very large realistic data, since it would slow down the query response time too much. Our paper at ISWC this year shows it’s not all that impossible: on different real-life datasets of up to 1 billion triples, QueryPIE can do on the fly backward-chaining inference at query-time, implementing the full OWL Horst fragment with response times in millisecs on just 8 machines.

All code available at http://few.vu.nl/~jui200/files/querypie-1.0.0.tar.gz

Chinese LarKC BooK

Thu, 21 Jul 2011 07:51:41 +0000

by Zhisheng Huang

The China Higher Education Press will publish a LarKC book in Chinese. This book will appear in the book series of Web Intelligence and Web Science (http://www.wici-lab.org/wici/WIWS/) .

This Chinese LarKC book consists of two parts: Technology part and application part. The technology part covers the topics of LarKC platform, development guide and various plugins and workflows. The application part covers the topics of Linked Life Data, semantic information retrieval, urban computing, and cancer study. The main contributors of the book are six Chinese researchers in the LarKC Consortium, who are from Amsterdam, WICI, and Siemens. See the appended text below for the detail.
The book is expected to be published by the end of this year.

Here is the outline of the book content and the main contributors.

Chapter 1 Introduction to LarKC
by Zhisheng Huang (VUA) and Ning Zhong (WICI)

Chapter 2 LarKC Platform
by Jun Fang (VUA)

Chapter 3 Identification and Selection
by Yi Zeng (WICI)

Chapter 4 Abstraction and Transformation
by Yi Huang (SIEMENS)

Chapter 5 Reasoning and Deciding
by Jun Fang (VUA) and Zhisheng Huang (VUA)

Chapter 6 LarKC Development Guide
by Zhisheng Huang (VUA) and Jun Fang (VUA)

Chapter 7 Linked Life Data
by Yi Huang (SIEMENS) and Zhisheng Huang (VUA)

Chapter 8 Semantic information retrieval for biomedical applications
by Ru He (SIEMENS) and Zhisheng Huang (VUA)

Chapter 9 Semantic Technology and Gene Study
by Zhisheng Huang (VUA)

Chapter 10 Urban Computing
by Yi Huang (SIEMENS) and Zhisheng Huang (VUA)

Chapter 11 Conclusions
by Zhisheng Huang (VUA), Ru He (SIEMENS), and Ning Zhong (WICI)

LarKC from an HPC perspective

Sun, 19 Jun 2011 21:53:33 +0000

The LarKC folk at the German High Performance Computing Centre in Stuttgart did a rather nice write-up on LarKC from a high-performance computing perspective, intended for their own community. Find the relevant pages here.

Traffic LarKC wins the AI Mashup Challenge

Fri, 03 Jun 2011 14:43:53 +0000

A LarKC workflow for traffic-aware route-planning has won the 1st prize in the AI Mashup Challenge at the ESWC 2011 conference, held this week on Crete.

The detail of “Traffic_LarKC” can be found at https://sites.google.com/a/fh-hannover.de/aimashup11/home/traffic_larkc, but in brief:

Four different datasets are used:

the traffic sensors data, obtained from Milano Municipality
the Milano street topology
historical weather data from the Italian website ilMeteo.it
calendar information (week days and week-end days, holidays, etc.) from Milano Municipality and from the Mozilla Calendar project.

These are used in a batchtime workflow to predict the traffic situation over the next two ours and in a runtime workflow to respond to route-planning queries from users.

The demo can be found at http://larkc.cefriel.it/traffic-larkc,
a video is at http://larkc.cefriel.it/traffic-larkc/traffic-larkc-video.html
a paper is at https://sites.google.com/a/fh-hannover.de/aimashup11/home/traffic_larkc/traffic-larkc2_aimc-eswc-2011.pdf?attredirects=0&d=1, and
the competition entry is at https://sites.google.com/a/fh-hannover.de/aimashup11/home/traffic_larkc.

This LarKC workflow shows that Linked Open Data and the corresponding technologies are now getting good enough to compete with what’s possible in closed commercial systems.

Congratulations to the entire team that has made this possible!

The Large Knowledge Collider release V2.5

Mon, 30 May 2011 06:29:43 +0000

The LarKC development team is proud to announce the new release V2.5 of the LarKC platform. The new release is a considerable improvement over the previous V2.0 edition, with the following distinctive features:

V2.5 is fully compliant with the LarKC final architecture. You can now develop your workflows and plugins, and be assured that future updates won’t change the main APIs.
The Management Interface, which makes it possible to run LarKC from your browser, has an updated RESTful implementation. Besides RDF/XML, workflows can now be described in very readable N3 notation.
The endpoint for submitting queries to LarKC is now user-definable, and multiple endpoints are supported.
The Plug-in Registry has been improved, and is now coupled with the browser-based Management Interface
LarKC now uses a Maven-based build system, giving improved version and dependency management, and a simplified procedure for new plug-in creation
A number of extra tools have been introduced to make life for LarKC users a lot easier. Besides the Mangement Interface to run LarKC from your browser, V2.5 also contains:
- A WYSIWIG Worfklow Designer tool that allows you to construct workflows by drag-and-drop, right from your browser: click on some plugins, drag them to the workspace, click to connect them, and press run! (see screenshot below).
- An updated plug-in wizard for Eclipse.
We have thouroughly updated the distributed execution framework. Besides deploying LarKC plugins through Apache (simply by dropping them in your Apache folder), it is now also possible to deploy plugins through JEE (for webservers) or GAT (for clusters).
The WYSIWYG Workflow Designer allows you to specify remote execution of a plugin simply by connecting a plugin to a remote host. Templates are provided for such remote host declaration.
LarKC now takes care of advanced data caching for plug-ins
V2.5 comes with extended and improved JUnit tests
Last but not least, we have considerably improved documentation and user manuals, including a quick-start guide, tutorial materials and example workflows.

The release can be downloaded from http://sourceforge.net/projects/larkc/files/Release-2.5/larkc-release-2.5.zip/download
The platform’s manual is available at http://sourceforge.net/projects/larkc/files/Release-2.5/LarKC_Platform_Manual_2.5.pdf/download

Bugs can be submitted using the bug tracker at http://www.larkc.eu/bug-tracker

As usual, you are encouraged to use the discussion forums and mailing lists served by the LarKC@SourceForge development environment.
please see at http://larkc.sourceforge.net/

Explosion under inference (or not)

Sun, 15 May 2011 11:52:56 +0000

Should the semantic web be just about querying RDF? Or is it usefual (or even: feasible) to use the semantics of RDF, RDF Schema and OWL to derive additional information from the published RDF graphs? Both the feasibility and the usefulness of this depends on the amount of additional triples that are derived by inference: when almost zero, there is little point to inference, when explosively large, it might become infeasible.

LarKC researchers at OntoText produced an informative table showing the amount of additional triples that can be inferred from some of the most popular datasets on the Web. It’s interesting to see how the datasets differ in their semantic richness, with their ratio of explicit triples vs. inferred triples ranging from close to zero (CIA Factbook) to a 16-fold increase (for DBPedia). Please let us know if you have similar statistics for other datasets.

All of the data below taken from FactForge which by itself now contains 1.5billion triples, nearly four times larger than in the beginning of the LarKC project in 2008. All of the figures below obtained with BigOWLIM 3.4, under the OWL-Horst semantics. Size is reported in millions of triples.

Dataset	Explicit Indexed Triples	Inferred Indexed Triples	Total of Indexed Triples	Entities (nodes in the graph)	Inferred closure ratio
Schemata (Proton, SKOS, FOAF, RSS, DC) and ontologies (DBpedia, Geonames)	15	9	23	8	0.6
DBpedia (SKOS categories)	2,915	47,837	50,751	1,135	16.4
NY Times	574	328	902	185	0.6
UMBEL	4,638	6,936	11,575	1,190	1.5
Lingvoj	20	182	201	18	9.2
CIA Factbook	76	4	80	24	0.1
WordNet	1,943	6,067	8,010	842	3.1
Geonames	142,011	194,191	336,202	42,738	1.4
DBpedia core	825,162	166,740	991,902	125,803	0.2
Freebase	494,344	52,411	546,754	123,511	0.1
MusicBrainz	45,492	36,572	82,064	15,585	0.8

BigOWLIM - OWL Semantic Repository (ontotext.com)

The first LarKC Pharma Workshop in Stuttgart

Mon, 02 May 2011 15:21:40 +0000

By Bosse Andersson
The first LarKC Pharma workshop was held in Stuttgart April 19 and 20. An interesting mix of participants from pharmaceutical companies, semantic web companies and research/academia formed an open atmosphere with many intense discussions and hopefully future interactions.

The workshop had an outline similar to previous LarKC tutorials with a twist from the pharma domain in presentations and examples.

Participants did find the LarKC platform and the Linked Life Data repository useful;

From pharma perspective questions circulated around what the requirements will be for us to host/use LarKC as an internal experimental platform.
The semantic web companies where more interested in how to use components of LarKC or provide services that can leverage from the LarKC platform.
The research/academia community had a specific need to learn how to quickly get LarKC up and running for the first iteration in the Innovative Medicine Initiative, OpenPhacts.

Many questions did come up during lively discussions, some were answered others will be brought back to the consortium to address, e. g. how to lower the entrance to start using LarKC.

LarKC in the World

Thu, 31 Mar 2011 12:30:37 +0000

Although LarKC is based in Europe, the project of building, and applying, web-scale reasoning is world wide. One of the most exciting things about living in a connected world, and a world of abundant, location independent computational resources, is that people anywhere in the world can do world class AI research, and develop applications based on that research. The recent, and very rapid, increase in internet bandwidth going into Africa means that one can now use Shazam to get impromptu karaoke lyrics for the Texas country-and-western playing in a hotel bar in Accra. It also means that previously isolated African researchers can make a full contribution to the advance of semantic technology. In February, partially supported by the FP7 Active project, we had the opportunity to present LarKC, and the potential benefits of AI and human-computer collaboration, to students and researchers at the Ghana-India Kofi Annan Centre of Excellence in ICT in Ghana. Discussion following the talks was lively, with great local ideas for the application of AI in knowledge capture from small farmers, and resource allocation for rural health care. Video from some talks is being made available on VideoLectures.net, there was good coverage from the local media, and we look forward to building a collaboration with our new colleagues.

Ghana’s Influential Women Celebrated on Int’l Women’s Day (macjordangh.wordpress.com)

Probase: a peek in Microsoft’s Web-of-Data kitchen

Tue, 22 Mar 2011 23:46:55 +0000

An interesting peek in Microsoft’s kitchen (the Beijing labs, by the looks of it): Probase and ReadWriteWeb writeup on it. It’s a very large web-fed knowledge-base, including concept hierarchies (2.7 million concepts, 4.5 million subclass relations, 16 million instances). Including all major knowledge sources (Freebase, WordNet, Cyc, DBPedia, Yago, a.o.), with pretty well researched quality measures. Unfortunately, none of the data is Linked in any way, none of this available, let alone in some standard format.This is interestingly different from IBM’s Watson knowledge base. That is mostly filled with knowledge extracted from linguistic sources (although structured data does play a limited role). Probase seems to rely much more on structured knowledge sources.

LarKC platform v3.0 release

Thu, 06 Oct 2011 10:26:06 +0000

The LarKC project’s development team would like to announce a new release (v.3.0) of the LarKC platform, which is available for downloading here. The new release is a considerable improvement of the previous release (v.2.5), with the following distinctive features: PLATFORM New (plain) plug-in registry light-weight plug-in loading and thus very low platform’s start-up time [...]

LarKC Workflow Challenge 2011

Tue, 31 May 2011 17:05:03 +0000

The LarKC consortium invites you to take part in the 2011 LarKC Workflow Challenge. LarKC (the large knowledge collider) is a free and open platform that makes it easy to produce scalable, semantic mashup, and to run them on both serial and parallel machines. Learning to use the platform is a great skill for getting [...]

Web of Data Interpreter – A LarKC Spin-Off

Mon, 21 Mar 2011 14:52:10 +0000

Web of Data Interpreter (WoDI) is a recently launched spin-off company from the LarKC project, currently located in Innsbruck, Austria. The targeted development segment of WoDI is the implementation of intelligent tools and methods for accessing, reasoning and consuming linked data. The main areas of WoDI innovation are scalable reasoning with rules and streams of [...]

Scalable Integration and Processing of Linked Data @ WWW’11

Mon, 21 Feb 2011 11:27:57 +0000

The LarKC team is proud to announce that its tutorial “Scalable Integration and Processing of Linked Data” was accepted at this year’s International World Wide Web Conference 2011 (WWW’11) that will take place from March 28th to April 1st, 2011 in Hyderabad, India. Abstract of the Tutorial The goal of this tutorial is to introduce, [...]

LarKC Pharma Workshop

Wed, 16 Feb 2011 12:08:49 +0000

Based on the great success of LarKC’s Early Adopters Tutorials, the next workshop is targeted to drug development and discovery. The LarKC Pharma Workshop will take place on April 19th and 20th 2011 in Stuttgart. The workshop builds on previous tutorials and is customized for drug development/discovery participants. Having completed this workshop, participants will have [...]

LarKC Platform v2.0 released

Mon, 03 Jan 2011 10:38:52 +0000

We are glad to announce that the LarKC Platform Release v2.0 is now available in our repository on SourceForge. The redistributable package can be downloaded via the following URL: http://sourceforge.net/projects/larkc/files/Release-2.0/larkc-release-2.0.zip/download (OS independent) The source code belonging to this release can be checked out from SVN: http://larkc.svn.sourceforge.net/viewvc/larkc/branches/Release_2.0_prototype/platform/ A complete manual for both users and developers can [...]

New version of mpiJava released

Wed, 08 Dec 2010 08:28:25 +0000

LarKC announces a new release of mpiJava (1.2.6) – a Message-Passing Interface (MPI) library, allowing a Java application to efficiently run on a distributed, parallel, and high-performance computer architecture. First introduced in the HPJava project and developed by Pervasive Technology Labs, Indiana University, Syracuse University, and CSM, University of Portsmouth, mpiJava@SourceForge (http://sourceforge.net/projects/mpijava/) is now managed [...]

4th Early Adopters Tutorial

Fri, 22 Oct 2010 09:25:47 +0000

The fourth early adopters tutorial will be held in conjunction with next LarKC project meeting on the 13th November, 2010 in the Gongda Jianguo Hotel, Beijing University of Technology, Beijing, China. This tutorial will enable participants to the get access to early research results and technologies from the LarKC project, and will mainly focus on [...]

The LarKC project movie

Thu, 30 Sep 2010 14:49:58 +0000

Watch the LarKC project movie and find out what it is all about!

Talk at ESCoP Summer School in Computational and Mathematical Modeling of Cognition

Fri, 27 Aug 2010 07:44:41 +0000

Lael Schooler gave a talk on LarKC at “European Society for Cognitive Psychology Summer School in Computational and Mathematical Modeling of Cognition” in Mallnitz, Austria, 9-19 July 2010.