226 research outputs found
DBpedia's triple pattern fragments: usage patterns and insights
Queryable Linked Data is published through several interfaces, including SPARQL endpoints and Linked Data documents. In October 2014, the DBpedia Association announced an official Triple Pattern Fragments interface to its popular DBpedia dataset. This interface proposes to improve the availability of live queryable data by dividing query execution between clients and servers. In this paper, we present a usage analysis between November 2014 and July 2015. In 9 months time, the interface had an average availability of 99.99 %, handling 16,776,170 requests, 43.0% of which were served from cache. These numbers provide promising evidence that low-cost Triple Pattern Fragments interfaces provide a viable strategy for live applications on top of public, queryable datasets
Towards a Cloud-Based Service for Maintaining and Analyzing Data About Scientific Events
We propose the new cloud-based service OpenResearch for managing and
analyzing data about scientific events such as conferences and workshops in a
persistent and reliable way. This includes data about scientific articles,
participants, acceptance rates, submission numbers, impact values as well as
organizational details such as program committees, chairs, fees and sponsors.
OpenResearch is a centralized repository for scientific events and supports
researchers in collecting, organizing, sharing and disseminating information
about scientific events in a structured way. An additional feature currently
under development is the possibility to archive web pages along with the
extracted semantic data in order to lift the burden of maintaining new and old
conference web sites from public research institutions. However, the main
advantage is that this cloud-based repository enables a comprehensive analysis
of conference data. Based on extracted semantic data, it is possible to
determine quality estimations, scientific communities, research trends as well
the development of acceptance rates, fees, and number of participants in a
continuous way complemented by projections into the future. Furthermore, data
about research articles can be systematically explored using a content-based
analysis as well as citation linkage. All data maintained in this
crowd-sourcing platform is made freely available through an open SPARQL
endpoint, which allows for analytical queries in a flexible and user-defined
way.Comment: A completed version of this paper had been accepted in SAVE-SD
workshop 2017 at WWW conferenc
Disaster Monitoring with Wikipedia and Online Social Networking Sites: Structured Data and Linked Data Fragments to the Rescue?
In this paper, we present the first results of our ongoing early-stage
research on a realtime disaster detection and monitoring tool. Based on
Wikipedia, it is language-agnostic and leverages user-generated multimedia
content shared on online social networking sites to help disaster responders
prioritize their efforts. We make the tool and its source code publicly
available as we make progress on it. Furthermore, we strive to publish detected
disasters and accompanying multimedia content following the Linked Data
principles to facilitate its wide consumption, redistribution, and evaluation
of its usefulness.Comment: Accepted for publication at the AAAI Spring Symposium 2015:
Structured Data for Humanitarian Technologies: Perfect fit or Overkill?
#SD4HumTech1
Curtains Up! Lights, Camera, Action! Documenting the Creation of Theater and Opera Productions with Linked Data and Web Technologies
International audienceFor this paper, in the context of the French research project Spectacle en Ligne(s), we have recorded the entire set of rehearsals of one theater and one opera production using state-of-the-art video equipment. The resulting raw video and audio tracks as well as manually generated annotation data were then preprocessed in order to localize actors and detect their dialogues. Based on these preprocessing steps, we have built a Web-based hypervideo application that allows for navigation through performance time, performance space, and rehearsal time using modern HTML5 Web technologies like the emerging Web Components standard. We publish and consume the annotation data as so-called Linked Data Fragments, a novel way to make triple-based structured data available in a scalable way. As a direct outcome, researchers interested in the genetic analysis and the creation process of live performances can, thanks to this application, freely zoom in and out of scenes, rehearsal sessions, and stage locations in order to better understand the different steps on the way to a chef d'oeuvre. A live demo of the application is publicly available at the URL http://spectacleenlignes.fr/hypervideo/
From Linked Data to Relevant Data -- Time is the Essence
The Semantic Web initiative puts emphasis not primarily on putting data on
the Web, but rather on creating links in a way that both humans and machines
can explore the Web of data. When such users access the Web, they leave a trail
as Web servers maintain a history of requests. Web usage mining approaches have
been studied since the beginning of the Web given the log's huge potential for
purposes such as resource annotation, personalization, forecasting etc.
However, the impact of any such efforts has not really gone beyond generating
statistics detailing who, when, and how Web pages maintained by a Web server
were visited.Comment: 1st International Workshop on Usage Analysis and the Web of Data
(USEWOD2011) in the 20th International World Wide Web Conference (WWW2011),
Hyderabad, India, March 28th, 201
Luzzu - A Framework for Linked Data Quality Assessment
With the increasing adoption and growth of the Linked Open Data cloud [9],
with RDFa, Microformats and other ways of embedding data into ordinary Web
pages, and with initiatives such as schema.org, the Web is currently being
complemented with a Web of Data. Thus, the Web of Data shares many
characteristics with the original Web of Documents, which also varies in
quality. This heterogeneity makes it challenging to determine the quality of
the data published on the Web and to subsequently make this information
explicit to data consumers. The main contribution of this article is LUZZU, a
quality assessment framework for Linked Open Data. Apart from providing quality
metadata and quality problem reports that can be used for data cleaning, LUZZU
is extensible: third party metrics can be easily plugged-in the framework. The
framework does not rely on SPARQL endpoints, and is thus free of all the
problems that come with them, such as query timeouts. Another advantage over
SPARQL based qual- ity assessment frameworks is that metrics implemented in
LUZZU can have more complex functionality than triple matching. Using the
framework, we performed a quality assessment of a number of statistical linked
datasets that are available on the LOD cloud. For this evaluation, 25 metrics
from ten different dimensions were implemented
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