[Asis-l] ISWC 2016 Benchmarking Linked Data Workshop

[Axel Ngonga]

Metadata
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Call for Papers
Submission deadline: July 7th 2016
EasyChair submission page: 
https://easychair.org/conferences/?conf=blink2016
Accepted papers: Short (8 pages) and long (16 pages)
Workshop page: http://project-hobbit.eu/events/blink-2016/
Conference: ISWC - Kobe, Japan - October, 17th or 18th, 2016

Description
=======
BLINK will provide a forum where topics related to the evaluation 
(included, but not limited to the performance, accuracy, expressive 
power and usability) of Linked Data Technologies for different steps of 
the Linked Data lifecycle can be discussed and elaborated upon.
Linked Data now part of the new data economy and Big Linked Data is 
gaining in use and traction. Systems are constantly being developed in 
order to support the booming exchange of data (existing in numerous 
formats) in the Web and the Enterprise. Linked Data benchmarks can 
function as valuable tools to objectively depict and illustrate the 
level of adequacy and thus performance provided by the existing Linked 
Data systems.
This workshop aims to bring together a broad range of attendants 
interested in benchmarking Linked Data and aims at identifying the 
specific needs and challenges of the domain in order to foster 
interdisciplinary collaborations towards attaining these challenges.
More specifically the objectives of this workshop are to:
create a discussion forum where researchers and industrials can meet and 
discuss topics related to the performance of Linked Data systems and
expose and initiate discussions on best practices, different application 
needs and scenarios related to Linked Data management.

Topics of Interest
===============
We welcome contributions presenting experiences with benchmarking Linked 
Data technologies as well as technical contributions regarding the 
development of benchmarks for all aspects of the Linked Data/Big Data 
lifecycle. All domains (e.g., life science, social networks, smart 
cities, news, digital forensics, e-science and geo-spatial data 
management)  are welcome.

Topics of interest include but are not limited to:
* Linked Data benchmarks
* Novel benchmarking results
* Analysis of existing benchmarks
* Novel measures for benchmarking Linked Data
* Linked Data benchmark evaluation
* Complex benchmarking pipelines
* Application of benchmarks in academic/industrial settings
* Tools and methodologies for the linked data generation and 
acquisition, analytics and processing,  storage and curation, 
visualization and data access.

This series of workshops are supported by H2020 European Project HOBBIT 
(Holistic Benchmarking of Big Linked Data), see http://project-hobbit.eu/.

Paper Submission
===========
The workshop will accept two types of submissions: short papers (8 
pages) will be either position papers or describe early works in the 
area of benchmarking. Long papers (up to 16 pages) will describe 
benchmarks, benchmarking techniques or benchmarking results along the 
linked data lifecycle. Details on the submission process can be found at 
http://project-hobbit.eu/events/blink-2016/

Important Dates:
July 7th, 2016: paper submission deadline
July 31st 2016: Notifications send to authors
August 25th 2016: Camera-ready papers for workshops
October 17th or 18th: Workshop

Submission Details
============
The workshop is now accepting paper submissions. Long papers (up to 16 
pages) and short papers (up to 8 pages) describing approaches or ideas / 
challenges on the topics of the workshop are invited. Submissions must 
be in PDF, formatted in the style of the Springer Publications format 
for Lecture Notes in Computer Science (LNCS). For details on the LNCS 
style, see Springer’s Author Instructions. Papers should be submitted 
through the EasyChair system 
https://easychair.org/conferences/?conf=blink2016 no later than midnight 
Hawaii time July 7th, 2016. Submissions will be reviewed by members of 
the workshop program committee. Accepted papers will be included in the 
ISWC 2016 Workshop on Benchmarking Linked Data (BLINK) proceedings.