ACM SIGSPATIAL International Workshop on Computational Transportation Science (IWCTS) - Call for papersSubmitted by jsanz on Fri, 2016-08-19 17:57.
October 31st, 2016, San Francisco Bay Area, California, USA (Workshop Website: https://udi.ornl.gov/iwcts2016)
Important Dates and Deadlines
- Paper submission due: September 2th, 2016 (CDT)
- Notification to the authors: September 23rd, 2016
- Camera ready papers due: October 3rd, 2016
- IWCTS Workshop: October 31st, 2016 (collocated with ACM SIGSPATIAL 2016)
About the WorkshopThe 9th International Workshop on Computational Transportation Science (IWCTS 2016) is particularly timely given the prominence of connected automated vehicles technologies in the global auto industry’s near-term growth strategies, of big data analytics and unprecedented access to sensing data of mobility, and of integration of this analytics into the optimization of mobility and transport. These developments are deeply computational. We will build upon the success of previous workshops to continue to focus on computation, knowledge discovery, and technology aspects of transportation systems while welcoming research papers in computer science, transportation science, urban and regional planning, the automotive arena, civil engineering, robotics, geography, geo-informatics, and other related disciplines.
BackgroundIn the near future, vehicles, travelers, and the infrastructure will collectively have billions of sensors that can communicate with each other. Transportation systems, due to their distributed/mobile nature, can become the ultimate test-bed for a ubiquitous (i.e., embedded, highly-distributed, and sensor-laden) computing environment of unprecedented scale. This environment will enable numerous novel applications and order of magnitude improvement of the performance of existing applications. Information technology is the foundation for implementing new strategies, particularly if they are to be made available in real-time to wireless devices in vehicles or in the hands of people. Contributing are increasingly more sophisticated geospatial and spatio-temporal information management capabilities. Human factors, technology adoption and use, user feedback and incentives for collaborative behavior are areas of technology policy central to the success of this ubiquitous computing environment.
Scope of Submissions
The International Workshop on Computational Transportation Science invites submissions of original, previously unpublished papers contributing to Computational Transportation Science. Position papers that report novel research directions or identify challenging problems are also invited. Papers incorporating one or more of the following themes are especially encouraged:• Collaborative transport, including collaborative multi-modal transport
• Computational and artificial intelligence aspects of assisted driving, collaborative transport or multi-modal transport
• Crowd sourcing and participatory sensing in transport
• Cameras as sensors for trajectory acquisition and event recognition
• Computer Vision-based information extraction from image sequences
• Context aware analysis of movement data
• New processing frameworks for handling masses of transport data (e.g. Hadoop)
• Uncertain information in collaborative transport and assisted travelling
• Mechanism design for collaborative behavior
• Data mining and statistical learning for travel information
• Human-computer interfaces in intelligent transportation applications
• Privacy, security, and trust in transportation information
• Novel applications targeted to health, mobility, livability and sustainability
Submission Format and GuidelinesAuthors should prepare an Adobe Acrobat PDF version of their full paper. Papers must be in English and not exceed 6-pages double column in ACM SIG format (US Letter size, 8.5 x 11 inches) including text, figures and references. Position papers are limited 4 pages in this format, and should be marked ‘(Position paper)’ in the subtitle. Accepted papers will be published in the ACM digital library under the condition that at least one author has registered for both the main SIGSPATIAL conference and the workshop, attends the workshop, and presents the accepted paper in the workshop. Otherwise, the accepted paper will not appear in the workshop proceedings or in the ACM Digital Library version of the workshop proceedings.
- Gautam S. Thakur, Oak Ridge National Laboratory, USA (email@example.com)
- Nicole Ronald, Swinburne University of Technology, Australia (firstname.lastname@example.org)
- Stephan Winter, The University of Melbourne, Australia (email@example.com)
For the first time, the ACM SIGSPATIAL 2016 will host the SIGSPATIAL ACM Student Research Competition (SRC). SRC allows undergraduate and graduate students to share their research results and exchange ideas with other students, judges, and conference attendees; understand the practical applications of their research; perfect their communication skills; and receive prizes and gain recognition from ACM and the greater computing community.
The Student Research Competition is open to graduate (only one author) and undergraduate (up to two authors per contribution) student members whose submissions are accepted by the SRC committee. SRC submissions should describe recent research conducted primarily by students or a recent development that involves a substantial amount of work achieved primarily by students. To be considered, complete a submission of an extended abstract of a topic of interest to the ACM SIGSPATIAL conference (please check the main conference CFP for relevant topics) and indicate the level of the participation (undergraduate or graduate). Valid ACM student membership and student status enrolment as of the submission deadline are required for the lead student.
Submission will be judged based on novelty, impact, approach, results, and contributions to the field of spatial systems and algorithms. Selected competitors must attend the SRC session during the conference and should prepare a poster for demonstrating their work during the conference. If selected for further competition at the next level, they should be prepared to give a short talk of 10 minutes about their research projects in front of the judging committee and conference attendees. Winners of the SIGSPTIAL 2016 SRC will be announced at the conference.
Selected competitors by the SRC committee will receive up to $500 USD for their conference travel, depending on need. Winners from each category will advance to the SRC Grand Finals, where winners from various ACM SIGs are evaluated to nominate the ACM-wide SRC winners. The winners of the Grand Finals will be recognized at the Annual ACM Awards Banquet, the same banquet that also recognizes the Turing Award winners.
The SRC competition is fully sponsored by a generous donation from Microsoft Research.
Each submission should include the author(s)' name(s), affiliations, email addresses, research advisors' names, ACM student member number, SRC category (undergraduate or graduate), and an extended abstract of no more than two pages in the conference template. The SRC submission should not have been published before or under concurrent submission to another venue/SIGSPATIAL track. Please submit your papers through the EasyChair system at: https://easychair.org/ conferences/?conf= acmsigspatial16src
Submission Deadline: August 25,
2016. September 2nd, 2016.
Notification of Acceptance: September 20, 2016 September 27th, 2016.
For more information about the SRC competition, please contact the SRC Chair Moustafa Youssef at firstname.lastname@example.org
FREMONT, CA—July 20, 2016— Rasdaman, has been ranked as one of the 100 Most Promising BigData Solution Providers 2016 by CIOReview.
"It's a delightful experience to announce Rasdaman as one of the 100 Most Promising BigData Solution Providers 2016," said Jeevan George, Managing Editor of CIOReview. "Rasdaman is recognized for providing highly innovative products that helps to store and query massive, multi-dimensional array of data into the data base, which brings new dimension to the industries in the Big Data arena."
Rasdaman is a leader in Array Databases, and specializes in raster service standardization, leader in geo raster services, international project management, and spatial data infrastructures. It provides Scalable Array Engine typical representatives include spatio-temporal sensor, image, simulation, and statistics data. Through its SQL-embedded array query language, rasdaman is pioneer and world technology leader in flexible, fast, and scalable array analytics. The rasdaman technology is available in two compatible editions. Open-source rasdaman community is freely available as source code. The performance boosters of prorietary rasdaman enterprise edition overlay in a compatible way. It also provides Analytics tools, Visual geo clients: OpenLayers and Geo workbenches.
Digital Magazine Link:http://magazine.cioreview.com/magazines/July2016/BigData/#page=147
Founded in 2003, Rasdaman is the pioneer and leading Array Analytics Engine, the next generation in scalable data services for science, engineering, and beyond. It provides agile analytics on massive multidimensional arrays, such as regular and irregular spatio-temporal grids. For more info, visit: http://www.rasdaman.com/
Published from Fremont, California, CIOReview is a print magazine that explores and understands the plethora of ways adopted by firms to execute the smooth functioning of their businesses. A distinguished panel comprising of CEOs, CIOs, IT VPs including CIOReview editorial board finalized the "100 Most Promising BigData Solution Providers 2016" in the U.S. and shortlisted the best vendors and consultants.
For more info:
The gvSIG Association is now pleased to inform the “Introduction to gvSIG” summer webinars at the beginning of August.
Summer has arrived in a lot of places around the world. This is a good time to learn to use gvSIG, the open source GIS.
Do you want to create a thematic map with gvSIG or a new vector layer with your parcel, a road...? You can do it now at these open and free webinars.
There will be two webinars, that will last about 30 minutes:
- “Getting started with gvSIG” - August 3rd (14:00 UTC – Check the time in your country)
- “Vector editing, 3D view and other gvSIG tools” - August 10th (14:00 UTC – Check the time in your country)
At the first webinar we'll see how to manage a gvSIG project. We'll create new views with cartography, and we'll apply symbology and labelling. We'll introduce the reference systems, and finally we will create a thematic map to be printed or exported to a PDF file.
At the second webinar, we'll show how to create a new vector layer, where we'll digitalize several elements. We also will see the gvSIG toolbox, where we can find all the geoprocesses. We will apply one of them. We finally will see how the 3D extension works.
- Registration for the “Getting started with gvSIG” webinar: https://app.webinarjam.net/register/24718/711021346f
- Registration for the “Vector editing, 3D view and other gvSIG tools” webinar: https://app.webinarjam.net/register/24718/2ea6110ff3
We expect your participation!
|Workshop Title||Workshop Acronym||Website URL|
|9th ACM SIGSPATIAL Workshop on Computational Transportation Science (IWCTS 2016)||IWCTS||https://udi.ornl.gov/iwcts2016|
|7th ACM SIGSPATIAL Workshop on GeoStreaming (IWGS 2016)||IWGS||http://www.iwgeostream.com|
|2nd ACM SIGSPATIAL Workshop on Emergency Management using GIS (EM-GIS 2016)||EM-GIS||http://www.dviz.cn/em-gis2016/|
|5th ACM SIGSPATIAL Workshop on Analytics for Big Geospatial Data (BigSpatial-2016)||BigSpatial||http://www.cse.buffalo.edu/~|
|5th ACM SIGSPATIAL Workshop on Mobile Geographic Information Systems (MobiGIS 2016)||MobiGIS||http://www.mobigis.org|
|2nd ACM SIGSPATIAL Workshop on Smart Cities and Urban Analytics (UrbanGIS) 2016||UrbanGIS||https://wp.nyu.edu/urbangis/|
|3rd ACM SIGSPATIAL PhD Workshop||PhD||https://sites.google.com/site/|
|8th ACM SIGSPATIAL Workshop on Indoor Spatial Awareness (ISA 2016)||ISA||https://sites.google.com/site/|
|ACM SIGSPATIAL Workshop on Location-based Social Networks (LBSN 2016)||LBSN|
|6th ACM SIGSPATIAL Workshop on Mobile Entity Localization, Tracking and Analysis (MELT 2016)||MELT||https://sites.google.com/site/|
|10th Workshop on Geographic Information Retrieval (GIR 2016)||GIR||http://www.geo.uzh.ch/~rsp/|
The pycsw team proudly announces the release of pycsw 2.0.0 “Doug”.
The 2.0.0 “Doug” release brings major features, enhancements and fixes to the codebase, including:
- CSW 3 support (OGC Reference Implementation)
- Python 3 support
- WMTS harvesting (thanks @jfdickens)
- JSON output improvements
- XML output improvements
- GM03 support for Swiss metadata
- add temporal extent support to WMS layer harvesting
The full list of enhancements and bug fixes is available at https://github.com/geopython/pycsw/milestone/8. Users are strongly advised to review the migration guide.
The 2.0.0 release is codenamed “Doug” in honour of Doug Nebert of the FGDC. Doug was internationally recognized as a champion of metadata, discovery and interoperability. Involved in numerous international standards bodies and spatial data infrastructure initiatives, Doug was one of the editors of the CSW 3.0 specification and encouraged pycsw developers to adopt and implement CSW 3.0 as part of US data.gov efforts. Doug’s vision and expertise will always be remembered and appreciated by the pycsw development team.
pycsw is an OGC CSW server implementation written in Python.
pycsw fully implements the OpenGIS Catalogue Service Implementation Specification (Catalogue Service for the Web). Initial development started in 2010 (more formally announced in 2011). The project is certified OGC Compliant, and is an OGC Reference Implementation. Since 2015, pycsw is an official OSGeo Project.
pycsw allows for the publishing and discovery of geospatial metadata. Existing repositories of geospatial metadata can also be exposed via numerous APIs (CSW 2/CSW 3, OpenSearch, OAI-PMH, SRU), providing a standards-based metadata and catalogue component of spatial data infrastructures.
pycsw is Open Source, released under an MIT license, and runs on all major platforms (Windows, Linux, Mac OS X).
Source and binary downloads
The source code is available at: http://pycsw.org/download
Testers and developers are welcome.
The pycsw developer team.