WISM: Web Information Systems Modeling



Past:   Proceedings on DBLP

Future:  Post a CFP for 2015 or later   |   Invite the Organizers Email


All CFPs on WikiCFP

Event When Where Deadline
WISM 2014 Eleventh International Workshop on Web Information Systems Modeling
Oct 27, 2014 - Oct 30, 2014 Atlanta, Georgia, USA May 18, 2014
WISM 2012 Ninth International Workshop on Web Information Systems Modeling
Oct 15, 2012 - Oct 18, 2012 Florence, Italy Mar 15, 2012
WISM 2011 Eighth International Workshop on Web Information Systems Modeling
Oct 31, 2011 - Nov 3, 2011 Brussels, Belgium Apr 6, 2011
WISM 2010 Seventh International Workshop on Web Information Systems Modeling
Nov 1, 2010 - Nov 4, 2010 Vancouver, BC, Canada Apr 2, 2010
WISM 2009 Sixth International Workshop on Web Information Systems Modeling
Jun 8, 2009 - Jun 8, 2009 Amsterdam, the Netherlands Feb 15, 2009
WISM 2008 Fifth International Workshop on Web Information Systems Modeling
Oct 20, 2008 - Oct 23, 2008 Barcelona, Catalonia, Spain Apr 10, 2008

Present CFP : 2014

Web Information Systems (WIS) use the Web paradigm (and technologies) to retrieve information from data sources and deliver it to the users. Due to their complex requirements the design of WIS is not a trivial task. Design methodologies provide guidelines for the creation of WIS so that the complexity of this process becomes manageable. Based on the separation-of-concerns principle some of these methodologies propose models to specify different aspects of WIS design like data integration, navigation structure, user interface, user interaction, presentation personalization, etc.

Recent advances in networking technologies enabled WIS access via different devices (e.g., PDA, Smart phone, PC, BlackBerry, etc.). In addition to this device heterogeneity there is also a heterogeneous audience (e.g., different backgrounds, different goals, etc.) that wants to access the same system. In order to improve the user experience, these systems often need to personalize the content and its presentation based on the current user needs (e.g., user’s browsing platform or user preferences).

Another aspect that can influence the behaviour of a WIS is the context of use (e.g., the geographical position, the temporal information, the weather conditions, etc.). Systems that are able to exploit this kind of information will further improve the application usefulness for their users. Integrating such information is possibly made available by specialized services and the need to seamlessly integrate these services into a WIS is therefore an important part of WIS development research.

As the Web data is very diverse, WIS are seeking efficient and flexible approaches to provide integrated views over heterogeneous data sources. These data sources are usually autonomous (maintained by different organizations), overlapping, frequently changing, and distributed. All these characteristics make the data integration on the Web a very challenging research topic.

The increased use of rich-clients applications (e.g., AJAX, OpenLaszlo, etc.) poses new demands to WIS design. The design of these applications needs to go beyond the server roundtrip paradigm by considering the new functionality added to clients, an intelligent data-push communication with the server, interactive-rich graphical interfaces, etc. Also, with the current emergence of social Web applications (e.g., Facebook, LinkedIn, MySpace, etc.) there is a need to properly model the highly dynamic aspects of these systems. In addition, WIS can tap into the data made available by these systems to provide for previously unforeseen functionalities. Making use of rich clients and allowing users to establish social networks are some of the features that need to be considered when developing Web 2.0 applications.

Semantic Web (also known as Web 3.0) technologies (e.g., RDF(S), OWL, etc.) can help in the representation and processing of the different WIS design models aiming for an improved interoperability. One example of such a model is the user profile which is often described using a CC/PP vocabulary. Due to their focus on distribution over the Web, Semantic Web representation languages prove to be useful also for specifying the semantics of data and the semantics of interfaces in order to facilitate the integration of heterogeneous databases and Web services, respectively. The best practice recommendation of Linked Data allows Web applications to seamlessly publish, interconnect, and access information on the Semantic Web. The inference mechanisms of the Semantic Web (captured in the semantics of the representation language or in rule-based languages like RuleML and SWRL) can be used for deriving new information or building intelligent services on the Web.

Over the last few years, Web services have offered new opportunities to deploy WIS. Web services are independent from specific platforms and computing paradigms, and have the capacity to form composed processes, referred to as composite Web services. Web services composition fulfils user requests that require the participation of several component Web services. Several composition languages are now available (e.g., BPEL, WSFL, etc.). Semantic descriptions of Web services are also proposed for automating composition (e.g., OWL-S, WSMO, WSDL-S, etc.). A research topic that is worth pursuing is the modeling of these composite Web services.
Goal of the Workshop

The aim of the workshop is to provide a platform for bringing together researchers, practitioners, designers, and users of WIS and discuss how specific issues of Web Information Systems (WIS) design can be addressed by means of modeling. Specifically, we will discuss how the influence of Semantic Web technology can help in a model-driven WIS development. Thus, the workshop should enable a fruitful exchange of ideas in the state-of-the-art of WIS modeling.
Topics of Interest

The workshop topics include but are not limited to:

Methodologies for WIS Design
WIS Mining
WIS Evolution
WIS Adaptability
WIS Personalization
WIS Ubiquity
WIS Architectures
WIS Economics
Web Services-Oriented System Architecture
DSL for WIS Design
Integration of WIS
Temporal/Spatial Representations in WIS
Rich Client WIS
Social WIS
Semantic WIS
Ontologies in WIS
Linked Data in WIS
Web Services
Semantic Web Services
Business Rules in WIS
Data Models in WIS
Semistructured Data in WIS
Web Metadata in WIS
Query Languages in WIS
Big Data in WIS
Optimization Techniques for WIS
Human Computation Models for WIS
Information Retrieval Models for WIS
Security in WIS
Crowd Phenomena in WIS
Sentiment Analysis in WIS
Modeling E-commerce Applications

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