The MoDeST workshop aims to bring together researchers, as well as developers and practitioners, who are interested in studying and deploying Semantic Web technology on mobile devices, as well as illustrating its useful deployment in particular application domains.
Given the current scale and diversity of the Semantic Web, there is a clear potential for mobile devices to exploit online semantic data; including semantic geographical information (LinkedGeoData, GeoNames), information on people, places & things (FreeBase, DataHub, DBpedia), online news sources (NYTimes), products for sale (BestBuy), etc. In fact, various application domains have already demonstrated the utility of mobile semantic data, including context-awareness, augmented reality, recommender systems, tourism, and mHealth. Due to recent improvements in mobile hardware, an opportunity currently exists to fully realize this potential and empower mobile applications with fully-fledged semantic capabilities. Previous work has shown that mobile solutions should be tailored towards the unique restrictions of mobile devices, as well as the highly dynamic nature of mobile application scenarios. While valuable work has already been done in this regard (including several mobile RDF stores and mobile reasoners), recent studies have indicated that the mobile performance & scalability of certain Semantic Web tasks (e.g., rule-based/OWL reasoning) still leaves much to be desired. In addition to investigating and realizing tailored solutions, the development of effective and useful mobile Semantic Web applications will undoubtedly act as a catalyst for increasing efforts in realizing efficient, mobile back-end solutions.
The MoDeST workshop represents an ideal venue to publish qualitative, albeit work-in-progress, research on this topic, and to present useful mobile Semantic Web applications. In contrast to the potential of this field, combined with the interest already shown - as illustrated by publicly available frameworks supporting mobile RDF processing (e.g., AndroJena, RDF On The Go), and the breadth of application domains where it has been applied - no relevant workshops are currently being organized, or have in fact been organized in recent years. As such, the MoDeST workshop presents a unique forum for researchers from both the Semantic Web and mobile computing community, to discuss approaches, techniques and concrete implementations for the efficient utilization of mobile Semantic Web technology.
The topics of interest include, but are not limited to:
All papers must represent original, unpublished work not currently under review elsewhere. Papers will be evaluated according to their significance, originality, technical quality, clarity, style and relevance to the workshop. At least one author of each accepted paper is expected to attend the workshop.
Workshop participation is available to ISWC 2015 attendants at an additional cost. See http://iswc2015.semanticweb.org/registration for details.
Paper submission and reviewing for this workshop will be done electronically via EasyChair. All submissions must be written in English and must be formatted according to the information for LNCS Authors (see http://www.springer.com/computer/lncs?SGWID=0-164-6-793341-0). We aim to publish the workshop proceedings online at CEUR-WS.
The following types of contributions are welcome:
Please refer to the EasyChair page (https://easychair.org/conferences/?conf=modest2015) for paper submission.
The MoDeST workshop proceedings are published as CEUR-WS volume 1506.
E.W. Patton, W. Van Woensel, R. Yus: Proceedings of the International Workshop on Mobile Deployment of Semantic Technologies (MoDeST 2015), Bethlehem, Pennsylvania, USA. CEUR Workshop Proceedings, vol. 1506, CEUR-WS.org, 2015.
Jeff Z. Pan received his Ph.D. in computer science from The University of Manchester in 2004, on the topic of Description Logics: Reasoning Support for the Semantic Web. He joined the faculty in the Department of Computing Science at University of Aberdeen in 2005. He is now the Deputy Director of Research of the department. His research focuses primarily on knowledge representation and reasoning, in particular scalable ontology reasoning, querying and reuse, and their applications (such as Semantic Web, Advertising, Healthcare, Software Engineering and Multimedia). He is a key contributor to the W3C OWL2 standard. He leads the work of the TrOWL Tractable OWL2 reasoning infrastructure. He is widely recognised for his work on scalable and efficient ontology reasoning; he gave tutorials on this topic in e.g. AAAI2010, ESWC2010, ESWC2011, SemTech2011 and the Reasoning Web Summer School (2010 and 2011).
The Ubiquitous Semantic Web: The Story So Far
Semantic Web technologies make it possible to represent, integrate, query and reason about structured online data. Recent years have witnessed tremendous growth of mobile computing, represented by the widespread adoption of smart phones and tablets. The versatility of such smart devices and the capabilities of semantic technologies form a great foundation for a ubiquitous Semantic Web that will contribute to further realising the true potential of both disciplines. In this talk, I will provide a brief overview of state-of-the-art research in this emerging area and try to conclude with a summary of challenges and important research problems.
With the wide-spread availability of cheap but powerful mobile devices and high-speed mobile Internet, we are witnessing an increase in the development of mobile applications (apps). These apps could benefit from the advantages of the Semantic Web, such as, for example, knowledge sharing and reusing. The goal of this systematic review is to perform an exhaustive study on what semantic mobile apps have been already developed. The systems have been selected from a manual survey of conference proceedings as well as searching using Google Scholar. We have found 36 semantic mobile apps in this survey and presented a brief overview of each one. We believe that these results would help in identifying most popular domains, platforms, and semantic technologies used as well as highlighting problems and challenges to address for development of semantic mobile apps.
The number of mobile applications (apps) in major app stores exceeded one million in 2013. While app stores provide a central point for storing app metadata, they often impose restrictions on the access to this information thus limiting the potential to develop tools to search, recommend, and analyze app information. A few projects have circumvented these limitations and managed to create a dataset with a substantial number of apps. However, accessing this information, especially for the purpose of an integrated view, is difficult as there is no common standard for publishing data. We present Mobipedia, an effort to gather this information from various sources and publish it as RDF Linked Data. We describe the status of Mobipedia, which currently has information on more than one million apps that has been extracted from a number of unstructured and semi-structured sources. This paper describes the ontology used to model information, the process for fact extraction, and an overview of applications facilitated by Mobipedia.
We present a scenario for a mobile wine recommendation agent where semantic technologies can provide value to end users. The wine recommender uses an ontology in the SHOIN (d) description logic, and is extended to consider energy consumption of the device, intensional social contexts, and reasoning in a privacy-aware manner. We discuss the challenges semantic technologies, especially ones based on Description Logics, face in this scenario and formulate key issues for the mobile semantic technology community to address.
In the past few decades, the field of ecology has grown from a collection of disparate researchers who collected data on their local phenomenon by hand, to large ecosystems-oriented projects partially fueled by automated sensor networks and a diversity of models and experiments. These modern projects rely on sharing and integrating data to answer questions of increasing scale and complexity. Interpreting and sharing the big data sets generated by these projects relies on information about how the data was collected and what the data is about, typically stored as metadata. Metadata ensures that the data can be interpreted and shared accurately and efficiently. Traditional paper-based metadata collection methods are slow, error-prone, and non-standardized, making data sharing difficult and inefficient. Semantic technologies offer opportunities for better data management in ecology, but also may pose a challenging learning curve to already busy researchers. This paper presents a mobile application for recording semantic metadata about sensor network deployments and experimental settings in real time, in the field, and without expecting prior knowledge of semantics from the users. This application enables more efficient and less error-prone in-situ metadata collection, and generates structured and shareable metadata.
The smartphone applications ecosystem lacks significant controls and accountability mechanisms to protect users' privacy from snooping applications, especially when context may significantly impact the decision to share sensitive information. In this paper, we discuss some of the existing privacy concerns of mobile applications. In particular we highlight how semantic web and linked data technologies have the potential to help improve privacy controls through rules, queries, and reasoning. These technologies have the potential to obtain and maintain the integrity of private data, but there are privacy challenges that may result from widespread deployment of mobile semantic technologies.
While mobile computing domains have illustrated the usefulness of mobile semantic data, improvements in mobile hardware are paving the way for local semantic data access. To support this, a number of tools have been developed for storing, querying and reasoning over local semantic data. However, recent benchmarks have shown that mobile hardware still imposes limitations on efficient local data querying. Additionally, mobile scenarios pose unique challenges due to their dynamic nature; making it difficult to replicate semantic data a priori for local querying. In this paper, we propose a graph-based query distribution approach, which efficiently distributes query execution across configured remote datasets. Importantly, our approach aims to identify subqueries that can be outsourced to remote datasets, thus reducing local joining work.