Semantic web technology to support learning about the semantic web

This paper describes ASPL, an Advanced Semantic Platform for Learning, designed using the Magpie framework with an aim to support students learning about the Semantic Web research area. We describe the evolution of ASPL and illustrate how we used the results from a formal evaluation of the initial system to re-design the user functionalities. The second version of ASPL semantically interprets the results provided by a non-semantic web mining tool and uses them to support various forms of semantics-assisted exploration, based on pedagogical strategies such as performing later reasoning steps and problem space filtering

An Approach to Publish Spatial Data on the Web: The GeoLinked Data Case

In this paper we report on an ongoing process aimed at publishing hydrographical data on the Web with a Spanish GeoLinked Data Use Case. Moreover, we discuss the process we followed, and propose methodological guidelines for all the activities involved within the process

User interfaces supporting entity search for linked data

One of the main goals of semantic search is to retrieve and connect information related to queries, offering users rich structured information about a topic instead of a set of documents relevant to the topic. Previous work reports that searching for information about individual entities such as persons, places and organisations is the most common form of Web search. Since the Semantic Web was first proposed, the amount of structured data on the Web has increased dramatically. This is particularly the case for what is known as Linked Data, information that has been published using Semantic Web standards such as RDF and OWL. Such structured data opens up new possibilities for improving entity search on the Web, integrating facts from independent sources, and presenting users with contextually-rich information about entities. This research focuses on entity search of Linked Data in terms of three different forms of search: structured queries, where users can use the SPARQL query language for manipulating data sources; exploratory search, where users can browse from one entity to another; and focused search, where users can input an entity query as a free text keyword search. We undertake a comparative study between two distinct information architectures for structured querying to manipulate Linked Data over the Web. Specifically, we evaluate some of the main operators in SPARQL using several datasets of Linked Data. We introduce a framework of five criteria to evaluate 15 current state-of-the-art semantic tools available for exploratory search of Linked Data, in order to establish how well these browsers make available the benefits of Linked Data and entity search for human users. We also use the criteria to determine the browsers that are best suited to entity exploration. Further, we propose a new model, the Attribute Importance Model, for entity-aggregated search, with the purpose of improving user experience when finding information about entities. The model develops three techniques: (1) presenting entity type-based query suggestions; (2) clustering aggregated attributes; and (3) ranking attributes based on their importance to a given query. Together these constitute a model for developing more informative views and enhancing users’ understanding of entity descriptions on the Web. We then use our model to provide an interactive approach, with the Information Visualisation toolkit InfoVis, that enables users to visualise entity clusters generated by our Attribute Importance Model. Thus this thesis addresses two challenges of searching Linked Data. The first challenge concerns the specific issue of information resolution during the search: the reduction of query ambiguity and redundant results that contain irrelevant descriptions when searching for information about an entity. The second challenge concerns the more general problem of technical complexity, and addresses to the limited adoption of Linked Data that we ascribe to the lack of understanding of Semantic Web technologies and data structures among general users. These technologies pose new design problems for human interaction such as overloading data, navigation styles, and browsing mechanisms. The Attribute Importance Model addresses both these challenges

Understanding “influence”: An exploratory study of academics’ process of knowledge construction through iterative and interactive information seeking

The motivation for this study is to better understand the searching and sensemaking processes undertaken to solve exploratory tasks for which people lack pre-existing frames. To investigate people’s strategies for that type of task, we focused on “influence” tasks because, although they appear to be unfamiliar, they arise in much academic discourse, at least tacitly. This qualitative study reports the process undertaken by academics of different levels of seniority to complete exploratory search tasks that involved identifying influential members of their academic community and “rising stars, ” and to identify similar roles in an unfamiliar academic community. 11 think-aloud sessions followed by semi-structured interviews were conducted to investigate the role of specific and general domain expertise in the process of information seeking and knowledge construction. Academics defined and completed the task through an iterative and interactive process of seeking and sensemaking, during which they constructed an understanding of their communities and determined qualities of “being influential”. Elements of the Data/Frame Theory of Sensemaking (Klein et al., 2007) were used as sensitising theoretical constructs. The study shows that both external and internal knowledge resources are essential to define a starting point or frame, make and support decisions, and experience satisfaction. Ill-defined or non-existent initial frames may cause unsubstantial or arbitrary decisions, and feelings of uncertainty and lack of confidence

mSpace meets EPrints: a Case Study in Creating Dynamic Digital Collections

In this case study we look at issues involved in (a) generating dynamic digital libraries that are on a particular topic but span heterogeneous collections at distinct sites, (b) supplementing the artefacts in that collection with additional information available either from databases at the artefact's home or from the Web at large, and (c) providing an interaction paradigm that will support effective exploration of this new resource. We describe how we used two available frameworks, mSpace and EPrints to support this kind of collection building. The result of the study is a set of recommendations to improve the connectivity of remote resources both to one another and to related Web resources, and that will also reduce problems like co-referencing in order to enable the creation of new collections on demand

Improving Exploratory Search Interfaces: Adding Value or Information Overload?

One method for supporting more exploratory forms of search has been to include a compound of new interface features, such as facets, previews, collection points, synchronous communication, and note-taking spaces, within a single search interface. One side effect, however, is that some compounds can be confusing, rather than supportive during search. Faceted browsing, for example, conveys domain terminology and supports rich interaction, but can potentially present an abundance of information. In this paper we focus on the faceted example and conclude with our position that Cognitive Load Theory can be used to estimate and thus manage the potential complexities of adding new features to search interfaces

Integrating musicology's heterogeneous data sources for better exploration

Musicologists have to consult an extraordinarily heterogeneous body of primary and secondary sources during all stages of their research. Many of these sources are now available online, but the historical dispersal of material across libraries and archives has now been replaced by segregation of data and metadata into a plethora of online repositories. This segregation hinders the intelligent manipulation of metadata, and means that extracting large tranches of basic factual information or running multi-part search queries is still enormously and needlessly time consuming. To counter this barrier to research, the “musicSpace” project is experimenting with integrating access to many of musicology’s leading data sources via a modern faceted browsing interface that utilises Semantic Web and Web2.0 technologies such as RDF and AJAX. This will make previously intractable search queries tractable, enable musicologists to use their time more efficiently, and aid the discovery of potentially significant information that users did not think to look for. This paper outlines our work to date