Exploratory querying of SPARQL endpoints in space and time

Abstract

The linked data Web provides a simple and flexible way of accessing information resources in a self-descriptive format. This offers a realistic chance of perforating existing data silos. However, in order to do so, space, time and other semantic concepts need to function as dimensions for effectively exploring, querying and filtering contents. While triple stores, SPARQL endpoints, and RDF were designed for machine access, large burdens are still placed on a user to simultaneously explore and query the contents of a given endpoint according to these dimensions. First, one has to know the semantic concepts and the type of knowledge contained in an endpoint a-priori in order to query content effectively. Second, one has to be able to write and understand SPARQL and RDF. And third, one has to understand complex data type literals for space and time. In this article, we propose a way to deal with these challenges by interactive visual query construction, i.e., by letting query results feedback into both (space-time) exploration and filtering, and thus enabling exploratory querying. We propose design principles for SPEX (Spatio-temporal content explorer), a tool which helps people unfamiliar with the content of SPARQL endpoints or their syntax to explore the latter in space and time. In a preliminary user study on a repository of historical maps, we found that our feedback principles were effective, however, that successful question answering still requires improvements regarding space-time filtering, vocabulary explanation and the linking of space-time windows with other displays.

Semantic typing of linked geoprocessing workflows

“…Once operations are registered, workflow typing and retrieval can be done in an automated or semi-automated fashion, without GIS users having to deal with the complexities of linked data or SPARQL syntax, and without requiring any web GIS service interfaces. For example, exploratory query interfaces or web forms can be used for retrieval (Scheider et al 2017). Future work should therefore address the development of algorithms to generate enrichment rules for GIS tools and automated capturing and RDF transformation of workflows, within tools such as ArcGIS and R. Regularities in the enrichment rules should be identified, and codified into ontology design patterns, supporting the incremental inclusion of new GIS tools in the framework.…”

Using knowledge anchors to facilitate user exploration of data graphs

“…The interface allows users to create SPARQL queries using a set of graphical notations and editing actions. The state-of-the-art in approaches to support visual SPARQL query construction is presented in [35]. The focus of these works is in supporting layman users to perform exploratory querying of RDF graphs in space and time, which themes with interactive visual query construction methods.…”

“…The focus of these works is in supporting layman users to perform exploratory querying of RDF graphs in space and time, which themes with interactive visual query construction methods. The authors present a number of design principles to counter the challenges and evaluate them in a usability study on finding maps in a historical map repository [35]. Although these approaches hide the complexity of graph terminologies, they primarily focus on helping layman users to generate SPARQL queries instead of focusing on the properties of data graphs to guide users' exploration.…”

Deeply integrating Linked Data with Geographic Information Systems

“…There are particular advantages to both for handling and processing information that ideally should be preserved from one world to the other. For example, a particular strength of Linked Data is that metadata are on the same syntactical level as data (Kuhn et al., ), enabling exploratory querying (Scheider et al., ) and, thus, meaningful exploration of what geospatial data are available (Olieman, Kamps, & Claros, ) without relying on a separate catalog service. In this way, available RDF properties that link resources to their attributes or to other objects can be explored by users in visual graphs and maps using SPARQL (Mai et al., ; Scheider et al., ).…”