Adriano Savoca

Exploration of cultural heritage information via textual search queries

Searching information in a Geographical Information System (GIS) usually imposes that users explore precompiled category catalogs and select the types of information they are looking for. Unfortunately, that approach is challenging because it forces people to adhere to a conceptualization of the information space that might be different from their own. In order to address this issue, we propose to support textual search as the basic interaction model, exploiting linguistic information, together with category exploration, for query interpretation and expansion. This paper describes our model and its adoption in the OnToMap Participatory GIS.

OnToMap: Semantic Community Maps for Knowledge Sharing

We present the information retrieval model adopted in the OnToMap Participatory GIS. The model addresses the limitations of keyword-based and category-based search by semantically interpreting the information needs specified in free-text search queries. The model is based on an ontological representation of linguistic and encyclopaedic knowledge, which makes it possible to exploit terms and synonyms occurring in the definitions of concepts to flexibly match the users and systems terminologies. This feature enables users to query the application using their own vocabulary.

Semantic Interpretation of Search Queries for Personalization

This demo paper describes the semantic query interpretation model adopted in the OnToMap Participatory GIS and presents its benefits to information retrieval and personalized information presentation.

Concept-aware geographic information retrieval

Textual queries are largely employed in information retrieval to let users specify search goals in a natural way. However, differences in user and system terminologies can challenge the identification of the users information needs, and thus the generation of relevant results. We argue that the explicit management of ontological knowledge, and of the meaning of concepts (by integrating linguistic and encyclopaedic knowledge in the system ontology), can improve the analysis of search queries, because it enables a flexible identification of the topics the user is searching for, regardless of the adopted vocabulary. This paper proposes an information retrieval support model based on semantic concept identification. Starting from the recognition of the ontology concepts that the search query refers to, this model exploits the qualifiers specified in the query to select information items on the basis of possibly fine-grained features. Moreover, it supports query expansion and reformulation by suggesting the exploration of semantically similar concepts, as well as of concepts related to those referred in the query through thematic relations. A test on a data-set collected using the OnToMap Participatory GIS has shown that this approach provides accurate results.

Map-based visualization of 2D/3D spatial data via stylization and tuning of information emphasis

In Geographical Information search, map visualization can challenge the user because results can consist of a large set of heterogeneous items, increasing visual complexity. We propose a novel visualization model to address this issue. Our model represents results as markers, or as geometric objects, on 2D/3D layers, using stylized and highly colored shapes to enhance their visibility. Moreover, the model supports interactive information filtering in the map by enabling the user to focus on different data categories, using transparency sliders to tune the opacity, and thus the emphasis, of the corresponding data items. A test with users provided positive results concerning the efficacy of the model.

WeGovNow: A Map Based Platform to Engage the Local Civic Society.

In this paper we describe the advancement of WeGovNow, an Horizon 2020 European Union project involving twelve partners from Germany, Sweden, Greece, Italy and United Kingdom, aimed at using state-of-the-art digital technologies in community engagement platforms to involve citizens in decision making processes within their local neighbourhood. Different software components, both previously existing and developed specially for the project and covering separate aspects of community engagement, were integrated in a single web platform offering an homogeneous experience to the users. One of the main common threads beyond this integration process is the ability to collect crowd mapped information and show them back to the users in an engaging way on maps, harmonizing data coming from the different components and making the mapped space easily explorable.

Supporting Knowledge Sharing and Learning via Semantic Geographical Maps

Map-based applications are a good starting point for helping teachers in the preparation of learning material and students in their researches in social sciences. However, they offer basic information filtering support to the generation of dynamic maps. In this paper, we investigate the adoption of semantic knowledge representation and cooperative work approaches for managing thematic maps in group-based learning activities. Moreover, we present a possible solution, based on the OnToMap Participatory GIS, which uses an ontological representation of geographical information to support multi-faceted information retrieval, crowdsourcing, and map creation.

Transparency-based information filtering on 2D/3D geographical maps

The presentation of search results in GIS can expose the user to cluttered geographical maps, challenging the identification of relevant information. In order to address this issue, we propose a visualization model supporting interactive information filtering on 2D/3D maps. Our model is based on the introduction of transparency sliders that enable the user to tune the opacity, and thus the emphasis, of data categories in the map. In this way, he or she can focus the maps on the most relevant types of information for the task to be performed. A test with users provided positive results concerning the efficacy of our model.

Representing Ecological Network Specifications with Semantic Web Techniques

Ecological Networks (ENs) are a way to describe the structures of existing real ecosystems and to plan their expansion, conservation and improvement. In this work, we present a model to represent the specifications for the local planning of ENs in a way that can support reasoning, e.g., to detect violations within new proposals of expansion, or to reason about improvements of the networks. Moreover, we describe an OWL ontology for the representation of ENs themselves. In the context of knowledge engineering, ENs provide a complex, inherently geographic domain that demands for the expressive power of a language like OWL augmented with the GeoSPARQL ontology to be conveniently represented. More importantly, the set of specification rules that we consider (taken from the project for a local EN implementation) constitute a challenging problem for representing constraints over complex geographic domains, and evaluating whether a given large knowledge base satisfies or violates them.

Personalised community maps

With the convergence of geographical information systems (GIS) and internet technology, the public administration is starting to use online maps as a web-based bidirectional communication channel with the population: maps are used: i) in public portals, for publishing and crowdsourcing information about the territory; ii) in policy-making, for defining a community vision of the territory and for involving people in public choices. Both cases raise challenges related to the large amount of data handled in the maps, and to their lack of group collaboration support. We attempted to address these issues by developing an information-sharing model, and a testbed software application, that support group management and the generation of persistent, custom community maps focused on the users interests. Our model builds on tag-based user profiles and on information filtering. This paper describes our model and the results of an evaluation of the GroupMapping application, based on it.