Using Linked Data for Prosopographical Research of Historical Persons : Case U.S. Congress Legislators

This paper shows how biographical registries can be represented as Linked Data, enriched by data linking to related data sources, and used in Digital Humanities. As a use case, a database of 11 987 historical U.S. Congress Legislators in 1789–2018 was transformed into a knowledge graph. The data was published as a Linked Data service, including a SPARQL endpoint, on top of which tools for biographical and prosopographical research are implemented. A faceted browser named U.S. Congress Prosopographer with visualization tools for knowledge discovery is presented to provide new insights in political history.Peer reviewe

Personal Semantics

International audienceQuantified self, life logging, digital eyeglasses, technology is ad- vancing rapidly to a point where people can gather masses of data about their own persons and their own life. Large-scale models of what people are doing are being built by credit companies, advertising agencies, and national security agencies, using digital traces that people leave behind them. How can individuals exploit their own data for their own benefit? With this mass of personal data, we will need to induce personal semantic dimensions to sift data and find what is meaningful to each individual. In this chapter, we present semantic dimensions, made by experts, and by crowds. We show the type of information that individuals will have access to once lifelogging becomes common, and we will sketch what personal semantic dimensions might look like

A Sparse Stress Model

Force-directed layout methods constitute the most common approach to draw general graphs. Among them, stress minimization produces layouts of comparatively high quality but also imposes comparatively high computational demands. We propose a speed-up method based on the aggregation of terms in the objective function. It is akin to aggregate repulsion from far-away nodes during spring embedding but transfers the idea from the layout space into a preprocessing phase. An initial experimental study informs a method to select representatives, and subsequent more extensive experiments indicate that our method yields better approximations of minimum-stress layouts in less time than related methods.Comment: Appears in the Proceedings of the 24th International Symposium on Graph Drawing and Network Visualization (GD 2016

Query Extension Suggestions for Visual Query Systems Through Ontology Projection and Indexing

Ontology-based visual query formulation is a viable alternative to textual query editors in the Semantic Web domain for extracting data from structured data sources in terms of the skills and knowledge required. A visual query system is at any moment responsible for providing the user with query extension suggestions; however, suggestions leading to empty results are often not useful. To this end, in this article, we first present an approach for projecting OWL 2 ontologies into navigation graphs to be used for query formulation and then a solution where an efficient finite index is used to calculate non-ranked approximated extension suggestions for ontology-based visual query systems using navigation graphs. The results of our experiments suggest that one can efficiently project an ontology into a navigation graph, query it for running an interactive user interface, and suggest query extensions that do not lead to dead-ends

Retrieving haystacks: a data driven information needs model for faceted search.

The research aim was to develop an understanding of information need characteristics for word co-occurrence-based search result filters (facets). No prior research has been identified into what enterprise searchers may find useful for exploratory search and why. Various word co-occurrence techniques were applied to results from sample queries performed on industry membership content. The results were used in an international survey of 54 practising petroleum engineers from 32 organizations. Subject familiarity, job role, personality and query specificity are possible causes for survey response variation. An information needs model is presented: Broad, Rich, Intriguing, Descriptive, General, Expert and Situational (BRIDGES). This may help professionals to more effectively meet their information needs and stimulate new needs, improving a systems ability to facilitate serendipity. This research has implications for faceted search in enterprise search and digital library deployments

A task completion engine to enhance search session support for air traffic work tasks

Providing support for users during their search sessions has been hailed as a major challenge in interactive information retrieval (IIR). Providing such support requires considering the context of the search and facilitating the work task at hand. In this paper, we consider the work tasks associated with air traffic analysts, who perform numerous searches using a multifaceted search interface in order to acquire business intelligence regarding particular events and situations. In particular, we develop a novel task completion engine and seamlessly incorporated it within a current air traffic search system to facilitate the comparison of information objects found. In a study with 24 participants, we found that they completed the complex work task faster using the comparison feature, but for simple work tasks, participants were slower. However, participants reported (statistically) significantly higher satisfaction and had (statistically) significantly higher accuracy using the search system equipped with task completion engine. These findings help to steer systems to provide a better support to users in their search process. © Springer International Publishing AG 2017