Related papers: Integrating Knowledge Graphs and Visualization Das…

The exponential growth of scientific literature requires effective management and extraction of valuable insights. While existing scientific search engines excel at delivering search results based on relational databases, they often neglect…

The rapid growth of publicly available textual resources, such as lexicons and domain-specific corpora, presents challenges in efficiently identifying relevant resources. While repositories are emerging, they often lack advanced search and…

In this paper we show how advanced visualization tools can help the researcher in investigating and extracting information from data. The focus is on VisIVO, a novel open source graphics application, which blends high performance…

Scientists always look for the most accurate and relevant answers to their queries in the literature. Traditional scholarly digital libraries list documents in search results, and therefore are unable to provide precise answers to search…

Data-driven discoveries require identifying relevant data relationships from a sea of complex, unstructured, and heterogeneous scientific data. We propose a hybrid methodology that extracts metadata and leverages scientific domain knowledge…

Scientists have always used the studies and research of other researchers to achieve new objectives and perspectives. In particular, employing and operating the measured data in previous studies is so practical. Searching the content of…

The rapid growth in the volume, variety, and velocity of geospatial data has created data ecosystems that are highly distributed, heterogeneous, and semantically inconsistent. Existing data catalogs, portals, and infrastructures still rely…

Here we present a holistic approach for data exploration on dense knowledge graphs as a novel approach with a proof-of-concept in biomedical research. Knowledge graphs are increasingly becoming a vital factor in knowledge mining and…

Interactive visualizations for exploring and retrieval have not yet become an integral part of digital libraries and information retrieval systems. We have integrated a set of interactive graphics in a real world social science digital…

One of the most useful techniques to help visual data analysis systems is interactive filtering (brushing). However, visualization techniques often suffer from overlap of graphical items and multiple attributes complexity, making visual…

Finding inherent or processed links within a dataset allows to discover potential knowledge. The main contribution of this article is to define a global framework that enables optimal knowledge discovery by visually rendering co-occurences…

Knowing how to construct text-based Search Queries (SQs) for use in Search Engines (SEs) such as Google or Wikipedia has become a fundamental skill. Though much data are available through such SEs, most structured datasets live outside…

This paper describes an ongoing multi-scale visual analytics approach for exploring and analyzing biomedical knowledge at scale.We utilize global and local views, hierarchical and flow-based graph layouts, multi-faceted search, neighborhood…

Draco has been developed as an automated visualization recommendation system formalizing design knowledge as logical constraints in ASP (Answer-Set Programming). With an increasing set of constraints and incorporated design knowledge, even…

We present Ver, a data discovery system that identifies project-join views over large repositories of tables that do not contain join path information, and even when input queries are inaccurate. Ver implements a reference architecture to…

Data visualization techniques proffer efficient means to organize and present data in graphically appealing formats, which not only speeds up the process of decision making and pattern recognition but also enables decision-makers to fully…

Exploratory search is an open-ended information retrieval process that aims at discovering knowledge about a topic or domain rather than searching for a specific answer or piece of information. Conversational interfaces are particularly…

Over the past decades, research institutions have grown increasingly and consequently also their research output. This poses a significant challenge for researchers seeking to understand the research landscape of an institution. The process…

As the number of scientific publications and preprints is growing exponentially, several attempts have been made to navigate this complex and increasingly detailed landscape. These have almost exclusively taken unsupervised approaches that…

Thanks to recent advancements in machine learning, vector-based methods have been adopted in many modern information retrieval (IR) systems. While showing promising retrieval performance, these approaches typically fail to explain why a…