arXiv subjects

Jean-Daniel Fekete

Publications and source records attributed to Jean-Daniel Fekete.

21 records · Page 2Linked to original sources

arXiv2016

The CENDARI Infrastructure

The CENDARI infrastructure is a research supporting platform designed to provide tools for transnational historical research, focusing on two topics: Medieval culture and World War I. It exposes to the end users modern web-based tools relying on a sophisticated infrastructure to collect, enrich, annotate, and search through large document corpora. Supporting researchers in their daily work is a novel concern for infrastructures. We describe how we gathered requirements through multiple methods to understand the historians' needs and derive an abstract workflow to support them. We then outline the tools we have built, tying their technical descriptions to the user requirements. The main tools are the Note Taking Environment and its faceted search capabilities, the Data Integration platform including the Data API, supporting semantic enrichment through entity recognition, and the environment supporting the software development processes throughout the project to keep both technical partners and researchers in the loop. The outcomes are technical together with new resources developed and gathered, and the research workflow that has been described and documented.

cs.DL↗

arXiv2016

Progressive Analytics: A Computation Paradigm for Exploratory Data Analysis

Exploring data requires a fast feedback loop from the analyst to the system, with a latency below about 10 seconds because of human cognitive limitations. When data becomes large or analysis becomes complex, sequential computations can no longer be completed in a few seconds and data exploration is severely hampered. This article describes a novel computation paradigm called Progressive Computation for Data Analysis or more concisely Progressive Analytics, that brings at the programming language level a low-latency guarantee by performing computations in a progressive fashion. Moving this progressive computation at the language level relieves the programmer of exploratory data analysis systems from implementing the whole analytics pipeline in a progressive way from scratch, streamlining the implementation of scalable exploratory data analysis systems. This article describes the new paradigm through a prototype implementation called ProgressiVis, and explains the requirements it implies through examples.

cs.HC↗

arXiv2007

NodeTrix: Hybrid Representation for Analyzing Social Networks

The need to visualize large social networks is growing as hardware capabilities make analyzing large networks feasible and many new data sets become available. Unfortunately, the visualizations in existing systems do not satisfactorily answer the basic dilemma of being readable both for the global structure of the network and also for detailed analysis of local communities. To address this problem, we present NodeTrix, a hybrid representation for networks that combines the advantages of two traditional representations: node-link diagrams are used to show the global structure of a network, while arbitrary portions of the network can be shown as adjacency matrices to better support the analysis of communities. A key contribution is a set of interaction techniques. These allow analysts to create a NodeTrix visualization by dragging selections from either a node-link or a matrix, flexibly manipulate the NodeTrix representation to explore the dataset, and create meaningful summary visualizations of their findings. Finally, we present a case study applying NodeTrix to the analysis of the InfoVis 2004 coauthorship dataset to illustrate the capabilities of NodeTrix as both an exploration tool and an effective means of communicating results.

cs.HC↗