activity
20122026
most citedgraphVizdb: A Scalable Platform for Interactive Large Graph Visualization

41 citations · 55 across the 14 of their papers we have counts for

collaborators

17 papers

cs.DB2026

Human-Data Interaction, Exploration, and Visualization in the AI Era: Challenges and Opportunities

Jean-Daniel Fekete, Yifan Hu, Dominik Moritz +8

The rapid advancement of AI is transforming human-centered systems, with profound implications for human-AI interaction, human-data interaction, and visual analytics. In the AI era…

cs.AI2025

EmeraldMind: A Knowledge Graph-Augmented Framework for Greenwashing Detection

Georgios Kaoukis, Ioannis Aris Koufopoulos, Eleni Psaroudaki +4

As AI and web agents become pervasive in decision-making, it is critical to design intelligent systems that not only support sustainability efforts but also guard against misinform…

cs.DB2025

Adaptive Indexing for Approximate Query Processing in Exploratory Data Analysis

Stavros Maroulis, Nikos Bikakis, Vassilis Stamatopoulos +1

Minimizing data-to-analysis time while enabling real-time interaction and efficient analytical computations on large datasets are fundamental objectives of contemporary exploratory…

cs.DB2025

Visual Analytics Challenges and Trends in the Age of AI: The BigVis Community Perspective

Nikos Bikakis, Panos K. Chrysanthis, Guoliang Li +2

This report provides insights into the challenges, emerging topics, and opportunities related to human-data interaction and visual analytics in the AI era. The BigVis 2024 organizi…

cs.DB2024

Partial Adaptive Indexing for Approximate Query Answering

Stavros Maroulis, Nikos Bikakis, Vassilis Stamatopoulos +1

In data exploration, users need to analyze large data files quickly, aiming to minimize data-to-analysis time. While recent adaptive indexing approaches address this need, they are…

cs.LG2023★ 1 cited

Auditing for Spatial Fairness

Dimitris Sacharidis, Giorgos Giannopoulos, George Papastefanatos +1

This paper studies algorithmic fairness when the protected attribute is location. To handle protected attributes that are continuous, such as age or income, the standard approach i…

eess.SP2023

Data-driven soiling detection in PV modules

Alexandros Kalimeris, Ioannis Psarros, Giorgos Giannopoulos +3

Soiling is the accumulation of dirt in solar panels which leads to a decreasing trend in solar energy yield and may be the cause of vast revenue losses. The effect of soiling can b…

cs.DB2022★ 3 cited

QueryER: A Framework for Fast Analysis-Aware Deduplication over Dirty Data

Giorgos Alexiou, George Papastefanatos, Vassilis Stamatopoulos +2

In this work, we explore the problem of correctly and efficiently answering complex SPJ queries issued directly on top of dirty data. We introduce QueryER, a framework that seamles…

cs.DB2018

Hierarchical Characteristic Set Merging for Optimizing SPARQL Queries in Heterogeneous RDF

Marios Meimaris, George Papastefanatos

Characteristic sets (CS) organize RDF triples based on the set of properties characterizing their subject nodes. This concept is recently used in indexing techniques, as it can cap…

cs.HC2016★ 41 cited

graphVizdb: A Scalable Platform for Interactive Large Graph Visualization

Nikos Bikakis, John Liagouris, Maria Krommyda +2

We present a novel platform for the interactive visualization of very large graphs. The platform enables the user to interact with the visualized graph in a way that is very simila…

cs.HC2015

A Hierarchical Aggregation Framework for Efficient Multilevel Visual Exploration and Analysis

Nikos Bikakis, George Papastefanatos, Melina Skourla +1

Data exploration and visualization systems are of great importance in the Big Data era, in which the volume and heterogeneity of available information make it difficult for humans…

cs.HC2015

Towards Scalable Visual Exploration of Very Large RDF Graphs

Nikos Bikakis, John Liagouris, Maria Krommyda +2

In this paper, we outline our work on developing a disk-based infrastructure for efficient visualization and graph exploration operations over very large graphs. The proposed platf…

cs.DB2015★ 4 cited

A Framework for Managing Evolving Information Resources on the Data Web

Marios Meimaris, George Papastefanatos, Christos Pateritsas +2

The web of data has brought forth the need to preserve and sustain evolving information within linked datasets; however, a basic requirement of data preservation is the maintenance…

cs.DB2015

A Query Language for Multi-version Data Web Archives

Marios Meimaris, George Papastefanatos, Stratis Viglas +3

The Data Web refers to the vast and rapidly increasing quantity of scientific, corporate, government and crowd-sourced data published in the form of Linked Open Data, which encoura…

cs.DB2014

rdf:SynopsViz - A Framework for Hierarchical Linked Data Visual Exploration and Analysis

Nikos Bikakis, Melina Skourla, George Papastefanatos

The purpose of data visualization is to offer intuitive ways for information perception and manipulation, especially for non-expert users. The Web of Data has realized the availabi…

cs.DB2012★ 1 cited

Publishing Life Science Data as Linked Open Data: the Case Study of miRBase

Theodore Dalamagas, Nikos Bikakis, George Papastefanatos +2

This paper presents our Linked Open Data (LOD) infrastructures for genomic and experimental data related to microRNA biomolecules. Legacy data from two well-known microRNA database…

cs.DB2012★ 5 cited

Diachronic Linked Data: Towards Long-Term Preservation of Structured Interrelated Information

Yannis Stavrakas, George Papastefanatos, Theodore Dalamagas +1

The Linked Data Paradigm is one of the most promising technologies for publishing, sharing, and connecting data on the Web, and offers a new way for data integration and interopera…