Anastasios Gounaris
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View article: From Weather to Waypoints: Predicting Fuel Consumption and Optimizing Maritime Routes with ML and Graph Search
From Weather to Waypoints: Predicting Fuel Consumption and Optimizing Maritime Routes with ML and Graph Search Open
It will be submitted with the paper in a week.
View article: Unfolding Data Quality Dimensions in Practice: A Survey
Unfolding Data Quality Dimensions in Practice: A Survey Open
Data quality describes the degree to which data meet specific requirements and are fit for use by humans and/or downstream tasks (e.g., artificial intelligence). Data quality can be assessed across multiple high-level concepts called dimen…
View article: Handling out-of-order input arrival in CEP engines on the edge combining optimistic, pessimistic and lazy evaluation
Handling out-of-order input arrival in CEP engines on the edge combining optimistic, pessimistic and lazy evaluation Open
In Complex Event Processing, handling out-of-order, late, and duplicate events is critical for real-time analytics, especially on resource-constrained devices that process heterogeneous data from multiple sources. We present LimeCEP, a hyb…
View article: Stream DaQ: Stream-First Data Quality Monitoring
Stream DaQ: Stream-First Data Quality Monitoring Open
Data quality is fundamental to modern data science workflows, where data continuously flows as unbounded streams feeding critical downstream tasks, from elementary analytics to advanced artificial intelligence models. Existing data quality…
View article: Sequential pattern detection: similarities and differences across various fields
Sequential pattern detection: similarities and differences across various fields Open
Detecting pattern matches underpins key operations across fields, such as complex event processing (CEP), sequential pattern mining (SPM), string pattern matching, pattern mining from a large sequence, and business process mining. These fi…
View article: Storing and Querying Evolving Graphs in NoSQL Storage Models
Storing and Querying Evolving Graphs in NoSQL Storage Models Open
This paper investigates advanced storage models for evolving graphs, focusing on the efficient management of historical data and the optimization of global query performance. Evolving graphs, which represent dynamic relationships between e…
View article: Leveraging Feedback and Causality-Enriched Multimodal Context for Predictive Maintenance
Leveraging Feedback and Causality-Enriched Multimodal Context for Predictive Maintenance Open
We propose an anomaly detector-agnostic framework to exploit heterogeneous and multidimensional streams in industrial predictive maintenance, with the main objective of detecting early data anomalies preceding asset failures. Our novelty l…
View article: Investigating storage models for various types historical graphs
Investigating storage models for various types historical graphs Open
Our focus in this study revolves around enhancing the storage strategies for evolving graphs, particularly emphasizing the preservation and querying of their complete history. In particular, we review previous research on historical graph …
View article: A survey of open-source data quality tools: shedding light on the materialization of data quality dimensions in practice
A survey of open-source data quality tools: shedding light on the materialization of data quality dimensions in practice Open
Data Quality (DQ) describes the degree to which data characteristics meet requirements and are fit for use by humans and/or systems. There are several aspects in which DQ can be measured, called DQ dimensions (i.e. accuracy, completeness, …
View article: Engineering and evaluating an unsupervised predictive maintenance solution: a cold-forming press case-study
Engineering and evaluating an unsupervised predictive maintenance solution: a cold-forming press case-study Open
In real-world industries, production line assets may be affected by several factors, both known and unknown, which dynamically and unpredictably evolve so that past data are of little value for present ones. In addition, data is collected …
View article: A Comprehensive Scalable Framework for Cloud-Native Pattern Detection with Enhanced Expressiveness
A Comprehensive Scalable Framework for Cloud-Native Pattern Detection with Enhanced Expressiveness Open
Detecting complex patterns in large volumes of event logs has diverse applications in various domains, such as business processes and fraud detection. Existing systems like ELK are commonly used to tackle this challenge, but their performa…
View article: Optimizing the Execution of Product Data Models
Optimizing the Execution of Product Data Models Open
The Product Data Model (PDM) is an example of a declarative data-centric approach to modelling information-intensive business processes, which offers flexibility and facilitates process optimization. Declarative approaches are the de facto…
View article: Single Nucleotide Polymorphisms’ Causal Structure Robustness within Coronary Artery Disease Patients
Single Nucleotide Polymorphisms’ Causal Structure Robustness within Coronary Artery Disease Patients Open
An ever-growing amount of accumulated data has materialized in several scientific fields, due to recent technological progress. New challenges emerge in exploiting these data and utilizing the valuable available information. Causal models …
View article: Exploring alternatives of Complex Event Processing execution engines in demanding cases
Exploring alternatives of Complex Event Processing execution engines in demanding cases Open
Complex Event Processing (CEP) is a mature technology providing particularly efficient solutions for pattern detection in streaming settings. Nevertheless, even the most advanced CEP engines struggle to deal with cases when the number of p…
View article: Gene targeting in amyotrophic lateral sclerosis using causality-based feature selection and machine learning
Gene targeting in amyotrophic lateral sclerosis using causality-based feature selection and machine learning Open
Background Amyotrophic lateral sclerosis (ALS) is a rare progressive neurodegenerative disease that affects upper and lower motor neurons. As the molecular basis of the disease is still elusive, the development of high-throughput sequencin…
View article: Systematic exploitation of parallel task execution in business processes
Systematic exploitation of parallel task execution in business processes Open
Business process re-engineering (or optimization) has been attracting a lot of interest, and it is considered as a core element of business process management (BPM). One of its most effective mechanisms is task re-sequencing with a view to…
View article: A context-aware unsupervised predictive maintenance solution for fleet management
A context-aware unsupervised predictive maintenance solution for fleet management Open
We deal with the problem of predictive maintenance (PdM) in a vehicle fleet management setting following an unsupervised streaming anomaly detection approach. We investigate a variety of unsupervised methods for anomaly detection, such as …
View article: Demo: The RAINBOW Analytics Stack for the Fog Continuum
Demo: The RAINBOW Analytics Stack for the Fog Continuum Open
With the proliferation of raw Internet of Things (IoTs) data, Fog Computing is emerging as a computing paradigm for delay-sensitive streaming analytics with operators deploying big data distributed engines on Fog resources [1]. Nevertheles…
View article: Scalable real‑time health data sensing and analysis enabling collaborative care delivery
Scalable real‑time health data sensing and analysis enabling collaborative care delivery Open
This work describes a novel end-to-end data ingestion and runtime processing pipeline, which is a core part of a technical solution aiming to monitor frailty indices of patients during and after treatment and improve their quality of life.…
View article: A Collective Intelligence Platform to Support Older Cancer Survivors: Towards the Definition of LifeChamps System and Big Data Reference Architecture
A Collective Intelligence Platform to Support Older Cancer Survivors: Towards the Definition of LifeChamps System and Big Data Reference Architecture Open
Within the most recent years, most of the cancer patients are older age, which implies the necessity to a better understanding of aging and cancer connection. This work presents the LifeChamps solution built on top of cutting-edge Big Data…
View article: Rank-based Heuristics for Optimizing the Execution of Product Data Models
Rank-based Heuristics for Optimizing the Execution of Product Data Models Open
The Product Data Model (PDM) is an example of a data-centric approach to modelling information-intensive business processes, which offers exibility and facilitates process optimization. Because the approach is declarative in nature, there …
View article: Explainable Distance-Based Outlier Detection in Data Streams
Explainable Distance-Based Outlier Detection in Data Streams Open
Explaining outliers is a topic that attracts a lot of interest; however existing proposals focus on the identification of the relevant dimensions. We extend this rationale for unsupervised distance-based outlier detection, and through inve…
View article: Cost models for geo-distributed massively parallel streaming analytics
Cost models for geo-distributed massively parallel streaming analytics Open
This report is part of the DataflowOpt project on optimization of modern dataflows and aims to introduce a data quality-aware cost model that covers the following aspects in combination: (1) heterogeneity in compute nodes, (2) geo-distribu…
View article: Analysis of key flavors of event-driven predictive maintenance using logs of phenomena described by Weibull distributions
Analysis of key flavors of event-driven predictive maintenance using logs of phenomena described by Weibull distributions Open
This work explores two approaches to event-driven predictive maintenance in Industry 4.0 that cast the problem at hand as a classification or a regression one, respectively, using as a starting point two state-of-the-art solutions. For eac…
View article: Investigation of Database Models for Evolving Graphs
Investigation of Database Models for Evolving Graphs Open
We deal with the efficient implementation of storage models for time-varying graphs. To this end, we present an improved approach for the HiNode vertex-centric model based on MongoDB. This approach, apart from its inherent space optimality…