Knowledge Organization Systems (KOS) in the Semantic Web: A Multi-Dimensional Review

Since the Simple Knowledge Organization System (SKOS) specification and its SKOS eXtension for Labels (SKOS-XL) became formal W3C recommendations in 2009 a significant number of conventional knowledge organization systems (KOS) (including thesauri, classification schemes, name authorities, and lists of codes and terms, produced before the arrival of the ontology-wave) have made their journeys to join the Semantic Web mainstream. This paper uses "LOD KOS" as an umbrella term to refer to all of the value vocabularies and lightweight ontologies within the Semantic Web framework. The paper provides an overview of what the LOD KOS movement has brought to various communities and users. These are not limited to the colonies of the value vocabulary constructors and providers, nor the catalogers and indexers who have a long history of applying the vocabularies to their products. The LOD dataset producers and LOD service providers, the information architects and interface designers, and researchers in sciences and humanities, are also direct beneficiaries of LOD KOS. The paper examines a set of the collected cases (experimental or in real applications) and aims to find the usages of LOD KOS in order to share the practices and ideas among communities and users. Through the viewpoints of a number of different user groups, the functions of LOD KOS are examined from multiple dimensions. This paper focuses on the LOD dataset producers, vocabulary producers, and researchers (as end-users of KOS).Comment: 31 pages, 12 figures, accepted paper in International Journal on Digital Librarie

NEMO: Internet of Things based Real-time Noise and Emissions MOnitoring System for Smart Cities

With the advent of ubiquitous sensors and Internet of Things (IoT) applications, research and development initiatives on smart cities are ramping up worldwide. It enables remote monitoring, management, and control of devices and the generation of fresh and actionable insight from huge quantities of real-time data. Real-time noise and emissions monitoring of vehicles remain indispensable in a smart city context. Effective management and control of noise and emissions of vehicles on the road are necessary and possible through analyzing lots of sensor data in real-time to take an actionable insight. To contribute to this, as part of an ongoing effort of the European Union project called ''NEMO: Noise and Emissions Monitoring and Radical Mitigation'', in this paper, we present the design and development of an IoT-based real-time noise and emissions monitoring system for vehicles in a smart city context. Real-world sensor data of the vehicles in some European cities are collected during the pilot tests. We have developed a complete application for infrastructure managers and analysts to monitor the sensor data related to noise and emissions of vehicles in real-time. The data of the individual road vehicles and trains in selected EU cities and from trains on a track in the Netherlands are collected in the cloud and analyzed with artificial intelligence (AI) algorithms for classification such as high emitter, medium emitter, and normal emitters. We present the development of a complete software solution that can be integrated with existing intelligent transportation systems in smart cities. Finally, we report the initial vehicle classification results from the Rotterdam (Netherlands) pilot test as a representative example for the NEMO monitoring system.acceptedVersio

Advancements and Challenges in Object-Centric Process Mining: A Systematic Literature Review

Recent years have seen the emergence of object-centric process mining techniques. Born as a response to the limitations of traditional process mining in analyzing event data from prevalent information systems like CRM and ERP, these techniques aim to tackle the deficiency, convergence, and divergence issues seen in traditional event logs. Despite the promise, the adoption in real-world process mining analyses remains limited. This paper embarks on a comprehensive literature review of object-centric process mining, providing insights into the current status of the discipline and its historical trajectory

VisionKG: Unleashing the Power of Visual Datasets via Knowledge Graph

The availability of vast amounts of visual data with heterogeneous features is a key factor for developing, testing, and benchmarking of new computer vision (CV) algorithms and architectures. Most visual datasets are created and curated for specific tasks or with limited image data distribution for very specific situations, and there is no unified approach to manage and access them across diverse sources, tasks, and taxonomies. This not only creates unnecessary overheads when building robust visual recognition systems, but also introduces biases into learning systems and limits the capabilities of data-centric AI. To address these problems, we propose the Vision Knowledge Graph (VisionKG), a novel resource that interlinks, organizes and manages visual datasets via knowledge graphs and Semantic Web technologies. It can serve as a unified framework facilitating simple access and querying of state-of-the-art visual datasets, regardless of their heterogeneous formats and taxonomies. One of the key differences between our approach and existing methods is that ours is knowledge-based rather than metadatabased. It enhances the enrichment of the semantics at both image and instance levels and offers various data retrieval and exploratory services via SPARQL. VisionKG currently contains 519 million RDF triples that describe approximately 40 million entities, and are accessible at https://vision.semkg.org and through APIs. With the integration of 30 datasets and four popular CV tasks, we demonstrate its usefulness across various scenarios when working with CV pipelines

Automation for incorporating assets into monitoring tools

The project consists of an analysis of the different monitoring tools and automation functions in them to find the best tool for incorporating assets. These tools have been tested in a controlled environment to determine their capabilities. It all started with a study of automation needs and a search for monitoring tools. Subsequently, I made the choice of the tool according to established criteria and an adjusted result was obtained, so it was decided to incorporate the second-best option. Then, the configuration and implementation of both were carried out in a controlled environment and a test of both was proposed and executed. Finally, after analyzing and testing the two best options, it has been seen that both Nagios Core and Zabbix have offered similar results, but it has been determined that the best option for implementation in the client network is to meet the established needs is Zabbix.El proyecto consiste en un análisis de las diferentes herramientas de monitorización y funciones de automatización de las mismas para encontrar la mejor herramienta para la incorporación de activos. Estas herramientas se han probado en un entorno controlado para determinar sus capacidades. Todo comenzó con un estudio de necesidades de automatización y una búsqueda de herramientas de monitoreo. Posteriormente, realicé la elección de la herramienta según criterios establecidos y se obtuvo un resultado ajustado, por lo que se decidió incorporar la segunda mejor opción. Luego, se realizó la configuración e implementación de ambas en un ambiente controlado y se propuso y ejecutó un testeo para ambas. Finalmente, tras analizar y testear las dos mejores opciones, se ha visto que tanto Nagios Core como Zabbix han ofrecido resultados similares, pero se ha determinado que la mejor opción de implementación en la red del cliente para cubrir las necesidades establecidas es Zabbix.El projecte consisteix en una anàlisi de les diferents eines de monitorització i funcions d'automatització per trobar la millor eina per a la incorporació d'actius. Aquestes eines s'han provat en un entorn controlat per determinar-ne les capacitats. Tot va començar amb un estudi de necessitats d'automatització i una cerca d'eines de monitorització. Posteriorment, vaig fer l'elecció de l'eina segons criteris establerts i es va obtenir un resultat ajustat, per la qual cosa es va decidir incorporar-hi la segona millor opció. Després, es va realitzar la configuració i implementació de totes dues en un ambient controlat i es va proposar i executar un testeig d'ambdues. Finalment, després d'analitzar i testejar les dues millors opcions, s'ha vist que tant Nagios Core com Zabbix han ofert resultats similars, però s'ha determinat que la millor opció d'implementació a la xarxa del client per cobrir les necessitats establertes és Zabbix

merGeo: Integration Platform for Linked Data Management Tools

Στις μέρες μας, ο Σημασιολογικός Ιστός αντιπροσωπεύει την επόμενη σημαντική εξέλιξη στη σύνδεση πληροφοριών. Επιτρέπει τη σύνδεση δεδομένων από μια πηγή σε οποιαδήποτε άλλη πηγή στον ιστό, καθώς και την κατανόηση των δεδομένων αυτών από τους υπολογιστές, ώστε να μπορούν να εκτελούν ολοένα και πιο εξελιγμένες διεργασίες για λογαριασμό μας. Έχοντας αυτό κατά νου, οι ερευνητές και οι επαγγελματίες έχουν δημιουργήσει πολλά εργαλεία που επικεντρώνονται στη διαχείριση αυτής της αφθονίας των νέων δεδομένων ιστού. Αν και αυτή η διαδικασία διαχείρισης είναι αρκετά απαιτητική και περίπλοκη, με τη χρήση των κατάλληλων εργαλείων που επικεντρώνονται στη μετατροπή, την εξερεύνηση ή την οπτικοποίηση αυτών των δεδομένων μπορεί να γίνει πιο απλή. Ωστόσο, μέχρι στιγμής κάθε εργαλείο επικεντρώνεται σε μόνο μία από τις προαναφερθείσες διαδικασίες και ως αποτέλεσμα, o συνδυασμός αυτών των εργαλείων θα μπορούσε να χρησιμοποιηθεί για να αναβαθμιστεί ο τρόπος διαχείρισης των διασυνδεδεμένων δεδομένων. Σκοπός της παρούσας εργασίας είναι να συμβάλει στη διαδικασία διαχείρισης, διερεύνησης και οπτικοποίησης των διασυνδεδεμένων δεδομένων με την ανάπτυξη του merGeo, μιας εφαρμογής που επικεντρώνεται στην παροχή μιας εύχρηστης πλατφόρμας η οποία συνδυάζει τις δυνατότητες τριών ήδη γνωστών εργαλείων διαχείρισης διασυνδεδεμένων δεδομένων: του GeoTriples, του Strabon και του Sextant. Το merGeo προσφέρει μια φιλική προς το χρήστη εφαρμογή που επιτρέπει τόσο σε ειδήμονες του αντικειμένου όσο και σε μη ειδικούς να εκμεταλλευτούν εργαλεία και τεχνολογίες του σημασιολογικού ιστού και να τους πείσει να υιοθετήσουν αυτές τις τεχνολογίες παρουσιάζοντας τα οφέλη του να χρησιμοποιείς διαφορετικές εφαρμογές που βασίζονται σε διασυνδεδεμένα δεδομένα.Nowadays, Semantic Web represents the next major evolution in connecting information. It enables data to be linked from one source to any other source on the web and to be understood by computers so that they can perform increasingly sophisticated tasks on our behalf. With this in mind, researchers and practitioners have engineered many tools that focus on manipulating this abundance of new web data. Although this managing process is quite demanding and complicated, with the use of appropriate tools that concentrate on transformation, exploration or visualization of these data, this whole handling process could become simpler. However, till now each tool focuses only on a single one of the aforementioned procedures and as a result, a combination of them could be used to take the linked data manipulation to the next level. The objective of this thesis is to contribute to linked data management, exploration and visualization process by engineering merGeo, a web application which is focused on providing a user-friendly platform that combines the features of three already known linked data management tools: GeoTriples, Strabon and Sextant. MerGeo provides an easily operated platform that allows both to domain experts and daily users to take full advantage of semantic web tools and technologies and also convinces them to embrace these tools and technologies by demonstrating the benefits of using together different applications whose center of attention is linked data