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

Migrating microservices to graph database

Microservice architecture is a popular approach to structuring web backend services. Another emerging trend, after a period of hibernation, is utilizing modern graph database management systems for managing complex, richly connected data. The two approaches have rarely been used in tandem, as microservices emphasize modularization and decoupling of services, while graph data models favor data integration. In this study, literature on microservices and graph databases is reviewed and a synthesis between the two paradigms is presented. Based on the theoretical discussion, a software architecture combining the two elements is formulated and implemented using microservices serving content metadata at Yleisradio, the Finnish national broadcasting company. The architecture design follows the Design Science Research Process model. Finally, the renewed system is evaluated using quantitative and qualitative metrics. The performance of the system is measured using automated API queries and load tests. The new system was compared to an earlier version based on a PostgreSQL database. The tests gave slight indication that the renewed system performed better for complex queries, where a large number of relations were traversed, but worse in terms of throughput under heavy load. Based on the these findings, a number of performance-enhancing optimizations to the system are introduced. Observations and perpectives are also gathered in a project retrospective session. It is concluded that the resulting architecture holds promise for managing complex data rich in relations in a safe manner. In it, the different domains of the knowledge graph are decoupled into distinct named graphs managed by different microservices

Semantic Data Management in Data Lakes

In recent years, data lakes emerged as away to manage large amounts of heterogeneous data for modern data analytics. One way to prevent data lakes from turning into inoperable data swamps is semantic data management. Some approaches propose the linkage of metadata to knowledge graphs based on the Linked Data principles to provide more meaning and semantics to the data in the lake. Such a semantic layer may be utilized not only for data management but also to tackle the problem of data integration from heterogeneous sources, in order to make data access more expressive and interoperable. In this survey, we review recent approaches with a specific focus on the application within data lake systems and scalability to Big Data. We classify the approaches into (i) basic semantic data management, (ii) semantic modeling approaches for enriching metadata in data lakes, and (iii) methods for ontologybased data access. In each category, we cover the main techniques and their background, and compare latest research. Finally, we point out challenges for future work in this research area, which needs a closer integration of Big Data and Semantic Web technologies

Visualising Changes in a System of Linked Lightweight Ontologies

Ontologioiden avulla pyritään mallintamaan tiettyä alaa määrittelemällä kyseiseen alaan kuuluvia käsitteitä ja näiden välisiä yhteyksiä. Näitä käsitteitä voidaan käyttää alaa käsittelevän aineiston annotointiin. Lisäksi ontologioita voidaan linkittää toisiin ontologioihin, jolloin päästään hyödyntämään muualla tehtyä työtä. Ontologioita joudutaan luonnollisesti päivittämään, kun uusia käsitteitä tai muuta muutoksia tulee alalle. Tällöin myös kyseiseen ontologiaan linkittyneitä ontologioita voi joutua muuttamaan, jotta linkittyneet ontologiat pysyvät keskenään konsistentteina. Tässä työssä luotiin MUTU-työkalu auttamaan ontologiakehittäjää edellä kuvatussa muutostilanteessa. Työkalu välittää muutokset ontologiakehittäjälle, lajittelee muutokset muutoksen tyypin mukaan sekä esittää nämä muutokset linkitetyn ontologian kehittäjälle. Tieteellisenä tuloksena työkalu sisältää algoritmin, joka pyrkii ennustamaan, milloin toisessa ontologiassa tapahtunut muutos aiheuttaa muutoksen kehittäjän ontologiaan. Työkalun tavoitteena on helpottaa linkitetyn ontologian päivitystä varsinkin suurilla muutosmäärillä. Työkalun luomia muutoslistoja sekä muutosten lajittelun toimivuutta testattiin ontologiakehittäjillä todellisessa käyttötilanteessa. Työn tuloksena oli, että lajitteluheuristiikka toimi aineistossa hyvin käsitteiden ominaisuuksien muutoksissa ja auttaisi täten priorisoimaan läpikäytäviä muutoksia ontologiaa päivitettäessä.Ontologies aim to model a field by listing concepts and their relationships in the field. These concepts are then used in annotating data regarding the field. In addition, ontologies can be linked to other ontologies, thus utilising the work and knowledge of other ontology developers. Naturally, ontologies need to evolve due to the changes and advances of the field. In this case, also other ontologies linked to the ontology might require updates to ensure the consistency of the ontologies. In this work, I created a tool for assisting the ontology developer in the above described update. The tool was named mutu and it conveys the changes to the ontology developer, classifies the changes by their type and visualises the changes for the developer. As a scientific contribution, this work introduces an algorithm for classifying changes by their priority. The algorithm aims to predict which changes in the related ontology will cause changes in the ontology of the developer. The aim of the tool is to aid in updates with a large amount of changes. The created change lists and the performance of the change classification were tested in a real-life update task. The outcome of the evaluation was that the priority classification performance was good with the changes of property values, thus being an aid in prioritising changes in updating ontologies

An Ontology based Text-to-Picture Multimedia m-Learning System

Multimedia Text-to-Picture is the process of building mental representation from words associated with images. From the research aspect, multimedia instructional message items are illustrations of material using words and pictures that are designed to promote user realization. Illustrations can be presented in a static form such as images, symbols, icons, figures, tables, charts, and maps; or in a dynamic form such as animation, or video clips. Due to the intuitiveness and vividness of visual illustration, many text to picture systems have been proposed in the literature like, Word2Image, Chat with Illustrations, and many others as discussed in the literature review chapter of this thesis. However, we found that some common limitations exist in these systems, especially for the presented images. In fact, the retrieved materials are not fully suitable for educational purposes. Many of them are not context-based and didn’t take into consideration the need of learners (i.e., general purpose images). Manually finding the required pedagogic images to illustrate educational content for learners is inefficient and requires huge efforts, which is a very challenging task. In addition, the available learning systems that mine text based on keywords or sentences selection provide incomplete pedagogic illustrations. This is because words and their semantically related terms are not considered during the process of finding illustrations. In this dissertation, we propose new approaches based on the semantic conceptual graph and semantically distributed weights to mine optimal illustrations that match Arabic text in the children’s story domain. We combine these approaches with best keywords and sentences selection algorithms, in order to improve the retrieval of images matching the Arabic text. Our findings show significant improvements in modelling Arabic vocabulary with the most meaningful images and best coverage of the domain in discourse. We also develop a mobile Text-to-Picture System that has two novel features, which are (1) a conceptual graph visualization (CGV) and (2) a visual illustrative assessment. The CGV shows the relationship between terms associated with a picture. It enables the learners to discover the semantic links between Arabic terms and improve their understanding of Arabic vocabulary. The assessment component allows the instructor to automatically follow up the performance of learners. Our experiments demonstrate the efficiency of our multimedia text-to-picture system in enhancing the learners’ knowledge and boost their comprehension of Arabic vocabulary

Linked open data e ontologie per la descrizione del patrimonio culturale: criteri per la progettazione di un registro ragionato

La tesi affronta il tema del semantic web e della pubblicazione delle informazioni relative al patrimonio culturale in modalità linked open data. In particolare, oggetto dell’attività di ricerca sono i registri di ontologie, vale a dire quegli strumenti che descrivono formalmente i modelli ontologici disponibili sul web e ne agevolano il reperimento e la valutazione, incentivandone il riuso e facilitando i processi di allineamento semantico e di interoperabilità. I registri di ontologie rispondono in modo efficace all’assenza di strumenti di riferimento e di orientamento nei processi di modellazione concettuale delle risorse informative e sono stati sperimentati con successo in diversi domini, ma sono ancora inediti in ambito culturale. L’esame puntuale delle iniziative condotte nell’ultimo decennio nell’ambito dei beni culturali ha evidenziato con chiarezza la mancanza di un assetto epistemologico consolidato nella modellazione concettuale delle risorse informative, a fronte delle numerose ontologie realizzate in funzione dei molteplici progetti di pubblicazione di linked open data. Di conseguenza, risulta tutt’altro che agevole conoscere esaustivamente tutte le ontologie disponibili in relazione al proprio abito di interesse ed ottenere in maniera agevole e sistematica una valutazione attendibile circa la loro capacità rappresentativa e il loro grado di interoperabilità semantica. L’analisi dei principali registri di ontologie finora realizzati al di fuori del dominio dei beni culturali ha consentito di individuare e definire i requisiti di un registro di ontologie per i beni culturali (denominato CLOVER, Culture – Linked Open Vocabularies – Extensible Registry), e di elaborarne la relativa ontologia. L’ontologia ADMS-AP_IT (Asset Description Metadata Schema – Application Profile – Italy) è stata redatta a seguito di un’analisi sistematica e di una valutazione critica di preesistenti ontologie concepite per scopi similari. Essa è stata sottoposta ad AgID, che l’ha inclusa nella rete di ontologie e vocabolari controllati della pubblica amministrazione detta OntoPiA. Tale ontologia rappresenta un punto di arrivo del progetto di ricerca, ma anche una base di partenza per approfondire l'indagine su tali temi: in questo senso, la sua inclusione nella rete OntoPiA di ontologie e vocabolari controllati della pubblica amministrazione si configura come un'opportunità rilevante per sperimentarne l'applicabilità e migliorarne la qualità

Designing Data Spaces

This open access book provides a comprehensive view on data ecosystems and platform economics from methodical and technological foundations up to reports from practical implementations and applications in various industries. To this end, the book is structured in four parts: Part I “Foundations and Contexts” provides a general overview about building, running, and governing data spaces and an introduction to the IDS and GAIA-X projects. Part II “Data Space Technologies” subsequently details various implementation aspects of IDS and GAIA-X, including eg data usage control, the usage of blockchain technologies, or semantic data integration and interoperability. Next, Part III describes various “Use Cases and Data Ecosystems” from various application areas such as agriculture, healthcare, industry, energy, and mobility. Part IV eventually offers an overview of several “Solutions and Applications”, eg including products and experiences from companies like Google, SAP, Huawei, T-Systems, Innopay and many more. Overall, the book provides professionals in industry with an encompassing overview of the technological and economic aspects of data spaces, based on the International Data Spaces and Gaia-X initiatives. It presents implementations and business cases and gives an outlook to future developments. In doing so, it aims at proliferating the vision of a social data market economy based on data spaces which embrace trust and data sovereignty

Feral Ecologies: A Foray into the Worlds of Animals and Media

This dissertation wonders what non-human animals can illuminate about media in the visible contact zones where they meet. It treats these zones as rich field sites from which to excavate neglected material-discursive-semiotic relationships between animals and media. What these encounters demonstrate is that animals are historically and theoretically implicated in the imagination and materialization of media and their attendant processes of communication. Chapter 1 addresses how animals have been excluded from the cultural production of knowledge as a result of an anthropocentric perspective that renders them invisible or reduces them to ciphers for human meanings. It combines ethology and cinematic realism to craft a reparative, non-anthropocentric way of looking that is able to accommodate the plenitude of animals and their traces, and grant them the ontological heft required to exert productive traction in the visual field. Chapter 2 identifies an octopuss encounter with a digital camera and its chance cinematic inscription as part of a larger phenomenon of accidental animal videos. Because non-humans are the catalysts for their production, these videos offer welcome realist counterpoints to traditional wildlife imagery, and affirm cinemas ability to intercede non-anthropocentrically between humans and the world. Realism is essential to cinematic communication, and that realism is ultimately an achievement of non-human intervention. Chapter 3 investigates how an Internet hoax about a non-human ape playing with an iPad in a zoo led to the development of Apps for Apes, a real life enrichment project that pairs captive orangutans with iPads. It contextualizes and criticizes this projects discursive underpinnings but argues that the contingencies that transpire at the touchscreen interface shift our understanding of communication away from sharing minds and toward respecting immanence and accommodating difference. Finally, Chapter 4 examines a publicity stunt wherein a digital data-carrying homing pigeon races against the Internet to meet a computer. Rather than a competition, this is a continuation of a longstanding collaboration between the carrier pigeon and the infrastructure of modern communications. The carrier pigeon is not external but rather endemic to our understanding of communication as a material process that requires movement and coordination to make connections

Digitalization as a Paradigm Changer in Machine-Building Industry

Digitalization is a contemporary societal topic among businessmen, scholars, politicians, and citizens. The way Uber has changed the taxi business and subsequently is providing new models for the entire transportation industry or even changing urban planning principles is a practical example of the impact of digitalization. This example illustrates that digitalization offers major returns for some and ultimate losses for others, which is similar to Schumpeter’s “Creative Destruction” that he coined in 1942. Digitalization does not refer to a product or service; it is multiple technology-based products, services, and concepts as a systemic whole. Many of the impacts of digitalization are difficult to observe beforehand, as the impact rendered is systemic rather than a straightforward causal relation. Traditional strategic management theories and frameworks are used to analyze company performance and to explain which strategies individual firms or group of firms should implement to succeed. Many of the tools for top management aid in understanding changes in business environments and offer guidance for making the correct strategic choices, but in many cases, they fail to aid in the detection of systemic phenomena. At the same time, making these strategic choices is difficult, as explained by behavioral economics and management cognition, as the choices involve changing the status quo.This dissertation examines the digitalization impact on the machine-building industry that serves global container handling customers - ports and terminals. It is a traditional capital intensive business-to-business industry that has a relatively small number of global players. The investigation adopted a value chain view in which machine builders are actors, actors apply digital technologies provided by enablers. The end customers, ports and terminals are referred as users. The objective of the research was to increase understanding of digitalization’s potential for disruption or paradigm change as well as to identify the most important concepts that drive and inhibit this change. As the change brought about by digitalization is underway, it is necessary to understand whether the views regarding its impact differ between enablers, actors, and users. Mixed methods were applied that partly overlapped for triangulation purposes. The primary methodology included two rounds of Delphi interviews that were complemented by a survey and three case descriptions.Big Data/Artificial Intelligence emerged as the most prominent digital technology that can enable disruption in machine-building. Empirical results have shown that Big Data/Artificial Intelligence challenges the ways knowledge is created; it is more effective when machines and their components are connected to data networks, and the technology is both rapidly advancing and becoming more affordable. The cost, speed, availability, and features of Big Data/Artificial Intelligence development are driven by multiple industries where machine builders can have a relatively small impact.Empirical results have also shown that discipline and industry-based platforms are the most powerful economic drivers. The current management of the incumbents has little experience with these new elements, which have a major influence on industry dynamics. The platforms are especially powerful for change, as they enable a global network economy in which entrepreneurial knowledge workers can contribute to value creation in collaboration with startups and multinational corporations. Platform development cannot be stopped or delayed by incumbents in machine-building. They can ignore the development, adapt to it, or pursue a platform strategy of their own if the opportunities match the companies’ capabilities.Examples of the sub-drivers pushing the digital concepts forward are classical and rational productivity, lead times, features, quality, and cost. In addition, some of the inhibitive sub-drivers are relatively easy to identify, such as 3D printing speed or users providing access to their data. Concerns regarding data security delay investment, and changing legacy processes and systems requires time; however, empirical results have indicated that the strongest inertia is related directly to people and decision making. Three of the strongest people-related inhibitive sub-drivers are lack of systemic understanding, management beliefs, and lack of capabilities. The practical contribution for management is twofold. First, it must be believed that digitalization will somehow disrupt the current business, and second that the transformation is too complex to be only planned, but instead requires also experimental learning. A successful combination that has been suggested by books and articles as well as the results and comments from the Delphi interviews is developing an entrepreneurial mindset, conducting multiple small experiments, and applying the knowledge of external networks. This enables strategy formation through learning, which simultaneously develops the capabilities that are needed in data and user-centric business environments.Digitalisaatio on ajankohtainen aihe liikemiesten, tutkijoiden, poliitikkojen ja yksittäisten ihmisten keskuudessa. Yksi käytännön esimerkki digitalisaation vaikutuksista on Uber, jonka toimintatapa muuttaa taksiliiketoimintaa luoden samalla malleja koko kuljetustoimialalle ja vaikuttaen jopa kaupunkisuunnitteluun. Esimerkki valaisee myös sitä, miten digitalisaatio tarjoaa merkittäviä voittoja yksille ja kohtalokkaita tappioita toisille, kuten Schumpeter kuvasi ”luovan tuhon” ajatuksessaan jo vuonna 1942. Digitalisaatio ei ole yksittäinen tuote tai palvelu, vaan se on tuotteita, palveluita ja konsepteja, joita useat digitaaliset teknologiat systeemisesti mahdollistavat. Systeemisyys yksinkertaisten syy–seuraus-suhteiden sijaan tekee vaikutusten ymmärtämisen ja ennustamisen vaikeaksi. Perinteisiä strategisen johtamisen teorioita ja viitekehyksiä käytetään yritysten suorituskyvyn analysointiin ja sen ymmärtämiseksi, millä toimenpiteillä yritykset menestyisivät. Lisäksi monet ylimmät johdon työkalut helpottavat näkemään liiketoimintaympäristön muutoksia ja tarjoavat tukea oikeiden strategisten valintojen tekemiseen, mutta niissä on heikkouksia systeemisten ilmiöiden havaitsemiseksi. Behavioristinen taloustiede ja johtamisen kognitiotieteet auttavat ymmärtämään, miksi oikeat strategiset valinnat, jotka muuttavat vallitsevia uskomuksia, ovat vaikeita yksilötasolla.Tämä väitöstutkimus tutki digitalisaation vaikutusta koneenrakennustoimialaan, joka palvelee maailmanlaajuista kontinkäsittelyä – satamia ja terminaaleja. Toimiala on perinteinen, siinä on suhteellisen vähän globaaleja toimijoita ja se sitoo paljon pääomaa. Tutkimus lähestyi ongelmaa arvoketjun näkökulmasta siten, että koneenrakentajat ovat toimijoita, jotka soveltavat digitaalisia teknologioita, joita puolestaan mahdollistajat toimittavat. Arvo syntyy lopullisesti käyttäjille, joita ovat satamat ja terminaalit. Tutkimuksen tavoitteena oli lisätä ymmärrystä digitalisaation mahdollisesti aiheuttamasta murroksesta tai muutoksesta nykyiseen arvonluontimalliin sekä siitä, mitkä tekijät hidastavat tätä kehitystä. Koska mahdollinen muutos on meneillään, käsitysten erovaisuuksien ymmärtäminen arvoketjussa mahdollistajien, toimijoiden ja käyttäjien kesken on tärkeää. Tutkimuksen päämenetelmä oli kahden haastattelukierroksen Delfoi-tekniikka sekä tulosten validiteetin parantamiseksi käytetyt kyselytutkimus sekä kolme case-kuvausta.Tietomassojen suurtehokäsittely (Big Data) yhdessä tekoälyn (Artificial Intelligence) kanssa nousi tärkeimmäksi mahdollisen murroksen aikaansaavaksi digitaaliseksi teknologiaksi. Empiiriset tulokset osoittivat, että kyseiset teknologiat vaikuttavat uuden tietämyksen syntyyn ja että ilmiö kiihtyy, koska koneet ja niiden komponentit liittyvät kiihtyvässä tahdissa tietoverkkoihin. Kyseiset teknologiat kehittyvät edelleen samalla kun niiden käytön kustannukset laskevat. Nämä teknologiat palvelevat useita toimialoja, mutta koneenrakentajilla itsellään on vähäinen vaikutus teknologian kustannuksiin, nopeuteen, saatavuuteen, ominaisuuksiin tai niiden kehittymiseen.Empiiriset tulokset osoittivat myös, että tieteenhaara tai toimialapohjaiset alustat ovat voimakkaimmat potentiaalista murrosta aiheuttavat taloudelliset konseptit tämän tutkimuksen rajauksella. Alustat ovat uusia elementtejä, joilla on merkittävä vaikutus toimialan dynamiikkaan, mutta perinteisten yritysten johdolla on harvoin omaan opiskeluun tai kokemukseen perustuvaa osaamista niistä. Alustat saavat voimansa verkostovaikutuksista, joissa tietotyöläiset, startupit ja monikansalliset yritykset luovat yhdessä arvoa. Koneenrakentajat eivät pysty estämään alustojen syntymistä tai merkittävästi hidastamaan niiden kehitystä. Ne voivat ohittaa ilmiön, sopeutua siihen tai mahdollisuuksiensa ja kyvykkyyksiensä puitteissa luoda oman alustastrategiansa.Merkittävä osa ajureista, jotka kiihdyttävät digitaalisia konsepteja, ovat perinteisiä ja rationaalisia, kuten tuottavuus, läpimenoajat, ominaisuudet, laatu tai kustannukset. Osa kehitystä hidastavista ajureista on helposti tunnistettavissa, kuten 3D-tulostimen nopeus tai kuinka moni käyttäjä antaa pääsyn dataansa. Huoli tietoturvasta hidastaa investointeja, ja olemassa olevien prosessien ja järjestelmien vaihtaminen on aikaa vievää. Empiiriset tulokset osoittivat kuitenkin, että voimakkaimmat hidasteet liittyivät suoraan ihmisiin ja päätöksentekoon. Kolme merkittävintä ihmisiin liittyvää hidastetta olivat systeemisten ilmiöiden huono ymmärtäminen, johdon uskomukset ja kyvykkyyksien puute. Tulosten merkitys käytännön strategiselle johtamiselle kiteytyy kahteen asiaan. Ensinnäkin johdon pitää ymmärtää ja uskoa, että digitaalisuus murtaa joiltakin osin nykyisen liiketoiminnan, ja toiseksi kehitys on niin monisyistä, ettei menestystä voi kovinkaan tarkasti suunnitella etukäteen. Osa tutkimuksessa käytetystä kirjallisuudesta ja Delfoihaastatteluista saadut tulokset painottavat tällaisessa tilanteessa yrittäjyysmäistä ajattelutapaa ja paljon pieniä kokeiluja, joissa hyödynnetään ulkoisten verkostojen tietämystä. Toimintatapa mahdollistaa sen, että strategia voidaan luoda oppimalla, mikä samanaikaisesti kehittää kyvykkyyksiä, joita tarvitaan tieto- ja käyttäjäkeskeisissä liiketoimintaympäristöissä