RDF

In order to mimic the surface of parenteral nutrition emulsion droplets, the first molecular dynamics simulation of a palmitoyloleoylphosphatidylcholine (POPC) monolayer at a water/triglyceride (trilinoleoylglycerol, LLL) interface was performed. Triglyceride influence was evaluated by comparing computed phospholipid properties to the ones in a similarly modelled hydrated POPC bilayer. As expected, polar head properties (molecular area, lipid hydration, headgroup orientation) were not affected by triglycerides. In contrast, slight differences were observed on phospholipid alkyl tail region (order parameter, diffusion, Van der Waals interactions). This first approach can reasonably be extended to a further more realistic multicomponent model of clinical nutrition emulsions.

In cases when the information being collected and processed originates by a multi-sensor system, one has to be aware of the impact of the approaches followed in designing the overall system behavior. Typically, there are many steps involved in processing sensory information, from the time a real-world event takes place until the information that describes it and captures its semantics is stored and is available for further exploitation. It this paper we analyze and discuss the options available in the design phase while we underline their respective strengths and weaknesses. The main contribution of the paper lies in the analysis of the factors that affect the behavior and performance of an information system responsible for fusing and integrating sensory information. The main components that constitute such systems are presented in depth, while every choice and the respective effects are discussed in an organized and complete manner.

Semantic data browsing is important task for open and governmental data in behalf of public control. There are many projects and solutions regarding semantic data browsing and navigation, but despite the fact, in Slovakia, the availability of such data is poor. It is a shame, because projects like National Action Plan of Open Government and the site data.gov.sk are already operating for several years. In this work we would like to point out key aspects of semantic data and detail the Slovak market of semantic data. We design and propose our solution of semantic data browsing, evaluate the implementation in our AGECRT NET tool.

The Semantic Web was proposed as an extension of the traditional Web to give Web data context and meaning by using the Resource Description Framework (RDF) data model. The recent growth in the adoption of RDF in addition to the massive growth of RDF data, have led numerous efforts to focus on the challenges of processing this data. To this extent, many approaches have focused on vertical scalability by utilising powerful hardware, or horizontal scalability utilising always-on physical computer clusters or peer to peer networks. However, these approaches utilise fixed and high specification computer clusters that require considerable upfront and ongoing investments to deal with the data growth. In recent years cloud computing has seen wide adoption due to its unique elasticity and utility billing features.

This thesis addresses some of the issues related to the processing of large RDF datasets by utilising cloud computing. Initially, the thesis reviews the background literature of related distributed RDF processing work and issues, in particular distributed rule-based reasoning and dictionary encoding, followed by a review of the cloud computing paradigm and related literature. Then, in order to fully utilise features that are specific to cloud computing such as elasticity, the thesis designs and fully implements a Cloud-based Task Execution framework (CloudEx), a generic framework for efficiently distributing and executing tasks on cloud environments. Subsequently, some of the large-scale RDF processing issues are addressed by using the CloudEx framework to develop algorithms for processing RDF using cloud computing. These algorithms perform efficient dictionary encoding and forward reasoning using cloud-based columnar databases. The algorithms are collectively implemented as an Elastic Cost Aware Reasoning Framework (ECARF), a cloud-based RDF triple store. This thesis presents original results and findings that advance the state of the art of performing distributed cloud-based RDF processing and forward reasoning.

We present a query formulation language (called MashQL) in order to easily query and fuse structured data on the web. The main novelty of MashQL is that it allows people with limited IT skills to explore and query one (or multiple) data sources without prior knowledge about the schema, structure, vocabulary, or any technical details of these sources. More importantly, to be robust and cover most cases in practice, we do not assume that a data source should have-an offline or inline-schema.

The need for smart e-learning environments is resulting in new challenges for researchers and practitioners to develop intelligent systems that can be used to automate the Higher Education (HE) activities in an intelligent way. Some common examples of such activities are “analyzing, finding, and ranking the right resource to teach a course,” “analyzing and finding the people with common research interests to start joint research projects,” and “using data analytics and machine reasoning techniques for conducting the exams with different levels of complexities.” Ontological reasoning and smart data analytics can play an important role in analyzing and automating these HE activities and processes. In this paper, we present a framework named as Higher Education Activities and Processes Automation Framework (HEAPAF). The HEAPAF framework can be used to identify, extract, process, and produce the semantically enriched data in machine understandable format from different educational resources. We also present the Higher Education Ontology (HEO) that we designed and developed to accommodate the HE data and then to perform analysis and reasoning on it. As a proof of concept, we present a case study on the topic, “analyzing, finding, and ranking the right resources to teach a course,” which can dramatically improve the learning patterns of students in the growing smart educational environment. Finally, we provide the evaluation of our framework as evidence of its competency and consistency in improving academic analytics for educational activities and processes by using machine reasoning.

This paper outlines the cleansing and extraction process of
infobox data from Wikipedia data dump into Resource Description
Framework (RDF) triplets. The numbers of the extracted
triplets, resources, and predicates are substantially
large enough for many research purposes such as semantic
web search. Our software tool will be open-sourced for researchers
to produce up-to-date RDF datasets from routine
Wikipedia data dumps.

The paper presents the use of Solid Recovered Fuels (SRF) in Chelm Cement Plant (Poland). These types of fuels are produced from non-hazardous waste and can be used for energy recovery in waste co-combustion plants.
They are much cheaper compared to primary fuels, so their use in the process of cement clinker burning brings evident economic benefits. Chelm cement plant owned by the CEMEX company is a leader in the use of alternative fuels in Poland. In the years 2005-2011 the amount of co-combustion of alternative fuels in the cement had risen from 107 to 318 thousand tons, and their share in the cement kiln heat balance reached in 2011 the level of 73.5%. This increase did not result in increase of pollutant emissions to the air.
English title: The use of solid recovered fuels (SRF) from waste - case study of fuel co-combustion installation in Chełm cement plant.

L’ontologie est caractérisée par son évolution
constante  qui  nécessite  souvent  des  mises  à  jour
appropriées.  Son  caractère  évolutif  exige  la  prise  en
compte  des  changements  liés  à  plusieurs  facteurs,  à
savoir :  le  domaine,  la  conceptualisation  et  encore  la
réutilisation. 
Dans  cet  article,  nous  présentons  une  ontologie
d’évolution  qui  décrit  le  domaine  d’évolution,  son
utilisation  pour  représenter  l’évolution  et  garder  ses
traces.  Celles-ci  peuvent  être  exploitées  dans  d’autres
fonctionnalités comme la détection des relations entre les
différentes versions de l’ontologie.

Today's ICT system necessarily involves multiple system domains complying with different management models. Integration of domain-specific management models is required to achieve, for example, agile fault localization in a huge ICT system, but this has not been efficiently achieved due to the difficulty in bridging multiple management models. To address this issue, we propose a systems management architecture reusing an existing standardized system management model for each domain and integrating them by introducing meta-data modeling. To show the feasibility of our proposal, we demonstrate that managed data of IT and network resources modeled by Common Information Model (CIM) and Shared Information Data (SID) model are bridged by meta-data modeling based on Resource Description Framework (RDF). The architectural design implies reduced effort thanks to use of well-deployed and standardized models and meta-data modeling language with its easy-to-use query language.

There are different proposals to extend RDF model theory allowing a treatment of uncertainty within the language. This works proposes a unified approach for RDF graph and statement labeling. This approach is more general than fuzzy and temporal labels and can be used to label RDF graphs with membership degrees, timestamps, or with a combination of labelings. Starting from a definition of labeled sets and labeled logic, we define labeled RDF and labeled RDF Schema. A partial ordering among labels allows qualitative treatment of uncertainty

Στον χώρο της τεχνητής νοημοσύνης και ειδικότερα του Σημασιολογικού Ιστού ο όρος οντολογία σημαίνει τον προσδιορισμό ή την περιγραφή μιας έννοιας που είναι δυνατόν να συλλάβουμε. Μια οντολογία περιγράφει έννοιες και σχέσεις που μπορεί να υφίστανται μεταξύ τους μέσα σε ένα συγκεκριμένο πλαίσιο σχέσεων. Αποτελείται από μια ταξονομία και από ένα σύνολο κανόνων εξαγωγής συμπερασμάτων. Η αξιοποίηση της οντολογίας είναι απαραίτητη για τα συστήματα ανάκτησης πληροφοριών και για τις μηχανές αναζήτησης. Στην εργασία αυτή έγινε η μοντελοποίηση ενός συστήματος διαχείρισης βιβλιοθήκης πανεπιστημίου και καταγράφηκαν τα επιμέρους βήματα. Ορίστηκε η κατάλληλη οντολογία με χρήση της πλατφόρμας του Protégé και καταγράφηκαν δέκα ερωτήματα με χρήση της γλώσσας SPARQL.

According to Soule (n.d), the surge towards a semantic web has created a need for efficient querying methods over large datasets that include statements about web resources. Husain et al (2011) state that semantic web technologies are being developed in order to present data that can be retrieved and understood by both humans and machines. The authors posit that these technologies have been standardized to address certain limitations such published web pages that aren’t suitable for reasoning. The most prominent standard is the Resource Description Framework (RDF) because of its ability to represent data in a machine readable format. According to the World Wide Web Consortium (W3C) (n.d). RDF has features that facilitate data merging regardless of the underlying schemas and also supports the evolution of the schemas over time without the need to change the consuming clients.

La  tarea  de  Desambiguación  de  Entidades  Nombradas,  junto  con  la  de  Reconocimiento  de
Entidades Nombradas, ha venido a intentar automatizar el proceso de construcción de la Web
Semántica aun cuando se cuenta con la realidad de que los  sistemas actuales que responden
a ambas,  están  lejos de prescindir  de una etapa de supervisión humana para corregir  los errores
que pudieran surgir en su aplicación. Por su complejidad, ambos problemas, siguen abiertos a
la comunidad de investigación,  sin  solución completa  para dominios generales de textos en
Lenguaje Natural.  Es por eso que este trabajo, a modo de  aproximación,  además de un sistema
de  Desambiguación  de  Entidades  Nombradas  para  español  e  inglés,  brinda  un  conjunto  de
ideas  y medidas de similaridad  que pudieran ser de mucha utilidad para tal tarea.  Estas métricas
de similaridad entre una entidad nombrada y una entidad, combinan algoritmos de Inteligencia
Artificial  como  el  de  aprendizaje  supervisado  Multinomial  Naive  Bayes,  con  la  distancia  de
Levenshtein y la similitud coseno del Modelo Vectorial de Recuperación  de Información. En el
sistema implementado,  buscando  poner  en práctica las métricas diseñadas,  se realizó el enlace
con DBpedia  a través de Wikipedia, y se probó el desempeño de varias configuraciones  de
dicho  sistema  en  un  pequeño  corpus  manual  para  el  idioma  inglés,  estas  configuraciones
respondieron a las medidas y técnicas de Procesamiento del  Lenguaje Natural utilizadas para
la desambiguación.

This paper is a survey of the research topics in the field of Semantic Web, Linked Data and Web of Data. This study looks at the contributions of this research community over its first twenty years of existence. Compiling several bibliographical sources and bibliometric indicators , we identify the main research trends and we reference some of their major publications to provide an overview of that initial period. We conclude with some perspectives for the future research challenges. RÉSUMÉ. Cet article est une étude des sujets de recherche dans le domaine du Web sémantique, des données liées et du Web des données. Cette étude se penche sur les contributions de cette communauté de recherche au cours de ses vingt premières années d'existence. En compilant plusieurs sources bibliographiques et indicateurs bibliométriques, nous identifions les princi-pales tendances de la recherche et nous référencons certaines de leurs publications majeures pour donner un aperçu de cette période initiale. Nous concluons avec une discussion sur les tendances et perspectives de recherche.

We have created the Knowledgebase of Standard Biological Parts (SBPkb) as a publically accessible Semantic Web resource for synthetic biology (sbolstandard.org). The SBPkb allows researchers to query and retrieve standard biological parts for research and use in synthetic biology. Its initial version includes all of the information about parts stored in the Registry of Standard Biological Parts (partsregistry.org). SBPkb transforms this information so that it is computable, using our semantic framework for synthetic biology parts. This framework, known as SBOL-semantic, was built as part of the Synthetic Biology Open Language (SBOL), a project of the Synthetic Biology Data Exchange Group. SBOL-semantic represents commonly used synthetic biology entities, and its purpose is to improve the distribution and exchange of descriptions of biological parts. In this paper, we describe the data, our methods for transformation to SBPkb, and finally, we demonstrate the value of our knowledgebase with a set of sample queries. We use RDF technology and SPARQL queries to retrieve candidate “promoter” parts that are known to be both negatively and positively regulated. This method provides new web based data access to perform searches for parts that are not currently possible.

Data exploration and visualization systems are of great importance in the Big Data era. Exploring and visualizing very large datasets has become a major research challenge, of which scalability is a vital requirement. In this survey, we describe the major prerequisites and challenges that should be addressed by the modern exploration and visualization systems. Considering these challenges, we present how state-of-the-art approaches from the Database and Information Visualization communities attempt to handle them. Finally , we survey the systems developed by Semantic Web community in the context of the Web of Linked Data, and discuss to which extent these satisfy the contemporary requirements.

A series of talks on Digital Humanities organised by the ERC funded research group TRIPTIC-EU within the Department for the Study of Ancient and Medieval Thought (Institute of Philosophy, Czech Academy of Sciences). Join us for a series of 45-minute talks by European scholars and experts who will discuss their projects and methods in Digital Humanities and talk about the challenges and opportunities they represent.

May 25, 2022, 2 p.m.

Roman Bleier (Historical Commission at the Bavarian Academy of Sciences and
Humanities and Centre for Information Modelling at the University of Graz).

Florian Zeilinger (Historical Commission at the Bavarian Academy of Sciences
and Humanities - currently, and the University of Graz, May 20 – June 30)

Digital Scholarly Editions and historians: editing the records of the Imperial Diet of 1576 (ONLINE).

Abstract
A team of researchers at the Historical Commission at the Bavarian Academy of
Sciences and Humanities and the University of Graz are developing a digital
scholarly edition of the records documenting the Imperial Diet (Reichstag) of
Regensburg in 1576. At the Imperial Diet, between June and October 1576,
Emperor Maximilian II and more than 200 representatives of the imperial estates
(Reichsstände) of the Holy Roman Empire discussed and decided about the
political fate of Central Europe. The numerous meetings and deliberations at the
Imperial Diet are of central interest to the ongoing project and new digital
edition.

From a digital scholarly editing point of view, the project explores a particular
way of editing historical documents (seen as a text characterised by its content)
and representing the formal information, for instance about the above-mentioned
deliberations, as structured data in RDF. This kind of editing is a further
development of editing practices used by historians–in a recent article Georg
Vogeler suggested the name “assertive edition”.

Our presentation will explore this editing approach in the context of the Imperial Diet's records edition. We will discuss how we have edited the historical records and
semantically enriched them with TEI markup, how we extract “facts” in the form of
RDF triples, and how we combine the edited texts with a database. This approach
allows us to access the Imperial Diet of 1576 as a bundle of communication
events and thereby opens it up for historiographical research interested in
content, communication and procedures.

To join this lecture please register at https://bit.ly/register-bleier.

More and more (semi) structured information is becoming available on the web in the form of documents embedding metadata (e.g., RDF, RDFa, Microformats and others). There are already hundreds of millions of such documents accessible and their number is growing rapidly. This calls for large scale systems providing effective means of searching and retrieving this semi-structured information with the ultimate goal of making it exploitable by humans and machines alike.This article examines the shift from the traditional web document model to a web data object (entity) model and studies the challenges faced in implementing a scalable and high performance system for searching semi-structured data objects over a large heterogeneous and decentralised infrastructure. Towards this goal, we define an entity retrieval model, develop novel methodologies for supporting this model and show how to achieve a high-performance entity retrieval system. We introduce an indexing methodology for semi-structured data which offers a good compromise between query expressiveness, query processing and index maintenance compared to other approaches. We address high-performance by optimisation of the index data structure using appropriate compression techniques. Finally, we demonstrate that the resulting system can index billions of data objects and provides keyword-based as well as more advanced search interfaces for retrieving relevant data objects in sub-second time.This work has been part of the Sindice search engine project at the Digital Enterprise Research Institute (DERI), NUI Galway. The Sindice system currently maintains more than 200 million pages downloaded from the web and is being used actively by many researchers within and outside of DERI.

Information residing in relational databases and delimited file systems are inadequate for reuse and sharing over the web. These file systems do not adhere to commonly set principles for maintaining data harmony. Due to these reasons, the resources have been suffering from lack of uniformity, heterogeneity as well as redundancy throughout the web. Ontologies have been widely used for solving such type of problems, as they help in extracting knowledge out of any information system. In this article, we focus on extracting concepts and their relations from a set of CSV files. These files are served as individual concepts and grouped into a particular domain, called the domain ontology. Furthermore, this domain ontology is used for capturing CSV data and represented in RDF format retaining links among files or concepts. Datatype and object properties are automatically detected from header fields. This reduces the task of user involvement in generating mapping files. The detail analysis has been performed on Baseball tabular data and the result shows a rich set of semantic information.

Solid waste management has always been about collection and disposal of garbage. We have currently moved on to a more efficient collection and disposal by using Engineered Sanitary Landfills in the Philippines. However, with the increase in population and the consequent increase in solid waste generation, we are now running out of spaces to establish solid waste disposal facilities. A global trend in solid waste management is towards resource recovery rather than disposal of waste. Resource recovery is no longer limited to recyclable materials such as tins, glass, paper, plastic and rubber. Resource recovery now involves the recovery of all solid waste materials, including residual waste. This is the value of RDF or refuse-derived fuel. RDF uses highly combustible residual waste, such as plastics and some biodegradable materials as fuel for cement kilns.It is currently being used by giant cement manufacturers Holcim and La Farge, consisting about 10% of the fuel they use in their cement kilns, which still uses an estimated 90% coal. The use of RDF, however, as a waste-to-energy technology must still be closely monitored under RA 9003 or the Ecological Solid Waste Management Act 2000 as well as the Clean Air Act. It remains to be an incinerating technology that requires equipment for flue gascleaning system to prevent air pollution. If RDF can be maintained as a clean technology and recovery of RDF-qualified waste materials can be increased, resource recovery from solid waste will become more efficient, then someday, we will finally be able to achieve zero waste.

في الشبكة العنكبوتية وضعت معظم المواقع على اساس معاني الكلمات، ظهور الويب الدلالي يتغلب على صعوبات محركات البحث ويوفر نتائج أفضل نظراً لكون المعلومات منظمة، الشبكة الدلالية  المصنفة تزيد من أداء محركات البحث وتوفر نتائج معززة لاستعلام المستخدم مقارنةً مع الويب الدلالي الغير مصنف. في هذه الورقة سندرس نوعين من التصنيفات.

The paper develops a conceptual model of scholarly editing in the digital environment which allows clear distinction and references between visual, palaeographical, linguistic and 'historical' ('content') information. It suggests that the 'content' layer can best be represented using W3C Semantic Web standards (RDF, SPARQL). It explains this on the example of historical acconting documents.

Semantic  web,  since  its  inception  is  approved  for  providing contexts  to  the  search  strings  applicable  to  a  given domain. Various frameworks or models based on semantic technologies utilizing semantic enhanced annotations and reasoning are recognized to  deliver  more  relevant  outputs.  Thus, Semantic Web based recommenders  are  required  for  enriched recommendations  in this age  of information overload on the web. Contextual  data  may be  used not only  to represent domain objects and the user preferences in a more precise and refined way but also to apply better matching procedures with the aid of semantic  similarity  measures.  Also,  the  presently  used  content
-based  recommendation  techniques  and  collaborative  filtering ones  may  certainly  benefit  from  the  introduction  of  explicit domain  knowledge  to  produce  recommendations  using  logical inferences  applicable  in  that  domain.  Both recommender systems  and  semantic  web complement  each  other  and  may aid  in their progress mutually.
In the last decade, there has been some research work done utilizing the semantic web technologies for aiding recommender systems, which play a significant role towards the goal of semantic web. In this paper, first,
recommender systems(RS)have been discussed along with key research concerns, benefits and issues being explored and revisited. Second,
scope  and  literature  survey  has  been  presented in
the track of  how  semantic  web  technologies  have  contributed  to
enhancements of RS. Third, the role of various semantic web technologies has been explored and discussed for enhancement of
present recommender systems. Fourth, useful inferences of the work
done are tabulated along with the key discussions.