Online Visual Image Resources and Reference Services: Understanding Preferred Resources

As students and teachers in higher education begin to use images in their courses, assignments, and research more frequently, new skills and literacies are needed to find and use images on the Web. Images can be found online in several different types of resources, including subscription image databases, freely available digital libraries and collections, user-generated collections such as Fickr or Picasa, and the general Web. Academic libraries and librarians can serve the image needs of their users by providing access to online image resources and visual literacy instruction. This paper presents a research study that explored the types of image reference questions librarians receive, the resources they use most often, and the difficulties of searching for images online

Engineering Agile Big-Data Systems

To be effective, data-intensive systems require extensive ongoing customisation to reflect changing user requirements, organisational policies, and the structure and interpretation of the data they hold. Manual customisation is expensive, time-consuming, and error-prone. In large complex systems, the value of the data can be such that exhaustive testing is necessary before any new feature can be added to the existing design. In most cases, the precise details of requirements, policies and data will change during the lifetime of the system, forcing a choice between expensive modification and continued operation with an inefficient design.Engineering Agile Big-Data Systems outlines an approach to dealing with these problems in software and data engineering, describing a methodology for aligning these processes throughout product lifecycles. It discusses tools which can be used to achieve these goals, and, in a number of case studies, shows how the tools and methodology have been used to improve a variety of academic and business systems

Engineering Agile Big-Data Systems

To be effective, data-intensive systems require extensive ongoing customisation to reflect changing user requirements, organisational policies, and the structure and interpretation of the data they hold. Manual customisation is expensive, time-consuming, and error-prone. In large complex systems, the value of the data can be such that exhaustive testing is necessary before any new feature can be added to the existing design. In most cases, the precise details of requirements, policies and data will change during the lifetime of the system, forcing a choice between expensive modification and continued operation with an inefficient design.Engineering Agile Big-Data Systems outlines an approach to dealing with these problems in software and data engineering, describing a methodology for aligning these processes throughout product lifecycles. It discusses tools which can be used to achieve these goals, and, in a number of case studies, shows how the tools and methodology have been used to improve a variety of academic and business systems

Industrial Symbiosis Recommender Systems

For a long time, humanity has lived upon the paradigm that the amounts of natural resources are unlimited and that the environment has ample regenerative capacity. However, the notion to shift towards sustainability has resulted in a worldwide adoption of policies addressing resource efficiency and preservation of natural resources.One of the key environmental and economic sustainable operations that is currently promoted and enacted in the European Union policy is Industrial Symbiosis. In industrial symbiosis, firms aim to reduce the total material and energy footprint by circulating traditional secondary production process outputs of firms to become part of an input for the production process of other firms.This thesis directs attention to the design considerations for recommender systems in the highly dynamic domain of industrial symbiosis. Recommender systems are a promising technology that may facilitate in multiple facets of the industrial symbiosis creation as they reduce the complexity of decision making. This typical strength of recommender systems has been responsible for improved sales and a higher return of investments. That provides the prospect for industrial symbiosis recommenders to increase the number of synergistic transactions that reduce the total environmental impact of the process industry in particular

Service-oriented design of environmental information systems

Service-orientation has an increasing impact upon the design process and the architecture of environmental information systems. This thesis specifies the SERVUS design methodology for geospatial applications based upon standards of the Open Geospatial Consortium. SERVUS guides the system architect to rephrase use case requirements as a network of semantically-annotated requested resources and to iteratively match them with offered resources that mirror the capabilities of existing services

Generic Architecture for Predictive Computational Modelling with Application to Financial Data Analysis: Integration of Semantic Approach and Machine Learning

The PhD thesis introduces a Generic Architecture for Predictive Computational Modelling capable of automating analytical conclusions regarding quantitative data structured as a data frame. The model involves heterogeneous data mining based on a semantic approach, graph-based methods (ontology, knowledge graphs, graph databases) and advanced machine learning methods. The main focus of my research is data pre-processing aimed at a more efficient selection of input features to the computational model. Since the model I propose is generic, it can be applied for data mining of all quantitative datasets (containing two-dimensional, size-mutable, heterogeneous tabular data); however, it is best suitable for highly interconnected data. To adapt this generic model to a specific use case, an Ontology as the formal conceptual representation for the relevant domain knowledge is needed. I have determined to use financial/market data for my use cases. In the course of practical experiments, the effectiveness of the PCM model application for the UK companies’ financial risk analysis and the FTSE100 market index forecasting was evaluated. The tests confirmed that the PCM model has more accurate outcomes than stand-alone traditional machine learning methods. By critically evaluating this architecture, I proved its validity and suggested directions for future research

Окружење за анализу и оцену квалитета великих и повезаних података

Linking and publishing data in the Linked Open Data format increases the interoperability and discoverability of resources over the Web. To accomplish this, the process comprises several design decisions, based on the Linked Data principles that, on one hand, recommend to use standards for the representation and the access to data on the Web, and on the other hand to set hyperlinks between data from different sources. Despite the efforts of the World Wide Web Consortium (W3C), being the main international standards organization for the World Wide Web, there is no one tailored formula for publishing data as Linked Data. In addition, the quality of the published Linked Open Data (LOD) is a fundamental issue, and it is yet to be thoroughly managed and considered. In this doctoral thesis, the main objective is to design and implement a novel framework for selecting, analyzing, converting, interlinking, and publishing data from diverse sources, simultaneously paying great attention to quality assessment throughout all steps and modules of the framework. The goal is to examine whether and to what extent are the Semantic Web technologies applicable for merging data from different sources and enabling end-users to obtain additional information that was not available in individual datasets, in addition to the integration into the Semantic Web community space. Additionally, the Ph.D. thesis intends to validate the applicability of the process in the specific and demanding use case, i.e. for creating and publishing an Arabic Linked Drug Dataset, based on open drug datasets from selected Arabic countries and to discuss the quality issues observed in the linked data life-cycle. To that end, in this doctoral thesis, a Semantic Data Lake was established in the pharmaceutical domain that allows further integration and developing different business services on top of the integrated data sources. Through data representation in an open machine-readable format, the approach offers an optimum solution for information and data dissemination for building domain-specific applications, and to enrich and gain value from the original dataset. This thesis showcases how the pharmaceutical domain benefits from the evolving research trends for building competitive advantages. However, as it is elaborated in this thesis, a better understanding of the specifics of the Arabic language is required to extend linked data technologies utilization in targeted Arabic organizations.Повезивање и објављивање података у формату "Повезани отворени подаци" (енг. Linked Open Data) повећава интероперабилност и могућности за претраживање ресурса преко Web-а. Процес је заснован на Linked Data принципима (W3C, 2006) који са једне стране елаборира стандарде за представљање и приступ подацима на Wебу (RDF, OWL, SPARQL), а са друге стране, принципи сугеришу коришћење хипервеза између података из различитих извора. Упркос напорима W3C конзорцијума (W3C је главна међународна организација за стандарде за Web-у), не постоји јединствена формула за имплементацију процеса објављивање података у Linked Data формату. Узимајући у обзир да је квалитет објављених повезаних отворених података одлучујући за будући развој Web-а, у овој докторској дисертацији, главни циљ је (1) дизајн и имплементација иновативног оквира за избор, анализу, конверзију, међусобно повезивање и објављивање података из различитих извора и (2) анализа примена овог приступа у фармацeутском домену. Предложена докторска дисертација детаљно истражује питање квалитета великих и повезаних екосистема података (енг. Linked Data Ecosystems), узимајући у обзир могућност поновног коришћења отворених података. Рад је мотивисан потребом да се омогући истраживачима из арапских земаља да употребом семантичких веб технологија повежу своје податке са отвореним подацима, као нпр. DBpedia-јом. Циљ је да се испита да ли отворени подаци из Арапских земаља омогућавају крајњим корисницима да добију додатне информације које нису доступне у појединачним скуповима података, поред интеграције у семантички Wеб простор. Докторска дисертација предлаже методологију за развој апликације за рад са повезаним (Linked) подацима и имплементира софтверско решење које омогућује претраживање консолидованог скупа података о лековима из изабраних арапских земаља. Консолидовани скуп података је имплементиран у облику Семантичког језера података (енг. Semantic Data Lake). Ова теза показује како фармацеутска индустрија има користи од примене иновативних технологија и истраживачких трендова из области семантичких технологија. Међутим, како је елаборирано у овој тези, потребно је боље разумевање специфичности арапског језика за имплементацију Linked Data алата и њухову примену са подацима из Арапских земаља

The ENVRI Reference Model (ENVRI RM) version 2.2, 30th October 2017

The ENVRI Reference Model (ENVRI RM, RM) exists to illustrate common characteristics of environmental science research infrastructures in order to provide a common language and understanding, promote technology and solution sharing and improve interoperability. Version 2.2 of the RM supersedes any earlier version

The ENVRI Reference Model (ENVRI RM) version 2.2, 30th October 2017

The ENVRI Reference Model (ENVRI RM, RM) exists to illustrate common characteristics of environmental science research infrastructures in order to provide a common language and understanding, promote technology and solution sharing and improve interoperability. Version 2.2 of the RM supersedes any earlier version