E-Learning and microformats: a learning object harvesting model and a sample application

In order to support interoperability of learning tools and reusability of resources, this paper introduces a framework for harvesting learning objects from web-based content. Therefore, commonly-known web technologies are examined with respect to their suitability for harvesting embedded meta-data. Then, a lightweight application profile and a microformat for learning objects are proposed based on well-known learning object metadata standards. Additionally, we describe a web service which utilizes XSL transformation (GRDDL) to extract learning objects from different web pages, and provide a SQI target as a retrieval facility using a more complex query language called SPARQL. Finally, we outline the applicability of our framework on the basis of a search client employing the new SQI service for searching and retrieving learning objects

Computerization of workflows, guidelines and care pathways: a review of implementation challenges for process-oriented health information systems

There is a need to integrate the various theoretical frameworks and formalisms for modeling clinical guidelines, workflows, and pathways, in order to move beyond providing support for individual clinical decisions and toward the provision of process-oriented, patient-centered, health information systems (HIS). In this review, we analyze the challenges in developing process-oriented HIS that formally model guidelines, workflows, and care pathways. A qualitative meta-synthesis was performed on studies published in English between 1995 and 2010 that addressed the modeling process and reported the exposition of a new methodology, model, system implementation, or system architecture. Thematic analysis, principal component analysis (PCA) and data visualisation techniques were used to identify and cluster the underlying implementation ‘challenge’ themes. One hundred and eight relevant studies were selected for review. Twenty-five underlying ‘challenge’ themes were identified. These were clustered into 10 distinct groups, from which a conceptual model of the implementation process was developed. We found that the development of systems supporting individual clinical decisions is evolving toward the implementation of adaptable care pathways on the semantic web, incorporating formal, clinical, and organizational ontologies, and the use of workflow management systems. These architectures now need to be implemented and evaluated on a wider scale within clinical settings

Reconciliation of Multiple Guidelines for Decision Support: A case study on the multidisciplinary management of breast cancer within the DESIREE project

Breast cancer is the most common cancer among women. DESIREE is a European project which aims at developing web-based services for the management of primary breast cancer by multidisciplinary breast units (BUs). We describe the guideline-based decision support system (GL-DSS) of the project. Various breast cancer clinical practice guidelines (CPGs) have been selected to be concurrently applied to provide state-of-the-art patient-specific recommendations. The aim is to reconcile CPG recommendations with the objective of complementarity to enlarge the number of clinical situations covered by the GL-DSS. Input and output data exchange with the GL-DSS is performed using FHIR. We used a knowledge model of the domain as an ontology on which relies the reasoning process performed by rules that encode the selected CPGs. Semantic web tools were used, notably the Euler/EYE inference engine, to implement the GL-DSS. "Rainbow boxes" are a synthetic tabular display used to visualize the inferred recommendations

Automated Rule-Based Selection and Instantiation of Layout Templates for Widget-Based Microsites

Veebi avatud arhitektuuron loonud soodsa pinnase veebisolevate andmete kasutamiseks nii keerulisemates kui lihtsamates veebirakendustes. Andmete kogumise ja visualiseerimise lihtsustamiseks lihtsates veebirakendustes on loodud hulganisti tööriistu, mille seas on ka mashup'ide loomise tööriistad. Olemasolevate tööriistadega kõrge kasutatavusega mashup veebilehe loomine võib aga paraku olla keerukas, kuna nõuab erinevate tehnoloogiate ning programmeerimiskeelte tundmist, rääkimata kasutatavuse juhtnööridega kursisolemist. Kuigi osad mashup'ide platvormid, a'la OpenAjax Hub, lihtsustavad olemasolevate komponentide kombineerimist, on lahendamata probleemiks siiani nende rakenduste kasutatavus. Käesolev magistritöö kirjeldab reeglipõhist lahendust andmete visualiseerimise vidinate jaoks sobiva veebilehe malli automaatseks valimiseks vastavalt enimlevinud veebilehtede kasutatavuse juhtnööridele. Selleks laetakse vidinate ning struktuurimallide kirjeldused koos kasutatavuse juhtnööridest saadud reeglitega reeglimootorisse ning kasutatakse reeglimootorit ekspertsüsteemina, mis soovitab sobivamaid malle vastavalt etteantud vidinate komplektile. Lahenduse reeglipõhine ülesehitus võimaldab uute vidinate ning mallide lisandumisel või juhtnööride muutumisel operatiivselt reageerida nendele muutustele reeglibaasi täiendamise kaudu. Väljapakutud lahendus realiseeriti käesoleva töö raames Auto Microsite rakendusena, mis koosneb serveri- ning kliendipoolsest osast. Serveri poolel toimub reeglite abil vidinate komplekti visualiseerimiseks sobiva malli valimine kasutades OO jDREW RuleML reeglimootorit ning rakenduse paketeerimiseks koodi genereerimine. Kliendi poolel kasutatakse OpenAjax Hub raamistikkuvidinate turvaliseks eraldamiseks ning omavahel suhtlemapanemisel. Samuti on kliendi poolel lahendatud genereeritud veebilehe vastavusse viimine brauseri võimalustega. Katsetamaks Auto Microsite rakendust praktikas loodi seda kasutades realisatsioonid kahele lihtsale stsenaariumile. Esimesel juhul viusaliseeriti Euroopa 1997-2008 tööjõukulude (Hourly labour costs in Euros (European Union 1997-2008) ing. k.) andmeid kaardi, tabeli, kokkuvõtte ja menüü vidinatega. Teisel juhul kasutati lisaks andmete visualiseerimise vidinatele ka väliseid andmeallikaid, mis olid realiseeritud mittevisuaalsete vidinatena. Saadud andmed visualiseeriti kahe tabeli ning ühe kaardi vidinaga. Näidisveebilehtede loomise tulemusena järeldub, et rakendus sobib lihtsate veebilehtede loomiseks. Lisaks on võimalik lahendust täiendada keerukamate veebirakenduste automaatseks loomiseks läbi vastavate mallide ning reeglite lisamise.This thesis proposes a rule-based widget and layout template matchmaking solution for widget-based microsites. The solution takes as an input a set of widget descriptions and a set of layout templates with widget placeholders and returns a microsite, where the most suitable template has been instantiated with corresponding widgets. Matchmaking is based on applying a rule engine to metadata of widgets and placeholders about their content categories and dimensions,. Additional usability rules are used to further improve the results with respect to commonly accepted usability guidelines. Such a solution makes it possible to modularly enhance the usability results in the future simply by adding new usability rules and layout templates. Furthermore, the solution can be applied in mashup creation tools for layout selection. The proposed solution has been implemented and is called Auto Microsite in this thesis. The system consists of a server-side and a client-side component. The server-side component matches widgets with layout template placeholders according to the given rules by using the OO jDREW RuleML engine. The client-side is responsible for presenting the mashup appropriately for the client device. The latter is based on OpenAjax Hub 2.0 framework, which enables secure sandboxing and communication of widgets in the generated microsite. Furthermore, OpenAjax Metadata 1.0 specification is used in this thesis to package the widgets such that they could be easily reused. In order to evaluate the Auto Microsite system in practice two proof of concept (PoC) scenarios were implemented. The first scenario visualized "Hourly labour costs in Euros (European Union 1997-2008)" data using widgets for a map, a table and a summary. In the second scenario, also data was queried through a SOAP service and a Web site. In the scenario data was visualized using two table widgets and a map widget. The SOAP service and queries to the Web site were packaged as non-visual widgets to fit the framework. The POCs demonstrate that the Auto Microsite system is able to construct widget-based microsites. Furthermore, the framework is capable of constructing also more complex Web applications, with several pages and more content widgets, by adding new rules and templates

Exploiting Semantics from Widely Available Ontologies to Aid the Model Building Process

This dissertation attempts to address the changing needs of data science and analytics: making it easier to produce accurate models opening up opportunities and perspectives for novices to make sense of existing data. This work aims to incorporate semantics of data in addressing classical machine learning problems, which is one way to tame the deluge of data. The increased availability of data and the existence of easy-to-use procedures for regression and classification in commodity software allows anyone to search for correlations amongst a large set of variables with scant regard of their meaning. Consequently, people tend to use data indiscriminately, leading to the practice of data dredging. It is easy to use sophisticated tools to produce specious models, which generalize poorly and may lead to wrong conclusions. Despite much effort having been placed on advancing learning algorithms, current tools do little to shield people from using data in a semantically lax fashion. By examining the entire model building process and supplying semantic information derived from high-level knowledge in the form of an ontology, the machine can assist in exercising discretion to help the model builder avoid the pitfalls of data dredging. This work introduces a metric, called conceptual distance, to incorporate semantic information into the model building process. The conceptual distance is shown to be practically computed from large-scale existing ontologies. This metric is exploited in feature selection to enable a machine to take semantics of features into consideration when choosing them to build a model. Experiments with ontologies and real world datasets show the comparable performance of this metric in selecting a feature subset to the traditional data-driven measurements, in spite of using only labels of features, not the associated measures. Further, a new end-to-end model building process is developed by using the conceptual distance as a guideline to explore an ontological structure and retrieve relevant features automatically, making it convenient for a novice to build a semantically pertinent model. Experiments show that the proposed model building process can help a user to produce a model with performance comparable to that built by a domain expert. This work offers a tool to help the common man battle the hazard of data dredging that comes from the indiscriminate use of data. The tool results in models with improved generalization and easy to interpret, leading to better decisions or implications

Sharing and Reusing Semantic Queries for Searching the Web

This Bachelor's Thesis was preformed during a study stay at the Université de Nice, France. It is about developing a graphical user interface for drawing or generating intentional maps using goals and strategies.This Bachelor's Thesis was preformed during a study stay at the Université de Nice, France. It is about developing a graphical user interface for drawing or generating intentional maps using goals and strategies.

A Semantic Information Management Approach for Improving Bridge Maintenance based on Advanced Constraint Management

Bridge rehabilitation projects are important for transportation infrastructures. This research proposes a novel information management approach based on state-of-the-art deep learning models and ontologies. The approach can automatically extract, integrate, complete, and search for project knowledge buried in unstructured text documents. The approach on the one hand facilitates implementation of modern management approaches, i.e., advanced working packaging to delivery success bridge rehabilitation projects, on the other hand improves information management practices in the construction industry