Integrating web services into data intensive web sites

Designing web sites is a complex task. Ad-hoc rapid prototyping easily leads to unsatisfactory results, e.g. poor maintainability and extensibility. However, existing web design frameworks focus exclusively on data presentation: the development of specific functionalities is still achieved through low-level programming. In this paper we address this issue by describing our work on the integration of (semantic) web services into a web design framework, OntoWeaver. The resulting architecture, OntoWeaver-S, supports rapid prototyping of service centred data-intensive web sites, which allow access to remote web services. In particular, OntoWeaver-S is integrated with a comprehensive web service platform, IRS-II, for the specification, discovery, and execution of web services. Moreover, it employs a set of comprehensive site ontologies to model and represent all aspects of service-centred data-intensive web sites, and thus is able to offer high level support for the design and development process

Personalizing Interactions with Information Systems

Personalization constitutes the mechanisms and technologies necessary to customize information access to the end-user. It can be defined as the automatic adjustment of information content, structure, and presentation tailored to the individual. In this chapter, we study personalization from the viewpoint of personalizing interaction. The survey covers mechanisms for information-finding on the web, advanced information retrieval systems, dialog-based applications, and mobile access paradigms. Specific emphasis is placed on studying how users interact with an information system and how the system can encourage and foster interaction. This helps bring out the role of the personalization system as a facilitator which reconciles the user’s mental model with the underlying information system’s organization. Three tiers of personalization systems are presented, paying careful attention to interaction considerations. These tiers show how progressive levels of sophistication in interaction can be achieved. The chapter also surveys systems support technologies and niche application domains

Revisiting requirements in web modelling languages

As a consequence of the great number of web modelling languages arisen in the last few years, some criteria to compare them have to be given. Thus, a few authors have made a recollection of the requirements that these languages should address, but, due to technological changes some new requirements have arisen and others haven’t been addressed by modelling languages, yet. This paper wants to be a stop to review which of the requirements proposed have been overcome, and which ones haven’t been yet. On the other hand, we also want to propose some new requirements in order to adapt the languages to the current technological state

Data DNA: The Next Generation of Statistical Metadata

Describes the components of a complete statistical metadata system and suggests ways to create and structure metadata for better access and understanding of data sets by diverse users

Web technologies for environmental big data

Recent evolutions in computing science and web technology provide the environmental community with continuously expanding resources for data collection and analysis that pose unprecedented challenges to the design of analysis methods, workflows, and interaction with data sets. In the light of the recent UK Research Council funded Environmental Virtual Observatory pilot project, this paper gives an overview of currently available implementations related to web-based technologies for processing large and heterogeneous datasets and discuss their relevance within the context of environmental data processing, simulation and prediction. We found that, the processing of the simple datasets used in the pilot proved to be relatively straightforward using a combination of R, RPy2, PyWPS and PostgreSQL. However, the use of NoSQL databases and more versatile frameworks such as OGC standard based implementations may provide a wider and more flexible set of features that particularly facilitate working with larger volumes and more heterogeneous data sources

MapReduce-based Solutions for Scalable SPARQL Querying

The use of RDF to expose semantic data on the Web has seen a dramatic increase over the last few years. Nowadays, RDF datasets are so big and rconnected that, in fact, classical mono-node solutions present significant scalability problems when trying to manage big semantic data. MapReduce, a standard framework for distributed processing of great quantities of data, is earning a place among the distributed solutions facing RDF scalability issues. In this article, we survey the most important works addressing RDF management and querying through diverse MapReduce approaches, with a focus on their main strategies, optimizations and results

Development of an interface for ontology‐based transformation between features of different types

Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial TechnologiesImplementation of the INSPIRE directive, the spatial data infrastructure for the Europe, has created a necessity for easy and convenient conversion between different models of geospatial data. Data model transformation across heterogeneous systems can be hampered by differences in terminology and conceptualization, particularly when multiple communities are involved. Requirement in current situation is an interface facilitating transformation of data to a desired format and immediate use of the data, which are collected from different formats and models. Ontology-aware software with shared understanding of concepts, enable users to interact with geospatial data models. Thus use of ontologies could make a friendly environment to the user in translating the data conveniently. Feature type ontologies, along with annotations are provided from an ongoing project at the Institute for Geoinformatics (IfGI, University of Münster, Germany), in order to reconcile differences in semantics. FME workbench provides a successful environment to execute set of rules for the data model transformation using a mapping file, which can be developed externally. The thesis work developed a user interface that includes operations to define rules for the translation of geospatial data, from one model to another. Annotated feature types are taken as input, and the results are encoded as FME Mapping files. The overall methodology involves three phases.(...

On-site customer analytics and reporting (OSCAR):a portable clinical data warehouse for the in-house linking of hospital and telehealth data

This document conveys the results of the On-Site Customer Analytics and Reporting (OSCAR) project. This nine-month project started on January 2014 and was conducted at Philips Research in the Chronic Disease Management group as part of the H2H Analytics Project. Philips has access to telehealth data from their Philips Motiva tele-monitoring and other services. Previous projects within Philips Re-search provided a data warehouse for Motiva data and a proof-of-concept (DACTyL) solution that demonstrated the linking of hospital and Motiva data and subsequent reporting. Severe limitations with the DACTyL solution resulted in the initiation of OSCAR. A very important one was the unwillingness of hospitals to share personal patient data outside their premises due to stringent privacy policies, while at the same time patient personal data is required in order to link the hospital data with the Motiva data. Equally important is the fact that DACTyL considered the use of only Motiva as a telehealth source and only a single input interface for the hospitals. OSCAR was initiated to propose a suitable architecture and develop a prototype solution, in contrast to the proof-of-concept DACTyL, with the twofold aim to overcome the limitations of DACTyL in order to be deployed in a real-life hospital environment and to expand the scope to an extensible solution that can be used in the future for multiple telehealth services and multiple hospital environments. In the course of the project, a software solution was designed and consequently deployed in the form of a virtual machine. The solution implements a data warehouse that links and hosts the collected hospital and telehealth data. Hospital data are collected with the use of a modular service oriented data collection component by exposing web services described in WSDL that accept configurable XML data messages. ETL processes propagate the data, link, and load it on the OS-CAR data warehouse. Automated reporting is achieved using dash-boards that provide insight into the data stored in the data warehouse. Furthermore, the linked data is available for export to Philips Re-search in de-identified format