A (digital) finger on the pulse

Complex Event Processing (CEP) is a computer-based technique used to track, analyse and process data in real-time (as an event happens). It establishes correlations between streams of information and matches to defined behaviour

On Reasoning with RDF Statements about Statements using Singleton Property Triples

The Singleton Property (SP) approach has been proposed for representing and querying metadata about RDF triples such as provenance, time, location, and evidence. In this approach, one singleton property is created to uniquely represent a relationship in a particular context, and in general, generates a large property hierarchy in the schema. It has become the subject of important questions from Semantic Web practitioners. Can an existing reasoner recognize the singleton property triples? And how? If the singleton property triples describe a data triple, then how can a reasoner infer this data triple from the singleton property triples? Or would the large property hierarchy affect the reasoners in some way? We address these questions in this paper and present our study about the reasoning aspects of the singleton properties. We propose a simple mechanism to enable existing reasoners to recognize the singleton property triples, as well as to infer the data triples described by the singleton property triples. We evaluate the effect of the singleton property triples in the reasoning processes by comparing the performance on RDF datasets with and without singleton properties. Our evaluation uses as benchmark the LUBM datasets and the LUBM-SP datasets derived from LUBM with temporal information added through singleton properties

HealthTrust: Assessing the Trustworthiness of Healthcare Information on the Internet

As well recognized, healthcare information is growing exponentially and is made more available to public. Frequent users such as medical professionals and patients are highly dependent on the web sources to get the appropriate information promptly. However, the trustworthiness of the information on the web is always questionable due to the fast and augmentative properties of the Internet. Most search engines provide relevant pages to given keywords, but the results might contain some unreliable or biased information. Consequently, a significant challenge associated with the information explosion is to ensure effective use of information. One way to improve the search results is by accurately identifying more trustworthy data. Surprisingly, although trustworthiness of sources is essential for a great number of daily users, not much work has been done for healthcare information sources by far. In this dissertation, I am proposing a new system named HealthTrust, which automatically assesses the trustworthiness of healthcare information over the Internet. In the first phase, an unsupervised clustering using graph topology, on our collection of data is employed. The goal is to identify a relatively larger and reliable set of trusted websites as a seed set without much human efforts. After that, a new ranking algorithm for structure-based assessment is adopted. The basic hypothesis is that trustworthy pages are more likely to link to trustworthy pages. In this way, the original set of positive and negative seeds will propagate over the Web graph. With the credibility-based discriminators, the global scoring is biased towards trusted websites and away from untrusted websites. Next, in the second phase, the content consistency between general healthcare-related webpages and trusted sites is evaluated using information retrieval techniques to evaluate the content-semantics of the webpage with respect to the medical topics. In addition, graph modeling is employed to generate contents-based ranking for each page based on the sentences in the seed pages. Finally, in order to integrate the two components, an iterative approach that integrates the credibility assessments from structure-based and content-based methods to give a final verdict - a HealthTrust score for each webpage is exploited. I demonstrated the first attempt to integrate structure-based and content-based approaches to automatically evaluate the credibility of online healthcare information through HealthTrust and make fundamental contributions to both information retrieval and healthcare informatics communities

Stillbirth : a loss for the whole family

Background: Stillbirth loss is a profound experience affecting around 450 families every year in Sweden. Method: Two questionnaires, one postal with three measurements over a two-year period with 55 parents (I), and a web questionnaire answered by 411 parents (III), five focus groups with a total of 25 parents (II), and individual face-to-face interviews with 13 bereaved adolescent siblings of a stillborn baby (IV) constitute the data collection. The qualitative data were analysed with a content analysis, descriptive statistics were used for the quantitative data. The overall aim of the thesis was to study the loss of a stillborn baby from the perspective of parents and siblings. Results: The parents strived to create an environment in which siblings are confidently allowed and invited to participate in processes surrounding the stillbirth. They promoted an understanding of the new and unexpected family situation. Some parents expressed difficulty in focusing on the needs of siblings during the acute grief after the loss. Most of the siblings met their stillborn sister or brother. The meeting was described as natural, enriching and self-evident and as an important component to create understanding; it attributed identity and personality to the stillborn baby. When the siblings created memories the baby was acknowledged and took on a tangible form. Furthermore, parents and siblings expressed feelings of broken expectations of becoming a larger family. Additionally, being a sister or brother of a stillborn baby brought up thoughts about the sibling relationship, and whether they could still identify themselves as big sisters or brothers. Many parents reported the loss had strengthened their relationship. Some parents and adolescent siblings expressed that they were grieving alone as well as together with other members of the family. They developed an inner strength and a trust in each other. For others, expectations of their own and other family members´ way of grieving could pose a threat to their close relationship; a lack of understanding for each other´s way to express grief or their needs could create an emotional distance. Some adolescents expressed feelings of being part of a common grief in the family, but simultaneously being outside. The loss of their baby sibling implied a temporary loss of their parents´ parenthood.clusions: This thesis gives new information on the thoughts and feelings in a family after they have experienced a stillbirth. Clinically the information can be used to help health-care professionals communicate with parents and siblings after this event. For parents seeking advice, it may help to know that the parents in this study, who actively involved the stillborn baby’s siblings in the meeting and farewell afterwards, by and large reported encouraging experiences only

Research Objects: Towards Exchange and Reuse of Digital Knowledge

What will researchers be publishing in the future? Whilst there is little question that the Web will be the publication platform, as scholars move away from paper towards digital content, there is a need for mechanisms that support the production of self-contained units of knowledge and facilitate the publication, sharing and reuse of such entities.

 In this paper we discuss the notion of _research objects_, semantically rich aggregations of resources, that can possess some scientific intent or support some research objective. We present a number of principles that we expect such objects and their associated services to follow

Semantics-Empowered Big Data Processing with Applications

We discuss the nature of Big Data and address the role of semantics in analyzing and processing Big Data that arises in the context of Physical-Cyber-Social Systems. We organize our research around the Five Vs of Big Data, where four of the Vs are harnessed to produce the fifth V - value. To handle the challenge of Volume, we advocate semantic perception that can convert low-level observational data to higher-level abstractions more suitable for decision-making. To handle the challenge of Variety, we resort to the use of semantic models and annotations of data so that much of the intelligent processing can be done at a level independent of heterogeneity of data formats and media. To handle the challenge of Velocity, we seek to use continuous semantics capability to dynamically create event or situation specific models and recognize relevant new concepts, entities and facts. To handle Veracity, we explore the formalization of trust models and approaches to glean trustworthiness. The above four Vs of Big Data are harnessed by the semantics-empowered analytics to derive value for supporting practical applications transcending physical-cyber-social continuum

USING NON-FINANCIAL DATA TO ASSESS THE CREDITWORTHINESS OF BUSINESSES IN ONLINE TRADE

Assessing the creditworthiness of prospective business partners is the first step in conducting trade. Traditionally the creditworthiness of partners was assessed using transactional methods, methods based on close observation of the other party and the heavy use of mostly subjective, soft information. During recent decades, however, these relational methods were largely replaced with transactional methods relying almost exclusively on objective financial data, otherwise known as hard data. A considerable portion of firms involved in business to business trade are now small companies that do not to have any reliable or comparable financial information. In the absence of such information, transactional methods of assessing business creditworthiness have very limited practical value. To provide a remedy, this study proposes using non-financial information available from the Web and thus a return to the more transactional methods. We identify sources of credit-related information available from a typical business to business exchange and test if such information can predict firm creditworthiness. We conduct a study with a group of online businesses on a major B2B exchange and empirically show that a number of non-financial factors can in fact predict online businesses’ level of creditworthiness

The Relationship Between Student Engagement and Professionalism in Pharmacy Students

This study investigates the relationship between student engagement (as measured by the National Survey of Student Engagement benchmarks) and pharmacy student professionalism (as measured by the Pharmacy Professionalism Domain instrument) in first and third year pharmacy students at seven different schools of pharmacy. Engagement provides the conceptual framework. Data were analyzed from 1,405 first and third year pharmacy students at seven different schools of pharmacy during spring 2010. Factor validity of the scales was assessed using Structural Equation modeling and model fit was established at RMSEA .052. The parameter estimates suggest convergent and divergent validity of the instruments. Mean level differences in professionalism were found by year with higher means for third year students in all of the professionalism domains except Reliability, Responsibility, and Accountability. Among first year students, the Enriching Educational Experience benchmark was the most important predictor of professionalism. Among third year students, the Student-Faculty Interaction was the most important predictor of professionalism

Research Objects: Towards Exchange and Reuse of Digital Knowledge

What will researchers be publishing in the future? Whilst there is little question that the Web will be the publication platform, as scholars move away from paper towards digital content, there is a need for mechanisms that support the production of self-contained units of knowledge and facilitate the publication, sharing and reuse of such entities. In this paper we discuss the notion of research objects, semantically rich aggregations of resources, that possess some scientifi?c intent or support some research objective. We present a number of principles that we expect such objects and their associated services to follow