Enhanced Trustworthy and High-Quality Information Retrieval System for Web Search Engines

The WWW is the most important source of information. But, there is no guarantee for information correctness and lots of conflicting information is retrieved by the search engines and the quality of provided information also varies from low quality to high quality. We provide enhanced trustworthiness in both specific (entity) and broad (content) queries in web searching. The filtering of trustworthiness is based on 5 factors – Provenance, Authority, Age, Popularity, and Related Links. The trustworthiness is calculated based on these 5 factors and it is stored thereby increasing the performance in retrieving trustworthy websites. The calculated trustworthiness is stored only for static websites. Quality is provided based on policies selected by the user. Quality based ranking of retrieved trusted information is provided using WIQA (Web Information Quality Assessment) Framework

Data Representation Model for Management and Distribution of Scientific Data

Scientific tools and computer simulations enable rapid creation of various types of data and a number of studies have been conducted on data provenance and web-based data representation models to enhance the distribution, reproduction and reusability of scientific data. Ontology is a knowledge representation model, which is also used as data and workflow technology for data provenance. In this study, as part of managing and distributing for scientific data studies, metadata and data representation model were defined for the management and distribution of Visible Korean online. In addition, additional metadata required for re-distributing the user data created through the Visible Korean study is defined using an ontology-based data representation model, and an RDFa-based web page generation method is proposed to search and extract data from existing web pages. This study enables to manage and distribute the Visible Korean online, which has been managed and distributed offline, and a virtuous recycling of distributing research results as wells

Hybrid Search: Effectively Combining Keywords and Semantic Searches

This paper describes hybrid search, a search method supporting both document and knowledge retrieval via the flexible combination of ontologybased search and keyword-based matching. Hybrid search smoothly copes with lack of semantic coverage of document content, which is one of the main limitations of current semantic search methods. In this paper we define hybrid search formally, discuss its compatibility with the current semantic trends and present a reference implementation: K-Search. We then show how the method outperforms both keyword-based search and pure semantic search in terms of precision and recall in a set of experiments performed on a collection of about 18.000 technical documents. Experiments carried out with professional users show that users understand the paradigm and consider it very powerful and reliable. K-Search has been ported to two applications released at Rolls-Royce plc for searching technical documentation about jet engines

A Linked Data Approach to Sharing Workflows and Workflow Results

A bioinformatics analysis pipeline is often highly elaborate, due to the inherent complexity of biological systems and the variety and size of datasets. A digital equivalent of the ‘Materials and Methods’ section in wet laboratory publications would be highly beneficial to bioinformatics, for evaluating evidence and examining data across related experiments, while introducing the potential to find associated resources and integrate them as data and services. We present initial steps towards preserving bioinformatics ‘materials and methods’ by exploiting the workflow paradigm for capturing the design of a data analysis pipeline, and RDF to link the workflow, its component services, run-time provenance, and a personalized biological interpretation of the results. An example shows the reproduction of the unique graph of an analysis procedure, its results, provenance, and personal interpretation of a text mining experiment. It links data from Taverna, myExperiment.org, BioCatalogue.org, and ConceptWiki.org. The approach is relatively ‘light-weight’ and unobtrusive to bioinformatics users

The Research Object Suite of Ontologies: Sharing and Exchanging Research Data and Methods on the Open Web

Research in life sciences is increasingly being conducted in a digital and online environment. In particular, life scientists have been pioneers in embracing new computational tools to conduct their investigations. To support the sharing of digital objects produced during such research investigations, we have witnessed in the last few years the emergence of specialized repositories, e.g., DataVerse and FigShare. Such repositories provide users with the means to share and publish datasets that were used or generated in research investigations. While these repositories have proven their usefulness, interpreting and reusing evidence for most research results is a challenging task. Additional contextual descriptions are needed to understand how those results were generated and/or the circumstances under which they were concluded. Because of this, scientists are calling for models that go beyond the publication of datasets to systematically capture the life cycle of scientific investigations and provide a single entry point to access the information about the hypothesis investigated, the datasets used, the experiments carried out, the results of the experiments, the people involved in the research, etc. In this paper we present the Research Object (RO) suite of ontologies, which provide a structured container to encapsulate research data and methods along with essential metadata descriptions. Research Objects are portable units that enable the sharing, preservation, interpretation and reuse of research investigation results. The ontologies we present have been designed in the light of requirements that we gathered from life scientists. They have been built upon existing popular vocabularies to facilitate interoperability. Furthermore, we have developed tools to support the creation and sharing of Research Objects, thereby promoting and facilitating their adoption.Comment: 20 page

The use of provenance in information retrieval

The volume of electronic information that users accumulate is steadily rising. A recent study [2] found that there were on average 32,000 pieces of information (e-mails, web pages, documents, etc.) for each user. The problem of organizin