176 research outputs found

    Fulfilling the needs of a metadata creator and analyst : An investigation of RDF browsing and visualization tools

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    The realization of Semantic Web vision is based on the creation and use of semantic web content which needs software tools both for semantic web developers and end users. Over the past few years, semantic web software tools like ontology editors and triple storage systems have emerged and are growing in maturity with time. While working on a large triple dataset during the course of a research aiming at a life-long “semantic” repository of personal information, besides other semantic web tools, we used several RDF browsing and visualization tools for analyzing our data. This analysis included ensuring the correctness of the data, conformance of instance data to the ontology, finding patterns and trails in the data, cross-checking and evaluating inferred data, etc. We found that many of the features needed by a metadata creator and analyst are missing from these tools. This paper presents an investigation of the tools that are used for browsing and visualizing RDF datasets. It first identifies the browsing and visualization features required by a semantic web developer and a metadata creator and analyst and then based on those features evaluates the most common RDF browsing and visualization tools available till date. We conclude this paper with recommendations for requirements to be fulfilled for future semantic web browsing and visualizationThe past and the future of information systems: 1976-2006 and beyondRed de Universidades con Carreras en Informática (RedUNCI

    Building XML data warehouse based on frequent patterns in user queries

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    [Abstract]: With the proliferation of XML-based data sources available across the Internet, it is increasingly important to provide users with a data warehouse of XML data sources to facilitate decision-making processes. Due to the extremely large amount of XML data available on web, unguided warehousing of XML data turns out to be highly costly and usually cannot well accommodate the users’ needs in XML data acquirement. In this paper, we propose an approach to materialize XML data warehouses based on frequent query patterns discovered from historical queries issued by users. The schemas of integrated XML documents in the warehouse are built using these frequent query patterns represented as Frequent Query Pattern Trees (FreqQPTs). Using hierarchical clustering technique, the integration approach in the data warehouse is flexible with respect to obtaining and maintaining XML documents. Experiments show that the overall processing of the same queries issued against the global schema become much efficient by using the XML data warehouse built than by directly searching the multiple data sources

    ONGOING SOCIAL SUSTAINABILITY COMPLIANCE MONITORING IN SUPPLY CHAINS

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    Social sustainability issus such as child labour at a supplier pose significant reputational risk for companies. Therefore, many companies now require that suppliers follow certain standards or codes of conduct. However, in today´s complex supply chains with hundreds of sourcing locations, ongoing monitoring of compliance through audits for every supplier is hardly practical. Consequntly, an information technology system is investigated as a tool to establish ongoing monitoring of suppliers based on available information with regard to the risk that suppliers breach the compliance rules defined. This paper describes work on a system that uses a Bayesian network to integrate evidence from multiple public and private data sources in order to rank suppliers dynamically. A particular focus of future work will be a prototype based on the issu of child labour and the advantages of applying text mining methods

    Fulfilling the needs of a metadata creator and analyst : An investigation of RDF browsing and visualization tools

    Get PDF
    The realization of Semantic Web vision is based on the creation and use of semantic web content which needs software tools both for semantic web developers and end users. Over the past few years, semantic web software tools like ontology editors and triple storage systems have emerged and are growing in maturity with time. While working on a large triple dataset during the course of a research aiming at a life-long “semantic” repository of personal information, besides other semantic web tools, we used several RDF browsing and visualization tools for analyzing our data. This analysis included ensuring the correctness of the data, conformance of instance data to the ontology, finding patterns and trails in the data, cross-checking and evaluating inferred data, etc. We found that many of the features needed by a metadata creator and analyst are missing from these tools. This paper presents an investigation of the tools that are used for browsing and visualizing RDF datasets. It first identifies the browsing and visualization features required by a semantic web developer and a metadata creator and analyst and then based on those features evaluates the most common RDF browsing and visualization tools available till date. We conclude this paper with recommendations for requirements to be fulfilled for future semantic web browsing and visualizationThe past and the future of information systems: 1976-2006 and beyondRed de Universidades con Carreras en Informática (RedUNCI

    Complex matching of RDF datatype properties

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    Property mapping is a fundamental component of ontology matching, and yet there is little support that goes beyond the identification of single property matches. Real data often requires some degree of composition, trivially exemplified by the mapping of "first name" and "last name" to "full name" on one end, to complex matchings, such as parsing and pairing symbol/digit strings to SSN numbers, at the other end of the spectrum. In this paper, we propose a two-phase instance-based technique for complex datatype property matching. Phase 1 computes the Estimate Mutual Information matrix of the property values to (1) find simple, 1:1 matches, and (2) compute a list of possible complex matches. Phase 2 applies Genetic Programming to the much reduced search space of candidate matches to find complex matches. We conclude with experimental results that illustrate how the technique works. Furthermore, we show that the proposed technique greatly improves results over those obtained if the Estimate Mutual Information matrix or the Genetic Programming techniques were to be used independently. The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-40285-2_18

    UbiqLog: a generic mobile phone based life-log framework

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    Smart phones are conquering the mobile phone market; they are not just phones they also act as media players, gaming consoles, personal calendars, storage, etc. They are portable computers with fewer computing capabilities than personal computers. However unlike personal computers users can carry their smartphone with them at all times. The ubiquity of mobile phones and their computing capabilities provide an opportunity of using them as a life logging device. Life-logs (personal e-memories) are used to record users' daily life events and assist them in memory augmentation. In a more technical sense, life-logs sense and store users' contextual information from their environment through sensors, which are core components of life-logs. Spatio-temporal aggregation of sensor information can be mapped to users' life events. We propose UbiqLog, a lightweight, configurable and extendable life-log framework that uses mobile phone as a device for life logging. The proposed framework extends previous research in this field, which investigated mobile phones as life-log tool through continuous sensing. Its openness in terms of sensor configuration allows developers to create exible, multipurpose life-log tools. In addition to that this framework contains a data model and an architecture, which can be used as reference model for further life-log development, including its extension to other devices, such as ebook readers, T.V.s, etc

    A framework for efficent association rule mining in XML data

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    [Abstract]: In this paper, we propose a framework, called XAR-Miner, for mining ARs from XML documents efficiently. In XAR-Miner, raw data in the XML document are first preprocessed to transform to either an Indexed XML Tree (IX-tree) or Multi-relational Databases (Multi-DB), depending on the size of XML document and memory constraint of the system, for efficient data selection and AR mining. Concepts that are relevant to the AR mining task are generalized to produce generalized meta-patterns. A suitable metric is devised for measuring the degree of concept generalization in order to prevent under-generalization or over-generalization. Resulting generalized meta-patterns are used to generate large ARs that meet the support and confidence levels. A greedy algorithm is also presented to integrate data selection and large itemset generation to enhance the efficiency of the AR mining process. The experiments conducted show that XAR-Miner is more efficient in performing a large number of AR mining tasks from XML documents than the state-of-the-art method of repetitively scanning through XML documents in order to perform each of the mining tasks

    Tjoa A M.: An Approach towards the Fulfilment of Security Requirements for Decision Support Systems

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    Evidence-based medicine is a new healthcare scientific paradigm aiming at the prevention, diagnosis and treatment of diseases using medical evidence. Because of the complex nature of the clinician’s task to gather all the necessary knowledge about given diseases, the practice of evidence-based medicine could not be envisioned without IT support. Integration of external evidence-based data sources into the existing clinical information system and finding of appropriate therapy alternatives for a given patient and a given disease is a major research challenge. With the rapid changes taking place in the field of health care, decision support systems play an increasingly important role. We propose a data warehouse solution, as an easy-to-use decision support platform, to enable the integration of a wide range of data sources. Caused by the innovative character of the field, no explicit common security regulations and standards yet exist. Defining these measures is a process, where both the patient’s individual rights (patient’s privacy and data protection) and the collective, societal demands (scientific progress and development of new technologies) need to be considered. This paper discusses the security measures to be enforced in order to protect the extraordinary sensitive nature of health data while usin
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