Peer-to-peer Searching and Sharing of Electronic Documents

Peer-to-peer systems have existed since the first incarnation of the Internet. In recent times the Internet has taken on a more hierarchical form, power has been taken away from the individual and placed in the hands of operators of large servers. However, with the re-emergence of p2p the individual is gaining more freedom. End users attached to the Internet now have the power to host and publish content through the user of p2p technologies. Peer-to-peer systems present significant design challenges and have opened up a floodgate of research in an effort to overcome some of the fundamental problems. This thesis details a conceptual peer-to-peer design solution to some of the fundamental problems facing p2p systems today. A prototype is developed as a proof-of-concept. The prototype demonstrates how by enabling users to join communities of other like-minded users in order to exchange files, the p2p environment becomes more structured. It is argued that this structuring of the network into communities leads the way for a more scalable p2p system. Utilising the routing capabilities of the latest p2p algorithms, the prototype includes an indexing service that facilitates the creation of virtual rendezvous points for users with similar interests (manifested by shared keywords). Users are described by the content they store. By using state of the art Information Retrieval techniques users can be grouped together to content sensitive communities. It is intended that this system be used as the basis of a distributed archive of research papers. The concept presented seeks to improve the efficiency of file searches associated with p2p file sharing applications. This can be achieved by incorporating a novel content community service layer in order to organise nodes based on the content they store. This has the potential to improve on existing systems such as Gnutella where nodes are organised in a somewhat random fashion. Initial findings suggest that the system has better scalability properties giving the user better search results that reflect the true content available within the system. Search results are more comprehensive; as search queries on semantic meaning rather than literal matching

The Semantic Student: Using Knowledge Modeling Activities to Enhance Enquiry-Based Group Learning in Engineering Education

This paper argues that training engineering students in basic knowledge modeling techniques, using linked data principles, and semantic Web tools – within an enquiry-based group learning environment – enables them to enhance their domain knowledge, and their meta-cognitive skills. Knowledge modeling skills are in keeping with the principles of Universal Design for instruction. Learners are empowered with the regulation of cognition as they become more aware of their own development. This semantic student approach was trialed with a group of 3rd year Computer Engineering Students taking a module on computer architecture. An enquiry-based group learning activity was developed to help learners meet selected module learning outcomes. Learners were required to use semantic feature analysis and linked data principles to create a visual model of their knowledge structure. Results show that overall student attainment was increased when knowledge modeling activities were included as part of the learning process. A recommendation for practice to incorporate knowledge modeling as a learning strategy within an overall engineering curriculum framework is described. This can be achieved using semantic Web technologies such as semantic wikis and linked data tools

A Two-Level Information Modelling Translation Methodology and Framework to Achieve Semantic Interoperability in Constrained GeoObservational Sensor Systems

As geographical observational data capture, storage and sharing technologies such as in situ remote monitoring systems and spatial data infrastructures evolve, the vision of a Digital Earth, first articulated by Al Gore in 1998 is getting ever closer. However, there are still many challenges and open research questions. For example, data quality, provenance and heterogeneity remain an issue due to the complexity of geo-spatial data and information representation. Observational data are often inadequately semantically enriched by geo-observational information systems or spatial data infrastructures and so they often do not fully capture the true meaning of the associated datasets. Furthermore, data models underpinning these information systems are typically too rigid in their data representation to allow for the ever-changing and evolving nature of geo-spatial domain concepts. This impoverished approach to observational data representation reduces the ability of multi-disciplinary practitioners to share information in an interoperable and computable way. The health domain experiences similar challenges with representing complex and evolving domain information concepts. Within any complex domain (such as Earth system science or health) two categories or levels of domain concepts exist. Those concepts that remain stable over a long period of time, and those concepts that are prone to change, as the domain knowledge evolves, and new discoveries are made. Health informaticians have developed a sophisticated two-level modelling systems design approach for electronic health documentation over many years, and with the use of archetypes, have shown how data, information, and knowledge interoperability among heterogenous systems can be achieved. This research investigates whether two-level modelling can be translated from the health domain to the geo-spatial domain and applied to observing scenarios to achieve semantic interoperability within and between spatial data infrastructures, beyond what is possible with current state-of-the-art approaches. A detailed review of state-of-the-art SDIs, geo-spatial standards and the two-level modelling methodology was performed. A cross-domain translation methodology was developed, and a proof-of-concept geo-spatial two-level modelling framework was defined and implemented. The Open Geospatial Consortium’s (OGC) Observations & Measurements (O&M) standard was re-profiled to aid investigation of the two-level information modelling approach. An evaluation of the method was undertaken using II specific use-case scenarios. Information modelling was performed using the two-level modelling method to show how existing historical ocean observing datasets can be expressed semantically and harmonized using two-level modelling. Also, the flexibility of the approach was investigated by applying the method to an air quality monitoring scenario using a technologically constrained monitoring sensor system. This work has demonstrated that two-level modelling can be translated to the geospatial domain and then further developed to be used within a constrained technological sensor system; using traditional wireless sensor networks, semantic web technologies and Internet of Things based technologies. Domain specific evaluation results show that twolevel modelling presents a viable approach to achieve semantic interoperability between constrained geo-observational sensor systems and spatial data infrastructures for ocean observing and city based air quality observing scenarios. This has been demonstrated through the re-purposing of selected, existing geospatial data models and standards. However, it was found that re-using existing standards requires careful ontological analysis per domain concept and so caution is recommended in assuming the wider applicability of the approach. While the benefits of adopting a two-level information modelling approach to geospatial information modelling are potentially great, it was found that translation to a new domain is complex. The complexity of the approach was found to be a barrier to adoption, especially in commercial based projects where standards implementation is low on implementation road maps and the perceived benefits of standards adherence are low. Arising from this work, a novel set of base software components, methods and fundamental geo-archetypes have been developed. However, during this work it was not possible to form the required rich community of supporters to fully validate geoarchetypes. Therefore, the findings of this work are not exhaustive, and the archetype models produced are only indicative. The findings of this work can be used as the basis to encourage further investigation and uptake of two-level modelling within the Earth system science and geo-spatial domain. Ultimately, the outcomes of this work are to recommend further development and evaluation of the approach, building on the positive results thus far, and the base software artefacts developed to support the approach

A follow-up study of one hundred and four special class boys who attended the Center School at Salem in Massachusetts from September, 1936 to June, 1946

Thesis (Ed.M.)--Boston Universit