International Telemetering Conference Proceedings / October 28-31, 1996 / Town and Country Hotel and Convention Center, San Diego, California / Today it is not uncommon to have large contractor teams involved in the design and deployment of even small satellite systems. The larger (and more geographically remote) the team members, the more difficult it becomes to efficiently manage the disbursement of telemetry data for evaluation and analysis. Further complications are introduced if some of the telemetry data is sensitive. An application is described which can facilitate telemetry data sharing utilizing the National Information Infrastructure (Internet).

There are at least 21 dendro-data formats used in dendrochronology laboratories around the world. Many of these formats are read by a limited number of programs, thereby inhibiting collaboration, limiting critical review of analyses, and risking the long-term accessibility of datasets. Some of the older formats are supported by a single program and are falling into disuse, opening the risk for data to become obsolete and unreadable. These formats also have a variety of flaws, including but not limited to no accurate method for denoting measuring units, little or no metadata support, lack of support for variables other than whole ring widths (e.g. earlywood/latewood widths, ratios and density). The proposed long-term solution is the adoption of a universal data standard such as the Tree-Ring Data Standard (TRiDaS). In the short and medium term, however, a tool is required that is capable of converting not only back and forth to this standard, but between any of the existing formats in use today. Such a tool is also required to provide continued access to data archived in obscure formats. This paper describes TRiCYCLE, a new application that does just this. TRiCYCLE is an open-source, cross-platform, desktop application for the conversion of the most commonly used data formats. Two open source Java libraries upon which TRiCYCLE depends are also described. These libraries can be used by developers to implement support for all data formats within their own applications.

This thesis reports on a research project undertaken over a four year period investigating and developing a software framework and application for integrating and managing building product information for construction engineering. The research involved extensive literature research, observation of the industry practices and interviews with construction industry practitioners and systems implementers to determine how best to represent and present product information to support the construction process. Applicable product models for information representation were reviewed and evaluated to determine present suitability. The IFC product model was found to be the most applicable. Investigations of technologies supporting the product model led to the development of a software tool, the IFC Assembly Viewer, which aided further investigations into the suitability of the product model (in its current state) for the exchange and sharing of product information. A software framework, or reusable software design and application, called PROduct Information Management System (PROMIS), was developed based on a non-standard product model but with flexibility to work with the IFC product model when sufficiently mature. The software comprises three subsystems namely: ProductWeb, ModelManager.NET and Product/Project Service (or P2Service). The key features of this system were shared project databases, parametric product specification, integration of product information sources, and application interaction and integration through interface components. PROMIS was applied to and tested with a modular construction business for the management of product information and for integration of product and project information through the design and construction (production) process.

"Storing data on untrusted storage makes secure data sharing a challenge issue. On one hand, data access policies should be enforced on these storage servers; on the other hand, confidentiality of sensitive data should be well protected against them. Cryptographic methods are usually applied to address this issue -- only encrypted data are stored on storage servers while retaining secret key(s) to the data owner herself; user access is granted by issuing the corresponding data decryption keys. The main challenges for cryptographic methods include simultaneously achieving system scalability and fine-grained data access control, efficient key/user management, user accountability and etc. To address these challenge issues, this dissertation studies and enhances a novel public-key cryptography -- attribute-based encryption (ABE), and applies it for fine-grained data access control on untrusted storage. The first part of this dissertation discusses the necessity of applying ABE to secure data sharing on untrusted storage and addresses several security issues for ABE. More specifically, we propose three enhancement schemes for ABE: In the first enhancement scheme, we focus on how to revoke users in ABE with the help of untrusted servers. In this work, we enable the data owner to delegate most computation-intensive tasks pertained to user revocation to untrusted servers without disclosing data content to them. In the second enhancement scheme, we address key abuse attacks in ABE, in which authorized but malicious users abuse their access privileges by sharing their decryption keys with unauthorized users. Our proposed scheme makes it possible for the data owner to efficiently disclose the original key owner's identity merely by checking the input and output of a suspicious user's decryption device. Our third enhancement schemes study the issue of privacy preservation in ABE. Specifically, our proposed schemes hide the data owner's access policy not only to the untrusted servers but also to all the users. The second part presents our ABE-based secure data sharing solutions for two specific applications -- Cloud Computing and Wireless Sensor Networks (WSNs). In Cloud Computing cloud servers are usually operated by third-party providers, which are almost certain to be outside the trust domain of cloud users. To secure data storage and sharing for cloud users, our proposed scheme lets the data owner (also a cloud user) generate her own ABE keys for data encryption and take the full control on key distribution/revocation. The main challenge in this work is to make the computation load affordable to the data owner and data consumers (both are cloud users). We address this challenge by uniquely combining various computation delegation techniques with ABE and allow both the data owner and data consumers to securely mitigate most computation-intensive tasks to cloud servers which are envisaged to have unlimited resources. In WSNs, wireless sensor nodes are often unattendedly deployed in the field and vulnerable to strong attacks such as memory breach. For securing storage and sharing of data on distributed storage sensor nodes while retaining data confidentiality, sensor nodes encrypt their collected data using ABE public keys and store encrypted data on storage nodes. Authorized users are given corresponding decryption keys to read data. The main challenge in this case is that sensor nodes are extremely resource-constrained and can just afford limited computation/communication load. Taking this into account we divide the lifetime of sensor nodes into phases and distribute the computation tasks into each phase. We also revised the original ABE scheme to make the overhead pertained to user revocation minimal for sensor nodes. Feasibility of the scheme is demonstrated by experiments on real sensor platforms. "

This thesis explores new forms of scholarly communication and the practice of open science among UK based academics. Open science broadly refers to practices that allow cost-free open access to academic research. Three aspects of open science are examined in this study: open access to research articles; open access to research data; and publishing ongoing research updates using social media. The study employs a mixed-methods approach, combining a series of scoping studies using qualitative methods followed up by an Internet survey of 1,829 UK academics. Overall this thesis has shown that whilst there is support for open science, the use of open science by academics was limited. Many academics were not aware of RCUK's open access policy and had limited experience of making their research articles freely accessible online. Most academics did not share their primary research data online. Although some academics had used a range of social media tools to communicate their research, the majority had not used social media in their research work. Overall, male, older and senior academics were more likely to use open access publishing and share primary research data, but were less likely to use social media for research. Academics based in Medical and Natural Sciences were more likely to use open access publishing and share research data, but less likely to use social media for their research compared to academics from Humanities and Social Sciences. Academics who were aware of RCUK's open access policy and who recognised the citation advantages of open access were more likely to publish in open access journals. Academics that were aware of RCUK's open access policy and had used social media for research were more likely to self-archive research articles. Academics that had used secondary data collected by others and self-archived research papers were more likely to share their own primary research data. Academics seemed to be strongly influenced by their colleagues' recommendation for the adoption of social media in research. Those who considered that the general public should know about their research findings were more likely to share their research on social media. A group of academics were identified and described as super users who frequently communicated ongoing research on social media. These super users were more likely to use tablet computers and have received social media training organised by their institutions. It is clear that open science is going to be a major factor in future academic work and in relation to building an academic career. Many academics have recognised the importance of open science. However to date the use of the tools for open science has been limited. With the right guidance and reinforcement of relevant policies, the new forms of scholarly communication can provide a pathway to open science which would serve to benefit individual academics, research communities and the public good.

O desenvolvimento de sistemas de ensino a distância (EaD) adaptativos vêm sendo o alvo de pesquisa nos últimos anos, porém uma das carências mais importantes é que estes sistemas não possuem dados suficientes que descrevam o aluno, de modo a realizar a adaptação adequada. Uma das grandes dificuldades no processo é a aquisição desses dados. Normalmente para a realização de um curso em um sistema de EaD na Web, o aluno, entre outras atividades, deve cadastrar-se no sistema e informar seus dados pessoais. Alguns sistemas possuem mecanismos para descoberta das preferências do aluno, seu estilo de aprendizagem ou estilo cognitivo, visando oferecer um ensino personalizado. Porém, se este mesmo aluno se matricular em outro curso que utilize outro sistema de EaD na Web, todas essas informações não são repassadas de um sistema para o outro e acabam sendo informadas ou descobertas novamente. Portanto, os sistemas não colaboram entre si no sentido de tornar as informações sobre os alunos mais completas. Quanto mais variada for a informação que os sistemas tiverem sobre os alunos, o modelo do aluno em cada sistema estará mais completo e, conseqüentemente, a adaptabilidade do conteúdo ao seu perfil, mais eficiente. O objetivo principal desta tese é solucionar a problemática associada ao gerenciamento de dados contidos no modelo de aluno quando compartilhadas entre vários ambientes de ensino a distância (EaD). Como solução, esta tese propõe o modelo LPEM (Learner Profile Exchange Model) que define as estratégias que regem o compartilhamento de dados de modelos de aluno entre diversos sistemas. O diferencial do modelo está no uso de uma ontologia (OntoLearner), baseada em padrões, para a troca de dados. A especificação da ontologia OntoLearner também consiste em uma contribuição da tese, e pode ser utilizada no contexto de qualquer sistema desse mesmo domínio. Um subconjunto relativo as principais funcionalidades do modelo foi implementado, para isso também foi definida nesta tese a especificação física do modelo, que oferece as funcionalidades do modelo na forma de Web services. Uma arquitetura orientada a serviços também é descrita na tese e serve de referencia para implementação do modelo LPEM. O protótipo serviu de indicativo para comprovar que a solução proposta é possível de ser implementada, gerando os resultados esperados quanto ao compartilhamento dos dados. / The development of adaptive systems has been the target of some research works over the last years. However, an important lack to be considered is that these systems do not have enough information about the student in order to provide an adequate adaptation. One of the most important drawbacks for this lack is the difficulty of acquiring such information. New learners of an e-learning system are normally required to update their personal information before proceeding in one of the offered courses. Some systems are able to adapt its course content presentation using some techniques that discover the learner’s preferences, level of previous knowledge, and cognitive style. However, this important information about learners is not shared among different e-learning systems. This forces the learner to fill cumbersome forms in each new system, and also forces each new systems to analyze and process new learner’s behavioral information. By consequence, current systems do not collaborate with each other in order to enrich the information related to users of different e-learning systems. Considering these problems, the main objective of this thesis is to address the problem of data management within the learner’s model when data are shared among different e-learning systems. In this thesis we propose the LPEM (Learner Profile Exchange Model) model, which defines the strategies to share the learner’s data model among the different systems. The main contribution of the proposed model is the use of an ontology, named OntoLearner, which is based on standards for data exchange. The ontology OntoLerarner is a contribution as well, since it has been developed for LPEM but can be used by any other system in this domain. A subset of the main functionalities of the proposed model was implemented. For that purpose, the physical model was defined in order to provide a functionalities model for Web Services. The prototype shows that the proposed solution can be implemented, generating the results expected for data sharing.

Families living on welfare in low-income impoverished neighborhoods encounter multiple barriers that need mitigating before seeking work to reach self-sufficiency. Many welfare recipients' self-sufficiency barriers are unnoticeable to caseworkers due to lack of data sharing to assess clients' needs through information technology processes. The purpose of this exploratory descriptive phenomenological qualitative study was to understand welfare recipients' viewpoints on socioeconomic barriers to living self-sufficiently and gain perspectives from human services caseworkers and technical resources on data sharing issues that impact recipients' ability to live independently from government assistance. Data collection and observational field notes resulted from in-depth interviews of 11 participants to capture welfare recipients' lived experience on human services barriers to achieve self-sufficiency, as well as, caseworker and technical resources views on welfare systems data sharing issues. The analysis of semistructured interviews revealed that welfare systems data sharing is an enhancement needed to help caseworkers identify and mitigate welfare recipients' self-sufficiency barriers. The common assessment framework model provided a contextual view to exploring research questions to elicit participants' perceptions of data sharing in welfare systems processes. The data analysis showed that the lack of data sharing impacts caseworkers' ability to assist recipients with self-sufficiency barriers. Results indicated the need for caseworkers to use data sharing to understand client's socioeconomic barriers and to make effective decisions to lead them to self-sufficiency. The impact on positive social change is using automated data sharing to identify and mitigate recipients' barriers to self-sufficiency.

In this talk, we will present the design and evaluation of PeerDB, a peer-to-peer (P2P) distributed data sharing system. PeerDB distinguishes itself from existing P2P systems in several ways. First, it is a full-fledge data management system that supports fine-grain content-based searching. Second, it facilitates sharing of data without shared schema. Third, it combines the power of mobile agents into P2P systems to perform operations at peers' sites. Fourth, PeerDB network is self-configurable, i.e., a node can dynamically optimize the set of peers that it can communicate directly with based on some optimization criterion. / Singapore-MIT Alliance (SMA)

Decisions to refer students for disciplinary consequences (Hyman & Perone, 1998), eligibility for special services referrals (Smart, Wilton, & Keeling, 1980), and even suspension or expulsion (Brooks, Schiraldi, & Zeidenberg, 2000), are all likely to be driven by teacher perceptions of student behavior. Yet though there is a wealth of research investigating the mechanisms and consequences of teacher perceptions of student behavior, the accuracy of these perceptions has not been addressed in the literature. This study contrasted staff responses on questionnaires about student behavior by infraction category, school locations, and times with the actual referral counts from each setting to achieve a measure of perceptive accuracy for each participant. The results presented in this study extend the research literature on teacher perceptions by providing strong support for data sharing as a perception-changing mechanism among participants working in schools implementing school-wide positive behavior support (SWPBS). Participants assigned to conditions in which school-wide discipline data were shared had accuracy scores which were statistically higher than those in non-data sharing conditions. However, asking participants to report their perceptions more than once did not increase the accuracy of their responses in a statistically significant way. The application of an experimental research design and the use of appropriate statistical significance tests draw attention to effects which are statistically real. Additionally, the random assignment of participants within schools to one of four conditions provides us with confidence that the intervention, and not some factor, caused the change in accuracy scores among participants.

Distributed systems, characterized by their ability to ensure the execution of multiple transactions across a myriad of applications, constitute a prime platform for building Web applications. However, Web application interactions raise issues pertaining to security and performance that make manual security management both time-consuming and challenging. This thesis is a testimony to the security and performance enhancements afforded by using the autonomic computing paradigm to design an adaptive cryptographic access control framework for dynamic data sharing environments. One of the methods of enforcing cryptographic access control in these environments is to classify users into one of several groups interconnected in the form of a partially ordered set. Each group is assigned a single cryptographic key that is used for encryption/decryption. Access to data is granted only if a user holds the "correct" key, or can derive the required key from the one in their possession. This approach to access control is a good example of one that provides good security but has the drawback of reacting to changes in group membership by replacing keys, and re-encrypting the associated data, throughout the entire hierarchy. Data re-encryption is time-consuming, so, rekeying creates delays that impede performance. In order to support our argument in favor of adaptive security, we begin by presenting two cryptographic key management (CKM) schemes in which key updates affect only the class concerned or those in its sub-poset. These extensions enhance performance, but handling scenarios that require adaptability remain a challenge. Our framework addresses this issue by allowing the CKM scheme to monitor the rate at which key updates occur and to adjust resource (keys and encrypted data versions) allocations to handle future changes by anticipation rather than on demand. Therefore, in comparison to quasi-static approaches, the adaptive CKM scheme minimizes the long-term cost of key updates. Finally, since self-protecting CKM requires a lesser degree of physical intervention by a human security administrator, we consider the case of "collusion attacks" and propose two algorithms to detect as well as prevent such attacks. A complexity and security analysis show the theoretical improvements our schemes offer. Each algorithm presented is supported by a proof of concept implementation, and experimental results to show the performance improvements. / Thesis (Ph.D, Computing) -- Queen's University, 2008-10-16 16:19:46.617