Quality Assessment of Linked Datasets using Probabilistic Approximation

With the increasing application of Linked Open Data, assessing the quality of datasets by computing quality metrics becomes an issue of crucial importance. For large and evolving datasets, an exact, deterministic computation of the quality metrics is too time consuming or expensive. We employ probabilistic techniques such as Reservoir Sampling, Bloom Filters and Clustering Coefficient estimation for implementing a broad set of data quality metrics in an approximate but sufficiently accurate way. Our implementation is integrated in the comprehensive data quality assessment framework Luzzu. We evaluated its performance and accuracy on Linked Open Datasets of broad relevance.Comment: 15 pages, 2 figures, To appear in ESWC 2015 proceeding

Opportunistic linked data querying through approximate membership metadata

Between URI dereferencing and the SPARQL protocol lies a largely unexplored axis of possible interfaces to Linked Data, each with its own combination of trade-offs. One of these interfaces is Triple Pattern Fragments, which allows clients to execute SPARQL queries against low-cost servers, at the cost of higher bandwidth. Increasing a client's efficiency means lowering the number of requests, which can among others be achieved through additional metadata in responses. We noted that typical SPARQL query evaluations against Triple Pattern Fragments require a significant portion of membership subqueries, which check the presence of a specific triple, rather than a variable pattern. This paper studies the impact of providing approximate membership functions, i.e., Bloom filters and Golomb-coded sets, as extra metadata. In addition to reducing HTTP requests, such functions allow to achieve full result recall earlier when temporarily allowing lower precision. Half of the tested queries from a WatDiv benchmark test set could be executed with up to a third fewer HTTP requests with only marginally higher server cost. Query times, however, did not improve, likely due to slower metadata generation and transfer. This indicates that approximate membership functions can partly improve the client-side query process with minimal impact on the server and its interface

Preserving Context Privacy in Distributed Hash Table Wireless Sensor Networks.

Wireless Sensor Networks (WSN) are often deployed in hostile or difficult scenarios, such as military battlefields and disaster recovery, where it is crucial for the network to be highly fault tolerant, scalable and decentralized. For this reason, peer-to-peer primitives such as Distributed Hash Table (DHT), which can greatly enhance the scalability and resilience of a network, are increasingly being introduced in the design of WSN's. Securing the communication within the WSN is also imperative in hostile settings. In particular, context information, such as the network topology and the location and identity of base stations (which collect data gathered by the sensors and are a central point of failure) can be protected using traffic encryption and anonymous routing. In this paper, we propose a protocol achieving a modified version of onion routing over wireless sensor networks based on the DHT paradigm. The protocol prevents adversaries from learning the network topology using traffic analysis, and therefore preserves the context privacy of the network. Furthermore, the proposed scheme is designed to minimize the computational burden and power usage of the nodes, through a novel partitioning scheme and route selection algorithm

TailX: Scheduling Heterogeneous Multiget Queries to Improve Tail Latencies in Key-Value Stores

International audienceUsers of interactive services such as e-commerce platforms have high expectations for the performance and responsiveness of these services. Tail latency, denoting the worst service times, contributes greatly to user dissatisfaction and should be minimized. Maintaining low tail latency for interactive services is challenging because a request is not complete until all its operations are completed. The challenge is to identify bottleneck operations and schedule them on uncoordinated backend servers with minimal overhead, when the duration of these operations are heterogeneous and unpredictable. In this paper, we focus on improving the latency of multiget operations in cloud data stores. We present TailX, a task-aware multiget scheduling algorithm that improves tail latencies under heterogeneous workloads. TailX schedules operations according to an estimation of the size of the corresponding data, and allows itself to procrastinate some operations to give way to higher priority ones. We implement TailX in Cassandra, a widely used key-value store. The result is an improved overall performance of the cloud data stores for a wide variety of heterogeneous workloads. Specifically, our experiments under heterogeneous YCSB workloads show that TailX outperforms state-of-the-art solutions and reduces tail latencies by up to 70% and median latencies by up to 75%

Secure set-based policy checking and its application to password registration

Policies are the corner stones of today's computer systems. They define secure states and safe operations. A common problem with policies is that their enforcement is often in con ict with user privacy. In order to check the satisfiability of a policy, a server usually needs to collect from a client some information which may be private. In this work we introduce the notion of secure set-based policy checking (SPC) that allows the server to verify policies while preserving the client's privacy. SPC is a generic protocol that can be applied in many policy-based systems. As an example, we show how to use SPC to build a password registration protocol so that a server can check whether a client's password is compliant with its password policy without seeing the password. We also analyse SPC and the password registration protocol and provide security proofs. To demonstrate the practicality of the proposed primitives, we report performance evaluation results based on a prototype implementation of the password registration protoco

Spatial Bloom Filters: Enabling Privacy in Location-Aware Applications

The wide availability of inexpensive positioning systems made it possible to embed them into smartphones and other personal devices. This marked the beginning of location-aware applications, where users request personalized services based on their geographic position. The location of a user is, however, highly sensitive information: the user's privacy can be preserved if only the minimum amount of information needed to provide the service is disclosed at any time. While some applications, such as navigation systems, are based on the users' movements and therefore require constant tracking, others only require knowledge of the user's position in relation to a set of points or areas of interest. In this paper we focus on the latter kind of services, where location information is essentially used to determine membership in one or more geographic sets. We address this problem using Bloom Filters (BF), a compact data structure for representing sets. In particular, we present an extension of the original Bloom filter idea: the Spatial Bloom Filter (SBF). SBF's are designed to manage spatial and geographical information in a space efficient way, and are well-suited for enabling privacy in location-aware applications. We show this by providing two multi-party protocols for privacy-preserving computation of location information, based on the known homomorphic properties of public key encryption schemes. The protocols keep the user's exact position private, but allow the provider of the service to learn when the user is close to specific points of interest, or inside predefined areas. At the same time, the points and areas of interest remain oblivious to the user

Dementia and guardianship: challenges in social work practice in a health care setting

This thesis critically examines social work practice in complex and disputed situations where an alternative legal decision-maker is perceived as necessary for a person with dementia. Australia has unique adult guardianship legislation and social workers are actively engaged in the process in a variety of ways, such as weighing the benefits against the possible harm and lodging applications. Yet within the profession this is an area where there is very little research. The purpose of this study is therefore to enable social workers to better understand the dynamics involved in adult guardianship proceedings for a person with dementia and provide knowledge that can be used for more effective practice. The theoretical approach is to use perspectives from social constructionism, with the links which can be made to modernism and postmodernism being taken into account. Five research case studies were investigated drawing from the caseload of social workers in an aged care service at a large metropolitan hospital in Australia. A thematic network analysis of the findings showed that the research case studies are constantly evolving, where different players participate by bringing their own perspectives, and in this process alliances are formed which reflect underlying dynamics of power. There are many diverse and contested issues, such as varied understandings of dementia and capacity and differing constructions of the notions of risk, protection and responsibility. The implications for social work practice are that in a contemporary health and welfare context social work is well placed to make an important contribution through its traditional roles of negotiation, interpretation and mediation between those who have discursive rights and those who do not

Hypoxia inducible factor 1α gene (HIF-1α) splice variants: potential prognostic biomarkers in breast cancer

<p>Abstract</p> <p>Background</p> <p>Hypoxia-inducible factor 1 (HIF-1) is a master transcriptional regulator of genes regulating oxygen homeostasis. The HIF-1 protein is composed of two HIF-1α and HIF-1β/aryl hydrocarbon receptor nuclear translocator (ARNT) subunits. The prognostic relevance of HIF-1α protein overexpression has been shown in breast cancer. The impact of HIF-1α alternative splice variant expression on breast cancer prognosis in terms of metastasis risk is not well known.</p> <p>Methods</p> <p>Using real-time quantitative reverse transcription PCR assays, we measured mRNA concentrations of total <it>HIF-1α </it>and 4 variants in breast tissue specimens in a series of 29 normal tissues or benign lesions (normal/benign) and 53 primary carcinomas. In breast cancers <it>HIF-1α </it>splice variant levels were compared to clinicopathological parameters including tumour microvessel density and metastasis-free survival.</p> <p>Results</p> <p><it>HIF-1α </it>isoforms containing a three base pairs TAG insertion between exon 1 and exon 2 (designated <it>HIF-1α</it>^<it>TAG</it>) and <it>HIF-1α</it>^{<it>736 </it>}mRNAs were found expressed at higher levels in oestrogen receptor (OR)-negative carcinomas compared to normal/benign tissues (<it>P </it>= 0.009 and <it>P </it>= 0.004 respectively). In breast carcinoma specimens, lymph node status was significantly associated with <it>HIF-1α</it>^{<it>TAG </it>}mRNA levels (<it>P </it>= 0.037). Significant statistical association was found between tumour grade and <it>HIF-1α</it>^{<it>TAG </it>}(<it>P </it>= 0.048), and total <it>HIF-1α </it>(<it>P </it>= 0.048) mRNA levels. <it>HIF-1α</it>^{<it>TAG </it>}mRNA levels were also inversely correlated with both oestrogen and progesterone receptor status (<it>P </it>= 0.005 and <it>P </it>= 0.033 respectively). Univariate analysis showed that high <it>HIF-1α</it>^{<it>TAG </it>}mRNA levels correlated with shortened metastasis free survival (<it>P </it>= 0.01).</p> <p>Conclusions</p> <p>Our results show for the first time that mRNA expression of a <it>HIF-1α</it>^{<it>TAG </it>}splice variant reflects a stage of breast cancer progression and is associated with a worse prognosis.</p> <p>See commentary: <url>http://www.biomedcentral.com/1741-7015/8/45</url></p