ETL-based interoperable data management system

An explosive increase of information and demand for inter-contents association knowledge has made clear the need for integrated contents management. With contents being managed in various ways, the issue of maintaining interoperability among data also has been a consistent concern. This paper proposes possible solutions for the integration of contents management and the unification of the management processes. It has been proven that the e-Tracer system is easy to use and appropriate to the integration of metadata through user’s usage and it is able to maintain interoperability for different types of contents.     

An interoperable spatiotemporal weather radar data dissemination system

This paper investigates an interoperable framework to disseminate Earth Science data to different application domains. The proposed framework can manage different Earth science data products and raster snapshots over time through the use of relevant metadata information. The framework generates images to be accessed by GIS software for various Earth science and web‐based applications. The access is enabled through the compliance with OpenGeospatial Consortium's Web Map Service (WMS) for interoperability such that any WMS viewer can access the service. The framework can provide GIS users the capability to incorporate geospatial information from other WMS servers. Using the United States NEXt generation weather RADar (NEXRAD) data, we demonstrate how the proposed framework can facilitate the dissemination of Earth Science data to a broad community in a near real‐time fashion. The proposed framework can be used to manage and disseminate various types of spatiotemporal Earth science data.     

Scaling Web sites through caching

A large jump in a Web site's traffic may indicate success, but this increased interest could turn into a nightmare if the site is not prepared to handle the bigger load. Site resources (processors, storage boxes, load balancers, LANs, and the like) could see their utilization rise to levels that generate increasingly long response times. Eventually, one of these resources - the so-called bottleneck resource - will reach 100 percent utilization, pushing the site's throughput to its maximum point. When a Web site becomes overloaded, customers grow frustrated with long waits and rejected requests. This situation can lead to an undesirable loss of site-generated revenue and may even tarnish the reputation of organizations relying on Web sites to support mission-critical applications. In this article, I discuss how caching technologies can improve Web site performance and scalability. I'll provide some simple quantitative expressions to let designers understand the most important trade-offs.     

Scaling CMOS devices through alternative structures

The conventional wisdom holds that CMOS devices cannot be scaled much further from where they are today because of several device physics limitations such as the large tunneling current in very thin gate dielectrics. It is shown that alternative device structures can allow CMOS transistors to scale by another 20 times. That is as large a factor of scaling as what the semiconductor industry accomplished in the past 25 years. There will be many opportunities and challenges in finding novel device structures and new processing techniques, and in understanding the physics of future devices.     

Scaling access to heterogeneous data sources with DISCO

Accessing many data sources aggravates problems for users of heterogeneous distributed databases. Database administrators must deal with fragile mediators, that is, mediators with schemas and views that must be significantly changed to incorporate a new data source. When implementing translators of queries from mediators to data sources, database implementers must deal with data sources that do not support all the functionality required by mediators. Application programmers must deal with graceless failures for unavailable data sources. Queries simply return failure and no further information when data sources are unavailable for query processing. The Distributed Information Search COmponent (Disco) addresses these problems. Data modeling techniques manage the connections to data sources, and sources can be added transparently to the users and applications. The interface between mediators and data sources flexibly handles different query languages and different data source functionality. Query rewriting and optimization techniques rewrite queries so they are efficiently evaluated by sources. Query processing and evaluation semantics are developed to process queries over unavailable data sources. In this article, we describe: 1) the distributed mediator architecture of Disco; 2) the data model and its modeling of data source connections; 3) the interface to underlying data sources and the query rewriting process; and 4) query processing semantics. We describe several advantages of our system     

Cross-border issues under EU data protection law with regards to personal data protection

We are living in an inter-connected, global digital society where the services of different operating systems are universal in nature, but many Internet activities are still being tackled by national laws and regulations. A long-existing question is which law is applicable in cases of Internet activities because the online world does not have any physical boundaries. How the European Union (EU) approaches this duality has become a concern for data protection laws. By analysing some recent Court of Justice of the European Union case laws, this article seeks to discover how the EU data protection law tackles disputes involving transnational issues online, which includes its extra-territorial application and cross-border data transfers. The article also indicates that there is an enormous gap between legislation and practice.     

An icosahedron-based method for even binning of globally distributed remote sensing data

A new scheme is presented for binning globally distributed measurements. The scheme is based on a network of evenly distributed grid points, defined by repeated subdivision of a spherical icosahedron. Delanuany triangulation is then used to obtain bin perimeters for each grid point, which results in a network of bins that are evenly distributed across the entire globe and have uniform area. A modified winding rule is used to determine which datapoints are in which bin. This binning method is especially suited to remote sensing applications involving datasets covering polar regions, where conventional rectangular latitude/longitude bins introduce distortion and streaking into the binned data if noise is present. It also has the property that adjacent bins overlap, providing Nyquist sampling and preventing spatial aliasing. Tests on synthetic data show that this icosahedral binning scheme preserves underlying data trends and is robust to noise.     

Validation of SeaWiFS and MODIS aerosol products with globally distributed AERONET data

The validation of aerosol products derived from ocean color missions is required for the assessment of their uncertainties and as a diagnostic for the atmospheric correction schemes used for determining the ocean apparent optical properties. A comprehensive validation of the aerosol products obtained from the ocean color missions SeaWiFS and MODIS is presented; it relies on the field observations collected at 85 AERONET sites and is completed by preliminary results obtained with the data of the maritime AERONET component. A robust match-up selection protocol yields approximately 7000 match-ups for each sensor. The median absolute relative difference for the aerosol optical thickness τ_a increases from 20-22% at 443 nm to 45-48% in the near-infrared. The validation statistics are comparable for both sensors but MODIS results appear degraded particularly for sites located on isolated islands. The median absolute difference is approximately 0.03 at all wavelengths. Results are further analyzed for specific geographic regions or groups of sites selected to represent oceanic, continental, or desert dust conditions. Importantly, the match-up sets appear generally representative of the regional natural variability in τ_a amplitude and spectral shape, with the notable exception of high τ_a conditions that are excluded. An important finding is the underestimate by the atmospheric correction of the Ångström exponent α, with a median bias of − 0.52. This underestimate is apparent even at low α values and regularly increases with α. This discrepancy in τ_a spectral shape might result from an inappropriate set of candidate aerosol models and/or uncertainties in the calibration at the near-infrared bands. As the validation data base is expanded and updated in relation to new versions of the processing chains, this work provides a benchmark for the assessment of the aerosol products derived from the SeaWiFS and MODIS ocean color missions.     

Rights protection for relational data

we introduce a solution for relational database content rights protection through watermarking. Rights protection for relational data is of ever-increasing interest, especially considering areas where sensitive, valuable content is to be outsourced. A good example is a data mining application, where data is sold in pieces to parties specialized in mining it. Different avenues are available, each with its own advantages and drawbacks. Enforcement by legal means is usually ineffective in preventing theft of copyrighted works, unless augmented by a digital counterpart, for example, watermarking. While being able to handle higher level semantic constraints, such as classification preservation, our solution also addresses important attacks, such as subset selection and random and linear data changes. We introduce wmdb., a proof-of-concept implementation and its application to real-life data, namely, in watermarking the outsourced Wal-Mart sales data that we have available at our institute.     

Rights protection for categorical data

A novel method of rights protection for categorical data through watermarking is introduced in this paper. New watermark embedding channels are discovered and associated novel watermark encoding algorithms are proposed. While preserving data quality requirements, the introduced solution is designed to survive important attacks, such as subset selection and random alterations. Mark detection is fully "blind" in that it doesn't require the original data, an important characteristic, especially in the case of massive data. Various improvements and alternative encoding methods are proposed and validation experiments on real-life data are performed. Important theoretical bounds including mark vulnerability are analyzed. The method is proved (experimentally and by analysis) to be extremely resilient to both alteration and data loss attacks, for example, tolerating up to 80 percent data loss with a watermark alteration of only 25 percent.     

可更新数据的数据完整性保护方法

数据收集是移动Agent的一类重要应用,在多个领域的移动Agent应用系统中涉及到数据收集。由于移动Agent可能受到恶意主机攻击,如何保证收集数据的完整性是一个重要的安全问题。文中在分析移动Agent 数据收集的安全性属性的基础上,提出了一个用于保证移动Agent在潜在恶意主机上访问时保护所收集数据的完整性安全协议。该协议能够实现数据的完整性验证与数据被收集的顺序无关,从而可以随机地访问主机,并且同一主机提交的数据可以自己更新,非常适合数据动态变化的应用系统。     

One-to-many data transformations through data mappers

The optimization capabilities of RDBMSs make them attractive for executing data transformations. However, despite the fact that many useful data transformations can be expressed as relational queries, an important class of data transformations that produce several output tuples for a single input tuple cannot be expressed in that way.

To overcome this limitation, we propose to extend Relational Algebra with a new operator named data mapper. In this paper, we formalize the data mapper operator and investigate some of its properties. We then propose a set of algebraic rewriting rules that enable the logical optimization of expressions with mappers and prove their correctness. Finally, we experimentally study the proposed optimizations and identify the key factors that influence the optimization gains.     

数据竞争的规制：数据的利用与数据保护的协调

自互联网出现以来,数据保护一直是个难题。当社交媒体网站在数字市场上大展拳脚的那一刻,对用户数据和信息的保护让决策者们不得不保持警惕。在数字经济时代的背景下,数据逐渐成为企业提升竞争力的重要要素,围绕着数据展开的市场竞争越来越多。数字经济时代,企业对数据资源的重视与争夺,将网络平台权利与用户个人信息保护、互联网企业之间有关数据不正当竞争的纠纷和冲突,推上了风口浪尖。因此,如何协调和把握数据的合理利用和保护之间的关系,规制不正当竞争行为,以求在数字经济快速发展的洪流中,占据竞争优势显得尤为重要。文章将通过分析数据的二元性,讨论数据在数字经济时代的价值,并结合反不正当竞争法和实践案例,进一步讨论数据利用和保护的关系。