Privacy Protection for Big Data Linking using the Identity Correlation Approach

Privacy protection for big data linking is discussed here in relation to the Central Statistics Office （CSO）, Ireland＇s, big data linking project titled the ＇Structure of Earnings Survey - Administrative Data Project＇ （SESADP）. The result of the project was the creation of datasets and statistical outputs for the years 2011 to 2014 to meet Eurostat＇s annual earnings statistics requirements and the Structure of Earnings Survey （SES） Regulation. Record linking across the Census and various public sector datasets enabled the necessary information to be acquired to meet the Eurostat earnings requirements. However, the risk of statistical disclosure （i.e. identifying an individual on the dataset） is high unless privacy and confidentiality safe-guards are built into the data matching process. This paper looks at the three methods of linking records on big datasets employed on the SESADP, and how to anonymise the data to protect the identity of the individuals, where potentially disclosive variables exist.

A Mathematical Solution to String Matching for Big Data Linking

This paper describes how data records can be matched across large datasets using a technique called the Identity Correlation Approach （ICA）. The ICA technique is then compared with a string matching exercise. Both the string matching exercise and the ICA technique were employed for a big data project carried out by the CSO. The project was called the SESADP （Structure of Earnings Survey Administrative Data Project） and involved linking the Irish Census dataset 2011 to a large Public Sector Dataset. The ICA technique provides a mathematical tool to link the datasets and the matching rate for an exact match can be calculated before the matching process begins. Based on the number of variables and the size of the population, the matching rate is calculated in the ICA approach from the MRUI （Matching Rate for Unique Identifier） formula, and false positives are eliminated. No string matching is used in the ICA, therefore names are not required on the dataset, making the data more secure ＆ ensuring confidentiality. The SESADP Project was highly successful using the ICA technique. A comparison of the results using a string matching exercise for the SESADP and the ICA are discussed here.

基于BIM和Linked Data的建筑业电子商务信息融合框架

建筑业电子商务平台信息存在海量、异构和分散等问题,影响了建筑业电子商务的发展。在分析现有电子商务平台信息特征,以及研究BIM和Linked Data技术在信息集成方面应用的基础上,提出一种基于BIM和Linked Data的建筑业电子商务信息融合框架。该框架以BIM作为商品信息模型;使用Linked Data将供应商信息、客户信息、配送信息、交易信息、采购合同信息关联到商品信息BIM模型中,形成融合的信息环境,为实现建筑业电子商务信息融合提供了一种有效的解决思路。

基于Linked Data技术的公安监控系统技术研究

信息化对传统的公安系统情报系统提出了前所未有的挑战,公安系统信息化是公安情报系统升级改造的重要工作。警用语义网情报系统对公安的情报信息的提取和共享等方面有很好的支持。运用基于Linked Data技术的语义网,对公安的重点人员监控系统进行研究分析,提出监控系统的工作流程。

基于Open Linked Data的中西医关联发现云平台

提出了一个用于中西医关联发现的云平台—BioTCM Cloud。该平台是构建在大量的开放链接数据(Linked Data)的基础上,以及跨领域知识整合的需要。面对海量的链接数据,提出了基于MapReduce框架的分布式语义推理框架,用于解决基于领域规则的知识推理问题。以中医草药为案例,分布式语义推埋可以建立中医药和西医之间的关联,以促进中西医之间的沟通和数据共享。

基于Geo Linked Data的地理框架数据描述与发布

随着Web化地理信息共享平台成为GIS领域信息服务的主流形式，对来自不同数据源的地理信息进行深层共享与集成已经成为一个重要的问题。地理语义网技术通过结构化数据描述及发布技术，为异构地理空间数据提供了一种语义集成的方式。本文通过介绍基础地理框架数据的GeoLinkedData化过程．描述了整个发布及应用过程的相关流程和技术。

Linked Data数据集的主题模型建立方法

提出了建立Linked Data数据集主题模型的方法.首先,将数据集中的RDF陈述三元组转换成主谓宾结构的语句,从而将Linked Data数据集转化为文本文档;然后,使用LDA算法对所有数据集的文本文档进行主题建模,即可得到每个数据集的主题向量,该向量就是描述数据集内容主题的特征.在Linked Data数据集链接目标推荐问题上,引入数据集的主题特征进行实验.使用数据集主题向量的余弦相似度替换基于记忆的协同过滤推荐算法中的相似度计算模块.结果表明,推荐效果比原始的协同过滤算法有很大提升.

开放关联数据赋能书目数据的实践指南--评Linked Open Data Enabled Bibliographical Data(LODE-BD)3.0

[目的/意义]评价Linked Open Data Enabled Bibliographical Data(LODE-BD)3.0一书在开放关联数据赋能书目数据方面做出的学术贡献,帮助读者掌握开放关联数据的应用技能。[方法/过程]阐述开放关联数据应用指南的编撰目的,理解LODE-BD的实践建议,思考如何将书目数据表示为开放关联数据,帮助用户开放获取相关的书目资源,实现书目资源的互联互通。[结果/结论]该书是一本成熟的,关于如何选择合适编码策略来生成开放关联数据赋能的书目数据的操作指南,具有丰富的理论价值、方法指导与实践意义。

BioPW+:基于Linked Data的生物途径数据可视化系统

自Linked Data项目被提出以来,大量的开放关联数据被发布到语义Web上,这其中就包含了许多的生物途径数据集。为了使生物学家能够有效地利用这些开放的数据集,对基于Linked Data的生物途径数据可视化系统进行研究,提出了生物途径可视化模型和展示布局方案,并且采用标识符动态映射实现了多源生物途径数据的浏览,最终开发了基于Linked Data的生物途径数据查询可视化系统——BioPW+。该系统应用语义Web技术,依靠SPARQL查询来定位生物途径的基本信息,然后基于Open PHACTS平台获取生物途径元素的详细信息,最终Web界面采用力导向图布局、Sankey图布局对生物途径数据进行展示并提供多种交互操作。与已有的仅仅基于某一特定数据库的生物途径工具相比,BioPW+系统基于Linked Data,可以同时一次性展示多个数据集中的生物途径数据及与其相关的其他生物化学数据,极大节省了时间并增强了数据的完整性。

LinkMF:结合Linked Data的协同过滤推荐算法

协同过滤(CF)是推荐系统中应用最为广泛的推荐算法之一,然而数据稀疏性和冷启动问题是协同过滤方法的两个主要挑战。由于Linked Data整合了关于实体的丰富且结构化的特征,可以作为额外的信息源来缓解以上两种挑战。该文中我们首次提出了结合Linked Data改进CF推荐算法,基于矩阵分解提出了一种新的CF模型——LinkMF,在保证推荐准确度的基础上利用Linked Data缓解数据稀疏性和冷启动问题。首先,我们从Linked Data中抽取项目的特征表示并为项目建模;然后提出新的相似度度量方法计算项目相似度;最后利用项目相似度约束和指导MF分解过程产生推荐。在MovielLens和YAGO标准数据集上的大量实验结果表明,LinkMF优于现有的一些CF方法,特别在缓解数据稀疏性和冷启动问题上取得很好地效果。

Energy-Efficient Data Collection over Underwater MI-Assisted Acoustic Cooperative MIMO WSNs

Underwater magnetic induction(MI)-assisted acoustic cooperative multiple-input-multipleoutput(MIMO) has been recently proposed as a promising technique for underwater wireless sensor networks(UWSNs).For the more,the energy utilization of energy-constrained sensor nodes is one of the key issues in UWSNs,and it relates to the network lifetime.In this paper,we present an energy-efficient data collection for underwater MI-assisted acoustic cooperative MIMO wireless sensor networks(WSNs),including the formation of cooperative MIMO and relay link establishment.Firstly,the cooperative MIMO is formed by considering its expected transmission range and the energy balance of nodes with it.Particularly,from the perspective of the node’s energy consumption,the expected cooperative MIMO size and the selection of master node(MN) are proposed.Sequentially,to improve the coverage of the networks and prolong the network lifetime,relay links are established by relay selection algorithm that using matching theory.Finally,the simulation results show that the proposed data collection improves its efficiency,reduces the energy consumption of the master node,improves the networks’ coverage,and extends the network lifetime.

Deployment Strategy for Multiple Controllers Based on the Aviation On-Board Software-Defined Data Link Network

In light of the escalating demand and intricacy of services in contemporary terrestrial,maritime,and aerial combat operations,there is a compelling need for enhanced service quality and efficiency in airborne cluster communication networks.Software-Defined Networking(SDN)proffers a viable solution for the multifaceted task of cooperative communication transmission and management across different operational domains within complex combat contexts,due to its intrinsic ability to flexibly allocate and centrally administer network resources.This study pivots around the optimization of SDN controller deployment within airborne data link clusters.A collaborative multi-controller architecture predicated on airborne data link clusters is thus proposed.Within this architectural framework,the controller deployment issue is reframed as a two-fold problem:subdomain partition-ing and central interaction node selection.We advocate a subdomain segmentation approach grounded in node value ranking(NDVR)and a central interaction node selection methodology predicated on an enhanced Artificial Fish Swarm Algorithm(AFSA).The advanced NDVR-AFSA(Node value ranking-Improved artificial fish swarm algorithm)algorithm makes use of a chaos algorithm for population initialization,boosting population diversity and circumventing premature algorithm convergence.By the integration of adaptive strategies and incorporation of the genetic algorithm’s crossover and mutation operations,the algorithm’s search range adaptability is enhanced,thereby increasing the possibility of obtaining globally optimal solutions,while concurrently augmenting cluster reliability.The simulation results verify the advantages of the NDVR-IAFSA algorithm,achieve a better load balancing effect,improve the reliability of aviation data link cluster,and significantly reduce the average propagation delay and disconnection rate,respectively,by 12.8%and 11.7%.This shows that the optimization scheme has important significance in practical application,and can meet the high requirements of modern sea,land,and air operations to aviation airborne communication networks.

FAIR + FIT: Guiding Principles and Functional Metrics for Linked Open Data(LOD) KOS Products

Purpose:To develop a set of metrics and identify criteria for assessing the functionality of LOD KOS products while providing common guiding principles that can be used by LOD KOS producers and users to maximize the functions and usages of LOD KOS products.Design/methodology/approach:Data collection and analysis were conducted at three time periods in 2015–16,2017 and 2019.The sample data used in the comprehensive data analysis comprises all datasets tagged as types of KOS in the Datahub and extracted through their respective SPARQL endpoints.A comparative study of the LOD KOS collected from terminology services Linked Open Vocabularies(LOV)and BioPortal was also performed.Findings:The study proposes a set of Functional,Impactful and Transformable(FIT)metrics for LOD KOS as value vocabularies.The FAIR principles,with additional recommendations,are presented for LOD KOS as open data.Research limitations:The metrics need to be further tested and aligned with the best practices and international standards of both open data and various types of KOS.Practical implications:Assessment performed with FAIR and FIT metrics support the creation and delivery of user-friendly,discoverable and interoperable LOD KOS datasets which can be used for innovative applications,act as a knowledge base,become a foundation of semantic analysis and entity extractions and enhance research in science and the humanities.Originality/value:Our research provides best practice guidelines for LOD KOS as value vocabularies.

个人征信行业的创新方向——韩国MyData行业与征信应用

个人征信体系作为消费经济的基础设施,在数字经济时代的地位越来越重要。传统个人征信模式面临新的数字经济形态、科技创新、个人数据严监管以及普惠金融的冲击,需要与时俱进。在韩国,“本人数据管理”(MyData)模式的创新尝试给个人征信带来了创新方向,有助于解决国内征信数据断直连监管。根据MyData模式的基本理念、发展路径和实践案例,从征信行业发展、数据合规和征信业务推进等方面总结启示。

Linked Data Based Framework for Tourism Decision Support System: Case Study of Chinese Tourists in Switzerland

Switzerland is one of the most desirable European destinations for Chinese tourists;therefore, a better understanding of Chinese tourists is essential for successful business practices. In China, the largest and leading social media platform—Sina Weibo, a hybrid of Twitter and Facebook—has more than 600 million users. Weibo’s great market penetration suggests that tourism operators and markets need to understand how to build effective and sustainable communications on Chinese social media platforms. In order to offer a better decision support platform to tourism destination managers as well as Chinese tourists, we proposed a framework using linked data on Sina Weibo. Linked Data is a term referring to using the Internet to connect related data. We will show how it can be used and how ontology can be designed to include the users’ context (e.g., GPS locations). Our framework will provide a good theoretical foundation for further understand Chinese tourists’ expectation, experiences, behaviors and new trends in Switzerland.

BioBroker: Knowledge Discovery Framework for Heterogeneous Biomedical Ontologies and Data

A large number of ontologies have been introduced by the biomedical community in recent years. Knowledge discovery for entity identification from ontology has become an important research area, and it is always interesting to discovery how associations are established to connect concepts in a single ontology or across multiple ontologies. However, due to the exponential growth of biomedical big data and their complicated associations, it becomes very challenging to detect key associations among entities in an inefficient dynamic manner. Therefore, there exists a gap between the increasing needs for association detection and large volume of biomedical ontologies. In this paper, to bridge this gap, we presented a knowledge discovery framework, the BioBroker, for grouping entities to facilitate the process of biomedical knowledge discovery in an intelligent way. Specifically, we developed an innovative knowledge discovery algorithm that combines a graph clustering method and an indexing technique to discovery knowledge patterns over a set of interlinked data sources in an efficient way. We have demonstrated capabilities of the BioBroker for query execution with a use case study on a subset of the Bio2RDF life science linked data.

Linked Data-based Slide Repository： The Episodic Slide Retrieval Using the Episodic Keyword Networks

This paper focuses on developing a system that allows presentation authors to effectively retrieve presentation slides for reuse from a large volume of existing presentation materials. We assume episodic memories of the authors can be used as contextual keywords in query expressions to efficiently dig out the expected slides for reuse rather than using only the part-of-slide-descriptions-based keyword queries. As a system, a new slide repository is proposed, composed of slide material collections, slide content data and pieces of information from authors＇ episodic memories related to each slide and presentation together with a slide retrieval application enabling authors to use the episodic memories as part of queries. The result of our experiment shows that the episodic memory-used queries can give more discoverability than the keyword-based queries. Additionally, an improvement model is discussed on the slide retrieval for further slide-finding efficiency by expanding the episodic memories model in the repository taking in the links with the author-and-slide-related data and events having been post on the private and social media sites.

The Method of Data Access for Nuclear Instrument Based on Linked List

A new method of data access which can effectively resolve the problem of high speed and real time reading data of nuclear instrument in small storage space is introduced. This method applies the data storage mode of “linked list” to the system of Micro Control Unit (MCU), and realizes the pointer access of nuclear data on the small storage space of MCU. Experimental results show that this method can solve some problems of traditional data storage method, which has the advantages of simple program design, stable performance, accurate data, strong repeatability, saving storage space and so on.

Studies on Novel Anti-jamming Technique of Unmanned Aerial Vehicle Data Link

Based on the M-ary spread spectrum （M-ary-SS）, direct sequence spread spectrum （DS-SS）, and orthogonal frequency division multiplex （OFDM）, a novel anti-jamming scheme, named orthogonal code time division multi-subchannels spread spectrum modulation （OC-TDMSCSSM）, is proposed to enhance the anti-jamming ability of the unmanned aerial vehicle （UAV） data link. The anti-jamming system with its mathematical model is presented first, and then the signal formats of transmitter and receiver are derived. The receiver＇s bit error rate （BER） is demonstrated and anti-jamming performance analysis is carded out in an additive white Ganssian noise （AWGN） channel. Theoretical research and simulation results show the anti-jamming performance of the proposed scheme better than that of the hybrid direct sequence frequency hopping spread spectrum （DS/FH SS） system. The jamming margin of the OC-TDMSCSSM system is 5 dB higher than that of DS/FH SS system under the condition of Rician channel and full-band jamming, and 6 dB higher under the condition of Rician channel environment and partial-band jamming.

RDF与MicroData在关联数据语义网中互操作技术应用研究

探讨了当前关联数据中描述数据的方法及关联数据中RDF后端语义数据模型与MicroData前端语义模型的描述规则.实现了MicroData数据与RDF转换的通用规则设计,使用该规则实现了MicroData与RDF数据的映射,最后完成了基于Drupal的MicroData数据与RDF的转换.