农业科技多维语义关联数据构建研究
|
摘要
人类社会正以惊人速度产生海量数据，信息总量每18个月就会翻一番，“大数据”时代已经来临，以数据密集型计算为特征的科学研究“第四范式”方兴为艾。在“信息泛滥、知识匮乏”的背景下，科研人员面对日益复杂的科研问题，对个性化、关联化、集成化精品信息资源，以及嵌入科研过程的深层次知识服务需求更为迫切。
通过引入关联数据的理念和方法，本文基于国家农业图书馆和农业科学数据共享平台中各类数据资源，开展了农业科技多维语义关联数据构建方法和关键技术研究，并选取“水稻”领域进行实证研究，设计并实现基于关联数据驱动的领域知识服务原型系统。开展的主要工作及取得成果包括：
（1）调研了国内外最新研究进展，分析了关联数据与数据网络、语义网和知识组织系统等概念的区别与联系，对关联数据进行了分类，深入调研了关联数据的构建流程、语义关联描述模型、构建工具和关联关系构建方法。
（2）应用简单知识组织系统SKOS，将农业科学叙词表CAT进行了规范语义描述，并与AGROVOC、NALT等几大涉农知识组织体系建立了映射，自主开发了批量转换工具将CAT转换为CAT/SKOS关联数据。
（3）在深入分析国家农业图书馆科技文献资源特点基础上，综合应用DCMI、BIBO等本体，对其进行了规范化描述和语义关联模型构建，自主开发了文献自动标引工具，将CAT/SKOS规范概念植入各类文献，基于开源工具D2R实现了农业科技文献语义关联数据构建。
（4）继承复用SWRC、VIVO、FOAF等本体，将农业科学数据共享中心700多个数据库集，以及农业科技机构、科技人员和科研项目等专题数据库进行了规范化语义描述，构建了覆盖科学数据、科技文献和叙词表的多维语义关联模型，构建了轻量级的农业科技多维语义关联数据网络，创建RDF三元组超过300万个。
（5）设计了关联数据驱动的领域知识服务系统体系架构和功能模块，通过集成SPARQL、Virtuoso等关键技术，开发了水稻领域知识服务原型系统，实现了领域知识的集成浏览和关联发现、动态分面导航与检索、SPARQL终端查询、HTTP URI参引解析和RDF内容下载等功能。
研究表明，引入关联数据的理念和技术方法，是实现海量农业科技信息资源精细化揭示、规范化描述、语义化组织和深度整合的最佳实践，对提高农业信息资源的可知性、可见性、可获得性将起到重要作用。基于关联数据来设计和开发新型知识服务功能，可进一步拓展知识服务途径，对促进农业科研创新有着重要研究价值和实践意义。本文在农业科技多维语义关联模型和关联数据驱动的领域知识服务系统构建方面都具有一定创新性。
The “Big Data” age is arriving as for the human beings are creating huge amount of data everyday,and the total volume of data would be doubled every18months.The “fourth paradigm” of discoverybased on data-intensive science emerging rapidly.However, the existing information organization andinformation service means is difficult to adapt to changes in agricultural research environment anddevelopment trend, and the researchers are often drowning in information, but starved forknowledge.They are looking for domain high qality information resources which are well organizedspecially, linked and merged, and depth-knowledge service means embed into their process ofagricultural research and innovation.
The idea and methodologies of Linked Data have been adopted in this paper, the key technologyand approaches of the construction of agricultural sci-tech semantic linked data have benn studied, andthe multidimensional semantic linking model has been designed.The semantic linked open data basedon part of the literature resources of China National Agricultural Library and also some scientific datafrom the National Agricultural Scientific Data Sharing Platform have been constructed andpublished.Finally, a prototype knowledge service system completely driven by the semantic linked datahas been designed and realized in the selected “rice” domain.
The main research work and results of this paper are concluded as following:
（1） The latest research and practices progress of Linked Data home and abroad have beeninvestigated, the difference and relation between the Linked Data and the Web of Data, Semantic Weband Knowledge Organization System was analyzed, and the classification of linked data, thetechnological process, semantic link descriptive model, automatic tools have also been studied.
（2） Concepts and semantic relationships within the Chinese Agricultural Thesaurus (CAT) havebeen formally described using the elements of Simple Knowledge Organization System (SKOS).Aconversion tool has been developed, and successfully converted the whole contents of CAT and itsmapping results with other knowledge organization systems related with agricultrure such asAGROVOC, NALT, etc., into the linked data version namely CAT/SKOS.
（3） Main classes and properties have been abstracted from the literature resources of ChinaNational Agricultural Library.The widely used vocabularies and ontologies such as DCMI, BIBO,etc.have been reused to formally describe and model these classes, properties and semanticrelationships.An automatic indexing tool has also been developed to embed the concepts and links ofCAT/SKOS into these literatures.The semantic linked data of agricultural literatures have beenconstructed and published based on the open source software D2R Server.
（4） Core metadatas of over700datasets and some particular databases hold the data about theinstitutes, researchers and projects of agricultural have been modeled by reusing the well knownvocabularies or ontologies (e.g.VIVO, SWRC, FOAF).The multidimensional semantic linking modelcovering the scientific data, literatures, and thesaurus has been designed.And based on this model, the expected multidimensional semantic linked data of agricultural sci-tech has been created and published.
（5） The architecture and function models of domain knowledge service system have beendesigned, which based on linked data.A prototype system was realized based on some key technologiessuch as SPARQL, Virtuoso and so forth.Some import service functions have been provide in this system,such as integrated browseing and discovery of domain knowledge, dynamic facet navigation andsearching, SPARQL query endpoint, HTTP URI dereferencing, downloading RDF triples.
In conclusion, this study proves that it is the best practice to applying the ideas, principles andmethodologies of linked data, to describe, organize and merge the huge amount of agriculturalinformation resources in a more fine described, formally structured and semantically linked way.Linkeddata would play a great role to increase the popularity, visibility, accessibility and value of agriculturalinformation resources.This research would be meaningful to explore new ways and patterns to organize,integrate and make good use of huge agricultural information resources, and promote the innovation ofagricultural science and technology. This study would be innovative at the aspects of construction ofmultidimensional semantic linking model and the prototype system completely based on the linked data.
通过引入关联数据的理念和方法，本文基于国家农业图书馆和农业科学数据共享平台中各类数据资源，开展了农业科技多维语义关联数据构建方法和关键技术研究，并选取“水稻”领域进行实证研究，设计并实现基于关联数据驱动的领域知识服务原型系统。开展的主要工作及取得成果包括：
（1）调研了国内外最新研究进展，分析了关联数据与数据网络、语义网和知识组织系统等概念的区别与联系，对关联数据进行了分类，深入调研了关联数据的构建流程、语义关联描述模型、构建工具和关联关系构建方法。
（2）应用简单知识组织系统SKOS，将农业科学叙词表CAT进行了规范语义描述，并与AGROVOC、NALT等几大涉农知识组织体系建立了映射，自主开发了批量转换工具将CAT转换为CAT/SKOS关联数据。
（3）在深入分析国家农业图书馆科技文献资源特点基础上，综合应用DCMI、BIBO等本体，对其进行了规范化描述和语义关联模型构建，自主开发了文献自动标引工具，将CAT/SKOS规范概念植入各类文献，基于开源工具D2R实现了农业科技文献语义关联数据构建。
（4）继承复用SWRC、VIVO、FOAF等本体，将农业科学数据共享中心700多个数据库集，以及农业科技机构、科技人员和科研项目等专题数据库进行了规范化语义描述，构建了覆盖科学数据、科技文献和叙词表的多维语义关联模型，构建了轻量级的农业科技多维语义关联数据网络，创建RDF三元组超过300万个。
（5）设计了关联数据驱动的领域知识服务系统体系架构和功能模块，通过集成SPARQL、Virtuoso等关键技术，开发了水稻领域知识服务原型系统，实现了领域知识的集成浏览和关联发现、动态分面导航与检索、SPARQL终端查询、HTTP URI参引解析和RDF内容下载等功能。
研究表明，引入关联数据的理念和技术方法，是实现海量农业科技信息资源精细化揭示、规范化描述、语义化组织和深度整合的最佳实践，对提高农业信息资源的可知性、可见性、可获得性将起到重要作用。基于关联数据来设计和开发新型知识服务功能，可进一步拓展知识服务途径，对促进农业科研创新有着重要研究价值和实践意义。本文在农业科技多维语义关联模型和关联数据驱动的领域知识服务系统构建方面都具有一定创新性。
The “Big Data” age is arriving as for the human beings are creating huge amount of data everyday,and the total volume of data would be doubled every18months.The “fourth paradigm” of discoverybased on data-intensive science emerging rapidly.However, the existing information organization andinformation service means is difficult to adapt to changes in agricultural research environment anddevelopment trend, and the researchers are often drowning in information, but starved forknowledge.They are looking for domain high qality information resources which are well organizedspecially, linked and merged, and depth-knowledge service means embed into their process ofagricultural research and innovation.
The idea and methodologies of Linked Data have been adopted in this paper, the key technologyand approaches of the construction of agricultural sci-tech semantic linked data have benn studied, andthe multidimensional semantic linking model has been designed.The semantic linked open data basedon part of the literature resources of China National Agricultural Library and also some scientific datafrom the National Agricultural Scientific Data Sharing Platform have been constructed andpublished.Finally, a prototype knowledge service system completely driven by the semantic linked datahas been designed and realized in the selected “rice” domain.
The main research work and results of this paper are concluded as following:
（1） The latest research and practices progress of Linked Data home and abroad have beeninvestigated, the difference and relation between the Linked Data and the Web of Data, Semantic Weband Knowledge Organization System was analyzed, and the classification of linked data, thetechnological process, semantic link descriptive model, automatic tools have also been studied.
（2） Concepts and semantic relationships within the Chinese Agricultural Thesaurus (CAT) havebeen formally described using the elements of Simple Knowledge Organization System (SKOS).Aconversion tool has been developed, and successfully converted the whole contents of CAT and itsmapping results with other knowledge organization systems related with agricultrure such asAGROVOC, NALT, etc., into the linked data version namely CAT/SKOS.
（3） Main classes and properties have been abstracted from the literature resources of ChinaNational Agricultural Library.The widely used vocabularies and ontologies such as DCMI, BIBO,etc.have been reused to formally describe and model these classes, properties and semanticrelationships.An automatic indexing tool has also been developed to embed the concepts and links ofCAT/SKOS into these literatures.The semantic linked data of agricultural literatures have beenconstructed and published based on the open source software D2R Server.
（4） Core metadatas of over700datasets and some particular databases hold the data about theinstitutes, researchers and projects of agricultural have been modeled by reusing the well knownvocabularies or ontologies (e.g.VIVO, SWRC, FOAF).The multidimensional semantic linking modelcovering the scientific data, literatures, and thesaurus has been designed.And based on this model, the expected multidimensional semantic linked data of agricultural sci-tech has been created and published.
（5） The architecture and function models of domain knowledge service system have beendesigned, which based on linked data.A prototype system was realized based on some key technologiessuch as SPARQL, Virtuoso and so forth.Some import service functions have been provide in this system,such as integrated browseing and discovery of domain knowledge, dynamic facet navigation andsearching, SPARQL query endpoint, HTTP URI dereferencing, downloading RDF triples.
In conclusion, this study proves that it is the best practice to applying the ideas, principles andmethodologies of linked data, to describe, organize and merge the huge amount of agriculturalinformation resources in a more fine described, formally structured and semantically linked way.Linkeddata would play a great role to increase the popularity, visibility, accessibility and value of agriculturalinformation resources.This research would be meaningful to explore new ways and patterns to organize,integrate and make good use of huge agricultural information resources, and promote the innovation ofagricultural science and technology. This study would be innovative at the aspects of construction ofmultidimensional semantic linking model and the prototype system completely based on the linked data.
引文
1.白海燕,梁冰.利用D2R实现关系数据库与关联数据的语义模式映射[J].现代图书情报技术,2011,(7/8):1-7.
2.白海燕,乔晓东.基于本体和关联数据的书目组织语义化研究[J].现代图书情报技术,2010,（9）:18-27.
3.白海燕,朱礼军.关联数据的自动关联构建研究[J].现代图书情报技术,2010,（2）:44-49.
4.白海燕.从关联数据的应用场景看信息服务发展的新动向[J].数字图书馆论坛,2012,(6):59-67.
5.白海燕.关联数据及DBpedia实例分析[J].现代图书情报技术,2010,（3）:33-39.
6.常春. Ontology在农业信息管理中的构建和转化.北京:中国农业科学院研究生院,2004.
7.朝乐门,张勇,邢春晓.面向开放关联数据的知识地图研究[J].图书情报工作,2012,56(10):17-24.
8.陈定权,肖鹏.关联数据会议文献研究述评[J].图书情报知识,2012,(3):103-110
9.陈彦.应用SPARQL进行RDF数据查询[J].企业技术开发（学术版）,2007,26(7):6-10.
10.邓兰兰,李春旺.Web数据关联创建策略研究[J].现代图书情报技术,2011,(5):1-6.
11.范炜,邹庆．词表资源关联化[J].情报理论与实践,2010,(5):21-25.
12.付旭雄.基于关联数据的知识地图中知识链接构建研究[D].武汉：华中师范大学,2012.
13.国家农业科学数据共享中心-农业科技机构数据库.(2005-08-01)[2013-03-20]. http://stb.agridata.cn/module_db/index_new.asp?rid=A030106&start=5&bs=&url=.
14.国家农业科学数据共享中心-农业科技人才数据库.(2005-08-01)[2013-03-20]. http://stb.agridata.cn/module_db/index_new.asp?rid=A030105&start=5&bs=&url=.
15.国家农业科学数据共享中心-国内农业在研项目数据库.(2005-08-01)[2013-03-20]. http://stb.agridata.cn/module_db/index_new.asp?rid=A030103&start=5&bs=&url=.
16.管进.基于关联数据的图书馆知识服务策略研究[J].图书馆理论与实践,2012,(6):9-11.
17.郭少友. OAI-PMH元数据的关联数据化方法研究[J].图书情报工作,2011,55(2):107-111.
18.郭少友.关联数据的动态链接维护研究[J].图书情报工作,2011,55(17)112-116.
19.胡莲香.国内关于图书馆应用关联数据研究综述与展望[J].农业网络信息,2012,(3):8-12.
20.黄鼎成,郭增艳.科学数据共享管理研究[M].北京:中国科学技术出版社,2002.
21.黄金霞.支持科研和学术发现的语义网应用实例研究[J].图书情报工作,2011,(11):125-129.
22.黄永文,岳笑,刘建华.关联数据应用的体系框架及构建关联数据应用的建议[J].现代图书情报技术,2011(9):7-13.
23.黄永文.关联数据驱动的Web应用研究[J].图书馆杂志.2010,29(7):55-59.
24.黄永文.关联数据在图书馆中的应用研究综述[J].现代图书情报技术,2010,（5）:1-7.
25.金海,袁平鹏.语义网数据管理技术及应用[M].北京:科学出版社,2010.
26.寇远涛.面向学科领域的科研信息环境建设研究[D].北京:中国农业科学院研究生院,2012.
27.郎杨琴,孔丽华.科学研究的第四范式——吉姆·格雷的报告”e-Science:一种科研模式的变革”简介[J].科研信息化技术与应用,2010,1(2):92-94.
28.李国杰.大数据研究的科学价值[J].中国计算机学会通讯,2012,8(9):8-15
29.李琳.关联数据在图书馆界的应用与挑战[J].图书与情报,2011(4):58-61.
30.李晓辉.图书馆科研数据管理与服务模式探讨[J].中国图书馆学报,2011,37(5):46-52.
31.李亚婷,曹洁,彭洋等. Web环境下关联数据的应用[J].情报理论与实践,2010,122-125.
32.林海青,楼向英,夏翠娟.图书馆关联数据:机会与挑战[J].中国图书馆学报,2012,38(197):58-67,112.
33.刘丽斌,张寿华,濮德敏等.《中国分类主题词表》的SKOS描述自动转换研究［J］.中国图书馆学报,2009,35(6):56-60.
34.刘炜,胡小菁,钱国富等. RDA与关联数据[J].中国图书馆学报，2012，(1)：34—42.
35.刘炜.关联数据:概念、技术及应用展望[J].大学图书馆学报,2011,(2):5-12.
36.娄秀明.用关联数据技术实现网络知识组织系统的研究[D].上海:华东师范大学.2010.
37.马费成,赵红斌,万燕玲等.基于关联数据的网络信息资源集成[J].情报杂志,2011,30(2):167-170,175.
38.马静,马春娥.如何利用D2R发布Linked data[EB/OL].(2010-03-25)[2012-05-22].http://www.ibm.com/developerworks/cn/web/1003_zhangjing_d2r.
39.马张华.信息组织（第二版）.北京:清华大学出版社,2003.
40.孟宪学等.农业科学数据核心元数据[M].北京:中国农业科学技术出版社,2008.
41.欧石燕.面向关联数据的语义数字图书馆资源描述与组织框架设计与实现[J].中国图书馆学报,2012,(6):58-71.
42.沈芸芸,冯英,刘秀文. DC元数据年度进展（2010）[J].数字图书馆论坛,2010,12:40-45.
43.沈志宏,刘筱敏,郭学兵等.关联数据发布流程与关键问题研究——以科技文献、科学数据的发布为例[J].中国图书馆学报,2012(2012):http://www.cnki.net/kcms/detail/11.2746. G2.20121105.2336.001.html
44.沈志宏,张晓林.关联数据及其应用现状综述[J].现代图书情报技术,2010(11):1-9.
45.孙鸿燕．图书馆关联数据的综合管理及其实现[J]．图书馆学研究，2011，(12):51-54,5.
46.谭洁清.关联数据的简介与进展[J].信息与电脑,2011(1):103,106.
47.汤怡洁,杨锐,刘毅.关联数据工具比较分析[J].现代图书情报技术,2011(增):*
48.陶俊,孙坦.基于Linked Data的RDF关联框架综析[J].现代图书情报技术,2011,27(12):1-8.
49.王军,张丽.网络知识组织系统的研究现状和发展趋势.中国图书馆学报,2008,34(1):65-69.
50.王珊,陈红.数据库系统原理教程[M].第1版.北京:清华大学出版社,1998.
51.王思丽,马建霞,祝忠明等.语义Web模式下综合科技资源的关联策略研究[J].现代图书情报技术,2011,(6):32-38.
52.王思丽,祝忠明.利用关联数据实现机构知识库的语义扩展研究[J].现代图书情报技术,2011(11):17-23.
53.王涛.基于关联数据的馆藏信息资源聚合研究[J].图书馆学刊,2012(8):44-46.
54.吴玥,李占羽.基于关联数据开放政府数据[J].电脑知识与技术,2010,6(31):8688-8691.
55.夏翠娟,刘炜等.关联数据发布技术及其实现——以Drupal为例[J].中国图书馆学报,2012,(1):49-57
56.鲜国建,孟宪学,常春.农业科学叙词表的OWL表示研究.中国农业科学,2007,42(增刊2):91～95
57.鲜国建,孟宪学,常春.基于农业本体的智能检索原型系统设计与实现.中国农学通报,2008,24(6):470-474.
58.熊太纯.基于SKOS的网络信息资源主题标引[J].图书馆学研究,2009(7):63-66.
59.徐华,曾微泊,王旭东.关联数据：图书馆学研究的新领域[J].南华大学学报,2011,12(6):107-109.
60.徐华.关联数据在国外图书馆中的应用及其借鉴意义[J].图书馆学研究,2011,(8):87-89.
61.徐雷. SPARQL查询优化[J],现代图书情报技术,2012,(10):42-48.
62.游毅,成全.基于关联数据的科研数据资源共享[J].情报杂志,2012,31(10):146-151.
63.喻非.《中国分类主题词表》网络化研究:从MARC到SKOS［C］.网络环境下信息组织的创新与发展:全国第五次情报检索语言发展方向研讨会论文集.北京:国家图书馆出版社,2009:139-147.
64.张继东,尹群.简单知识组织系统SKOS及其应用研究[J].现代情报,2008,28(11):20-25.
65.张继东,余以胜.利用叙词表构建本体的方法研究.现代图书情报技术,2006,(12):82-85.
66.张士男,宋文.《科图法》SKOS描述方案设计[J］.现代图书情报技术,2010(6):7-11.
67.张晓林.颠覆数字图书馆的大趋势[J].中国图书馆学报,2011,37(5):4-12.
68.赵瑞雪,寇远涛,鲜国建等.领域科研信息环境构建研究[J].数字图书馆论坛.2012(12):22-27.
69.周国民.农业科学数据共享中心通过国家认定[EB/OL].(2011-12-02)[2013-03-27].http://aii.caas.cn/bsdt/kyjz/551.htm.
70.周晓英.数据密集型科学研究范式的兴起与情报学的应对[J].情报资料工作,2012,(2):5-11.
71. Agricultural Thesaurus and Glossary Home Page [EB/OL].(2013-01-04)[2013-04-9].http://agclass.nal.usda.gov
72. Alexander K, Cyganiak R, Hausenblas M, etal. Describing Linked Datasets-On the Design and Usage of voiD, the“Vocabulary Of Interlinked Datasets”[C]. In: Proceedings of LDOW2009,April20,2009, Madrid, Spain.
73. Archer P, Goedertier S and Loutas N. Study on persistent URIs, with identification of best practices andrecommendations on the topic for the MSs and the EC[ER/OL].(2012-12-17)[2013-05-274].https://joinup.ec.europa.eu/sites/default/files/D7.1.3%20-%20Study%20on%20persistent%20URIs_4.pdf.
74. Auer S, Martin M, Frischmuth P, etal. Facilitation the publication of Open Governmental Data with the LOD2Stack.[EB/OL].[2012-12-17]. http://share-psi.eu/papers/LOD2.pdf
75. Baker T and Keizer J. Linked Data for Fighting Global Hunger: Experiences in setting standards for AgriculturalInformation Management. In: D. Wood (ed.), Linking Enterprise Data,2010:177-201.
76. Barnaghi, P, Presser, M and Moessner, K. Publishing linked sensor data[C]. In: ISWC2010,2010-11-07,Shanghai,China.
77. BBC Linked Data Journey.[EB/OL].(2010-05-27)[2012-12-20]. http://www.slideshare.net/rjw/bbc-linked-data-journey
78. Becker C and Bizer C. DBpedia Mobile: A Location-Enabled Linked Data Browser. In: Proceedings of the1stWorkshop about Linked Data on the Web (LDOW2008).
79. Belhajjame K, Cheney J, Garijo D, etal. The PROV Ontology: Model and Formal Semantics. Technical report2011[EB/OL].(2011-12-13)[2013-03-20]. http://www.w3.org/TR/2011/D-prov-o-20111213
80. Berrueta D, Brickley D, Decker S, etal. SIOC Core Ontology Specification.[EB/OL].(2007-06-12)[2013-03-04].http://rdfs.org/sioc/spec/
81. Bizer C, Cyganiak R and Heath T. How to publish Linked Data on the Web［EB/OL］.(2007-07-20［)2013-03-10］.http://sites.wiwiss.fu-berlin.de/suhl/bizer/pub/LinkedDataTutorial/20070727
82. Bizer C, Heath T and Lee TB. Linked Data-The Story So Far. In: Heath, T, Hepp, M, and Bizer, C (eds.).Special Issue on Linked Data, International Journal on Semantic Web and Information Systems (IJSWIS2009).
83. Bizer C, Heath T, Idehen K, etal. Linked data on the web (LDOW2008) Proceeding of the Seventeenthinternational conference on World Wide Web, Beijing, China.2008. pp.1265–1266.
84. Bizer, C. The Emerging Web of Linked Data[J]. Intelligent Systems, IEEE,2009,24(5):87-92.
85. Bizera C, Lehmannb J, Kobilarova G, etal. DBpedia-A crystallization point for the Web of Data. Web Semantics:Science, Services and Agents on the World Wide Web,2009,7(3):154-165.
86. Brickley D and Miller L. FOAF Vocabulary Specification.[EB/OL].(2010-01-01)[2012-01-03].http://xmlns.com/foaf/spec/20100101.html.
87. Carl L. The oreChem Project: Integrating Chemistry Scholarship with the Semantic Web. In: Proceedings of theWebSci'09: Society On-Line,18-20March2009, Athens, Greece.
88. Cheng G and Qu Y. Searching Linked Objects with Falcons: Approach, Implementation and Evaluation. Int. J.Sem. Web Inf. Sys.2009,5(3),49–70.
89. Codd, EF. A Relational Model of Data for Large Shared Data Banks[J]. Communications of the ACM,1970,13(6):377-387.
90. Collins, J P. The Fourth Paradigm Data-Intensive Scientific Discovery. Science,327,5972(Mar192010),1455-1456.
91. Corlosquet S. How to build Linked Data sites with Drupal7and RDFa.SemTech2010.［EB/OL］.[2012-05-10］.http://www.slideshare.net/scorlosquet/how-to-build-linked-datasites-with-drupal-7-and-rdfa.
92. Corlosquet S. Produce and consume Linked Data with Drupal［EB/OL］.[2012-05-22]. http://openspring.net/sites/openspring.net/files/corl-etal-2009iswc.pdf
93. D2R Server-Publishing Relational Databases on the Semantic Web.[EB/OL].(2010-02-16)[2012-02-15].http://www4.wiwiss.fu-berlin.de/bizer/d2r-server/
94. Data.gov Concept of Operations.[EB/OL].(2011-11-17)[2012-02-23]. http://www.data.gov/documents/data_gov_conops_v1.0.pdf
95. Datasets in the next LOD Cloud.[EB/OL].(2012-01-20)[2012-02-26]. http://www4.wiwiss.fu-berlin.de/lodcloud/
96. DC-2011, the eleventh International Conference on Dublin Core and Metadata Applications.[EB/OL].(2011-09-21)[2011-12-25]. http://dcevents.dublincore.org/index.php/IntConf/dc-2011
97. DCMI Metadata Terms [EB/OL].(2012-06-14)[2013-02-03]. http://dublincore.org/documents/2012/06/14/dcmi-terms/
98. Delbru R, Polleres A, Tummarello G, etal. Context Dependent Reasoning for Semantic Documents in Sindice. In:Proceedings of the4th InternationalWorkshop on Scalable Semantic Web Knowledge Base Systems (SSWS2008)(2008)
99. Dewey Decimal Classification-Linked Data［EB/OL］.(2012-06-12)［2013-03-02］.http://dewey.info
100. Dodds L and Davis I. Linked Data Patterns: A pattern catalogue for modelling, publishing, and consuming LinkedData[EB/OL].(2012-05-31)[2013-03-29]. http://patterns.dataincubator. org/book/linked-data-patterns.pdf
101. Dolan-Gavitt B, Leek T, Zhivich M, etal. Virtuoso: Narrowing the Semantic Gap in Virtual MachineIntrospection[C].Security and Privacy (SP),2011IEEE Symposium Berkeley CA: IEEE,2011:297-312
102. EuroVoc, the EU's multilingual thesaurus[EB/OL].(2012-12-18)[2013-04-09].http://eurovoc. uropa.eu/drupal/
103. FerréS, Hermann A and DucasséM. Semantic faceted search: Safe and expressive navigation in RDF graphs.Research report, IRISA (2011), http://hal.inria.fr/inria-00410959/PDF/PI-1964.pdf
104. FIELDING RT and TAYLOR RN. Principled design of the modern Web architecture[J]. ACM Transactions onInternet Technology,2002,2(2):115-150.
105. Getoor L. Link Mining: A New Data Mining Challenge [J]. Sigkdd Explorations,2003,5(1):84-89.
106. Glimm B. Using SPARQL with RDFS and OWL entailment, In proceedings of7th International Summer Schoolon Reasoning Web: Semantic Technologies for the Web of Data,2011, Lecture Notes in Computer Science, pp.137-201.
107. Golbeck J. Weaving a web of trust. Science.2008,321(5896):1640-1641.
108. Government HM. Putting the Frontline First: Smarter Government.[R/OL].(2009-12-07)[2012-01-06].http://www.hmg.gov.uk/media/52788/smarter-government-final.pdf.AGROVOC Linked Open Data [EB/OL].(2013-03-20)[2013-04-09]. http://aims.fao.org/standards/agrovoc/linked-open-data.
109. Hannemann J and Kett J. Linked Data for Libraries[C]. World Library and Information Congress:76th IFLAGeneral Conference and Assembly,10-15August2010, Gothenburg, Sweden.
110. Hartig O and Zhao J. Publishing and consuming provenance metadata on the web of linked data. In Proceedings ofIPAW2010,2010. https://cs.uwaterloo.ca/~ohartig/files/HartigZhao_Provenance_IPAW2010_Preprint.pdf
111. Haslhofer B and Schandl B. The OAI2LOD Server: Exposing OAI-PMH Metadata as Linked Data[C]. In:Proceedings of LDOW2008, Beijing China.
112. Hausenblas M. Linked Data Applications-The Genesis and the Challenges of Using Linked Data on the Web.[EB/OL].(2009-07-26)[2013-03-26]. http://wtlab.um.ac.ir/parameters/wtlab/filemanager/LD_resources/other/lod-app-tr-2009-07-26_0.pdf
113. Heath T and Bizer C. Linked Data: Evolving the Web into a Global Data Space[M]. Vol.1. Morgan&Claypool,2011,1-136.
114. Heath T and Motta E. Revyu: Linking reviews and ratings into the Web of Data. Web Semantics: Science, Servicesand Agents on the World Wide Web,2008,6(4):266-273.
115. Hey T, Tansler S, Tolle K, editors. The Fourth Paradigm: Data Intensive Scientific Discovery [M]. MicrosoftResearch Publishing,2009.
116. Hitzler P, Krotzsch M and Rudolph S. Foundations of Semantic Web Technologies. Chapman&Hall/CRC,2009.
117. Isaac A and Summers E. SKOS simple knowledge organization system primer.[EB/OL].(2008-2-21)[2012-01-04]. http://www.w3.org/TR/skos-primer/
118. Isele R,Jentzsch A and Bizer C. Silk Server-Adding Missing Links While Consuming Linked Data[C].In:Proceedings of the1st International Workshop on Consuming Linked Data, Shanghai,China,2010.
119. Jentzsch A, Zhao J, Hassanzadeh O, etal. Linking Open Drug Data. Proceedings of the Second TriplificationChallenge2009, Graz, Austria.2009
120. LC Linked Data Service (Library of Congress)[EB/OL].(2012-12-18)[2013-04-09]. http://id.loc.gov/
121. Lee TB, Chen Y, Chilton L, etal. Tabulator: exploring and analyzing Linked Data on the Semantic Web.Proceedings of the Third International Semantic Web User Interaction Workshop, Athens, Georgia, USA.2006.
122. Lee TB. Linked Data-Design Issues.[EB/OL].(2006-07-27)[2012-10-11]. http://www.w3.org/DesignIssues/LinkedData.html
123. Lee TB. Semantic Web-XML2000.[EB/OL].(2000-12-06)[2012-10-21]. http://www.w3.org/2000/Talks/1206-xml2k-tbl/Overview.html
124. Levenshtein V I. Binary Codes Capable of Correcting Deletions, Insertions and Reversals [J]. Doklady AkademiiNauk SSSR,1965,163(4):845-848.
125. Liang A, Sini M, Chang C, etal.(2006):The Mapping Schema from Chinese Agricultural Thesaurus toAGROVOC; New review of hypermedia and multimedia, vol.12, no1, pp.51-62, fromhttp://www.fao.org/docrep/008/af241e/af241e00.htm#Contents.
126. Linked data at OCLC [EB/OL].[2013-02-27]. http://www.oclc.org/data.htm1.
127. Linking Open Data.[EB/OL].(2012-01-19)[2013-02-16]. http://www.w3.org/wiki/SweoIG/TaskForces/CommunityProjects/LinkingOpenData
128. Lucene-SKOS-A SKOS Analyzer Module for Apache Lucene and Solr [EB/OL].[2012-07-20].https://github.com/behas/lucene-SKOS
129. Maali F, Cyganiak R and Peristeras V. Re-using Cool URIs: Entity Reconciliation Against LOD Hubs [C].Proceedings of LDOW2011, March29,2011, Hyderabad, India.
130. Malmsten M.将图书馆目录纳入语义万维网.李静雯译.现代图书情报技术,2009,3(3):2-8.
131. Manyika J, Chui M, Brown B, etal. Big data: The next frontier for innovation, competition, andproductivity[EB/OL].(2011-05-01)[2013-04-12]. http://www.mckinsey.com/insights/business_technology/big_data_the_next_frontier_for_innovation
132. Melanon B. Bringing Linked Data to Drupal;bringing the Semantic Web to theworld[EB/OL].(2008-10-15)[2012-05-22]. http://data.agaric.com/node/2700.
133. Melanon B. RDF's long lineage in Drupal.[EB/OL].(2008-09-21)[2012-05-22]. http://data.agaric.com/rdfs-long-lineage-drupal.
134. Momtchev V, Peychev D, Primov T, etal. Expanding the pathway and interaction knowledge in linked life data[C].In Proceedings of International Semantic Web Challenge,2009.
135. Myers J. Semantic Web and Linked Data “Coming of Age”.[EB/OL].(2010-07-20)[2012-12-22].http://www.slideshare.net/jaymmyers/semtech-maine.
136. Ngomo AN and Auer S. LIMES-A Time-Efficient Approach for Large-Scale Link Discovery on the Web ofData[C]. In: Proceedings of LDOW2011, March29,2011, Hyderabad, India.
137. OpenLink Data Explorer.[EB/OL].(2011-10-11)[2012-01-05]. http://www.w3.org/wiki/OpenLinkDataExplorer
138. Panzer M. DDC,SKOS and Linked Data on the Web [EB/OL].[2012-03-21]. http://www.oclc.org/news/events/presentations/2008/ISKO/20080805-deweyskos-panzer.ppt.
139. Phipps J. Linked Data Standards (SKOS), In: ASIS&T2010. October25,2010. Pittsburgh, PA, USA.
140. Prud’hommeaux E and Seaborne A. SPARQL Query Language for RDF[EB/OL].(2008-01-15)[2012-05-23].http://www.w3.org/TR/rdf-sparql-query/
141. Raimond Y, Sutton C and Sandler M. Automatic Interlinking of Music Datasets on the Semantic Web[C]. In:Proceedings of LDOW2008, Beijing China.
142. RDF-Semantic Web Standards.[EB/OL].(2004-02-10)[2012-03-17]. http://www.w3.org/RDF/
143. Reynolds D, Cayzer S, Dickinson I, etal. SWAD-Europe: Semantic web applications-analysis and selection[EB/OL］.(2010-12-18)［2013-03-02］. http://www.w3.org/2001/sw/Europe/reports/open_demonstrators/hp-applications-survey
144. Sauermann L and Cyganiak R. Cool URIs for the Semantic Web[EB/OL].(2008-12-03)[2013-03-29].http://www.w3.org/TR/cooluris/
145. Schultz A and Bizer C. The R2R Framework-Transforming RDF Datasets[EB/OL](2011-07-21)[2013-04-14].http://www4.wiwiss.fu-berlin.de/bizer/r2r/spec
146. Sderbck A, Malmsten M. LIBRIS Linked Library Data[J]. Nodalities,2008,(5):19-20.
147. SEMTECH2011: The Semantic Technology Conference.[EB/OL].(2011-10-20)[2012-02-25].http://semtech2011.semanticweb.com/
148. Sheng H, Chen HJ, Yu T, etal. Linked data based semantic similarity and data mining[C]. Information Reuse andIntegration (IRI),2010IEEE International Conference on,4-6Aug.2010.
149. Shotton D and Peroni S. FaBiO, the FRBR-aligned Bibliographic Ontology[EB/OL].(2012-12-20)[2013-03-03].http://purl.org/spar/fabio/.
150. Smith DA, Popov I and Schraefel MC. Data Picking Linked Data: Enabling Users to create Faceted Browsers[C].At Web Science Conference2010, Raleigh, NC, USA,26-27Apr2010.
151. Studer R, Benjamins R and Fensel D. Knowledge Engineering: Principles and Methods. Data and KnowledgeEngineering,1998,25（12）:161～197.
152. Summers E, Isaac A, Redding C, etal. LCSH, SKOS和关联数据[J].现代图书情报技术,2009(3):8-14.
153. Sure Y, Bloehdorn S, Haase P, etal.The SWRC ontology-Semantic Web for research communities. In Proceedingsof the12th Portuguese Conference on Artificial Intelligence (EPIA2005). Springer, Covilha, Portugal, December2005.
154. SWAD-Europe: Semantic Web Applications-Analysis and Selection[EB/OL］.［2012-03-02］.http:///www.w3.org/2001/sw/Europe/reports/open_demonstrators/hp-applications-survey
155. The D2RQ Platform–Accessing Relational Databases as Virtual RDF Graphs.[EB/OL].[2012-05-22].http://d2rq.org/
156. The Linked Data Service of the German National Library.[EB/OL].(2010-09-28)[2012-01-06].http://files.d-nb.de/pdf/linked_data_e.pdf
157. Third International Workshop on Consuming Linked Data (COLD2012)[EB/OL].(2012-11-12)[2013-01-06].http://km.aifb.kit.edu/ws/cold2012/
158. Thomas K. Presentation at the OpenCalais Workshop at WeMedia2010: Optimizing Content with Semantic Tech.[EB/OL].(2010-05-10)[2012-12-20]. http://www.slideshare.net/KristaThomas/open-calais-workshop-at-wemedia-2010/
159. Tim F, Li D, Rong P,etal. Swoogle: Searching for knowledge on the Semantic Web. Proc.20th NationalConference on Artificial Intelligence and17th Innovative Applications of Artificial Intelligence Conference, AAAIPress/The MIT Press, Pittsburgh, Pennsylvania, USA (Jul2005),1682-1683.
160. Toni G, Christoph B and Felix N. Holistic and Scalable Ontology Alignment for Linked Open Data[C]. In:Proceedings of LDOW2012, April16,2012, Lyon, France.
161. Tony Hey等著,潘教峰等译.第四范式:数据密集型科学发现[M].科学出版社,12年6月.
162. VIAF: The Virtual International Authority File.[EB/OL].(2010-06-15)[2012-2-21]. http://viaf.org/
163. Volz J, Bizer C, Gaedke M, etal. Silk–A Link Discovery Framework for the Web of Data. In: Linked Data on theWeb workshop at WWW2009,2009
164. W3C Provenance Incubator Group. Provenance Vocabulary Mappings. Technical report,2010.http://www.w3.org/2005/Incubator/prov/wiki/Provenance_Vocabulary_Mappings, Released on August06,2010.
165. Xian GJ and Zhao RX. A Review and Prospects on Collaborative Ontology Editing Tools[C].2010InternationalSymposium on Agricultural Ontology Service, October30-31,2010Beijing, China.
166. Xian L, Li D and James A. Study Supreme Court Decision Making with Linked Data. Web Science Conf.2010,April26-27,2010, Raleigh, NC, USA.
167. Yu HQ, Dietze S, Li N, etal. A linked data-driven&service-oriented architecture for sharing educational resources.In:1st International Workshop on eLearning Approaches for Linked Data Age (Linked Learning2011),8thExtended Semantic Web Conference (ESWC2011),29May2011, Heraklion, Greece.
168. Zeng ML and Fan W. SKOS and Its Application in Transferring Traditional Thesauri into Networked KnowledgeOrganization Systems ［EB/OL］.(2008-08-05)［2013-03-25］.https://www.oclc.org/content/dam/oclc/news/events/presentations/2008/ISKO/200808-SKOS-zeng.pdf.
169. Zhang Y, Chen T, W You, etal. A New Efficient Semantic Web Platform Based on the Solr, SIREn and RDF[J].Lecture Notes in Information Technology,2012,25:1-7.”
170. Zhao J and Hartig O. Towards Interoperable Provenance Publication on the Linked Data Web [C]. In: Proceedingsof LDOW2012, April16,2012, Lyon, France.
171. Zhao J. The Open Provenance Model Vocabulary.Technical report,2010.http://purl.org/et/opmv/ns
2.白海燕,乔晓东.基于本体和关联数据的书目组织语义化研究[J].现代图书情报技术,2010,（9）:18-27.
3.白海燕,朱礼军.关联数据的自动关联构建研究[J].现代图书情报技术,2010,（2）:44-49.
4.白海燕.从关联数据的应用场景看信息服务发展的新动向[J].数字图书馆论坛,2012,(6):59-67.
5.白海燕.关联数据及DBpedia实例分析[J].现代图书情报技术,2010,（3）:33-39.
6.常春. Ontology在农业信息管理中的构建和转化.北京:中国农业科学院研究生院,2004.
7.朝乐门,张勇,邢春晓.面向开放关联数据的知识地图研究[J].图书情报工作,2012,56(10):17-24.
8.陈定权,肖鹏.关联数据会议文献研究述评[J].图书情报知识,2012,(3):103-110
9.陈彦.应用SPARQL进行RDF数据查询[J].企业技术开发（学术版）,2007,26(7):6-10.
10.邓兰兰,李春旺.Web数据关联创建策略研究[J].现代图书情报技术,2011,(5):1-6.
11.范炜,邹庆．词表资源关联化[J].情报理论与实践,2010,(5):21-25.
12.付旭雄.基于关联数据的知识地图中知识链接构建研究[D].武汉：华中师范大学,2012.
13.国家农业科学数据共享中心-农业科技机构数据库.(2005-08-01)[2013-03-20]. http://stb.agridata.cn/module_db/index_new.asp?rid=A030106&start=5&bs=&url=.
14.国家农业科学数据共享中心-农业科技人才数据库.(2005-08-01)[2013-03-20]. http://stb.agridata.cn/module_db/index_new.asp?rid=A030105&start=5&bs=&url=.
15.国家农业科学数据共享中心-国内农业在研项目数据库.(2005-08-01)[2013-03-20]. http://stb.agridata.cn/module_db/index_new.asp?rid=A030103&start=5&bs=&url=.
16.管进.基于关联数据的图书馆知识服务策略研究[J].图书馆理论与实践,2012,(6):9-11.
17.郭少友. OAI-PMH元数据的关联数据化方法研究[J].图书情报工作,2011,55(2):107-111.
18.郭少友.关联数据的动态链接维护研究[J].图书情报工作,2011,55(17)112-116.
19.胡莲香.国内关于图书馆应用关联数据研究综述与展望[J].农业网络信息,2012,(3):8-12.
20.黄鼎成,郭增艳.科学数据共享管理研究[M].北京:中国科学技术出版社,2002.
21.黄金霞.支持科研和学术发现的语义网应用实例研究[J].图书情报工作,2011,(11):125-129.
22.黄永文,岳笑,刘建华.关联数据应用的体系框架及构建关联数据应用的建议[J].现代图书情报技术,2011(9):7-13.
23.黄永文.关联数据驱动的Web应用研究[J].图书馆杂志.2010,29(7):55-59.
24.黄永文.关联数据在图书馆中的应用研究综述[J].现代图书情报技术,2010,（5）:1-7.
25.金海,袁平鹏.语义网数据管理技术及应用[M].北京:科学出版社,2010.
26.寇远涛.面向学科领域的科研信息环境建设研究[D].北京:中国农业科学院研究生院,2012.
27.郎杨琴,孔丽华.科学研究的第四范式——吉姆·格雷的报告”e-Science:一种科研模式的变革”简介[J].科研信息化技术与应用,2010,1(2):92-94.
28.李国杰.大数据研究的科学价值[J].中国计算机学会通讯,2012,8(9):8-15
29.李琳.关联数据在图书馆界的应用与挑战[J].图书与情报,2011(4):58-61.
30.李晓辉.图书馆科研数据管理与服务模式探讨[J].中国图书馆学报,2011,37(5):46-52.
31.李亚婷,曹洁,彭洋等. Web环境下关联数据的应用[J].情报理论与实践,2010,122-125.
32.林海青,楼向英,夏翠娟.图书馆关联数据:机会与挑战[J].中国图书馆学报,2012,38(197):58-67,112.
33.刘丽斌,张寿华,濮德敏等.《中国分类主题词表》的SKOS描述自动转换研究［J］.中国图书馆学报,2009,35(6):56-60.
34.刘炜,胡小菁,钱国富等. RDA与关联数据[J].中国图书馆学报，2012，(1)：34—42.
35.刘炜.关联数据:概念、技术及应用展望[J].大学图书馆学报,2011,(2):5-12.
36.娄秀明.用关联数据技术实现网络知识组织系统的研究[D].上海:华东师范大学.2010.
37.马费成,赵红斌,万燕玲等.基于关联数据的网络信息资源集成[J].情报杂志,2011,30(2):167-170,175.
38.马静,马春娥.如何利用D2R发布Linked data[EB/OL].(2010-03-25)[2012-05-22].http://www.ibm.com/developerworks/cn/web/1003_zhangjing_d2r.
39.马张华.信息组织（第二版）.北京:清华大学出版社,2003.
40.孟宪学等.农业科学数据核心元数据[M].北京:中国农业科学技术出版社,2008.
41.欧石燕.面向关联数据的语义数字图书馆资源描述与组织框架设计与实现[J].中国图书馆学报,2012,(6):58-71.
42.沈芸芸,冯英,刘秀文. DC元数据年度进展（2010）[J].数字图书馆论坛,2010,12:40-45.
43.沈志宏,刘筱敏,郭学兵等.关联数据发布流程与关键问题研究——以科技文献、科学数据的发布为例[J].中国图书馆学报,2012(2012):http://www.cnki.net/kcms/detail/11.2746. G2.20121105.2336.001.html
44.沈志宏,张晓林.关联数据及其应用现状综述[J].现代图书情报技术,2010(11):1-9.
45.孙鸿燕．图书馆关联数据的综合管理及其实现[J]．图书馆学研究，2011，(12):51-54,5.
46.谭洁清.关联数据的简介与进展[J].信息与电脑,2011(1):103,106.
47.汤怡洁,杨锐,刘毅.关联数据工具比较分析[J].现代图书情报技术,2011(增):*
48.陶俊,孙坦.基于Linked Data的RDF关联框架综析[J].现代图书情报技术,2011,27(12):1-8.
49.王军,张丽.网络知识组织系统的研究现状和发展趋势.中国图书馆学报,2008,34(1):65-69.
50.王珊,陈红.数据库系统原理教程[M].第1版.北京:清华大学出版社,1998.
51.王思丽,马建霞,祝忠明等.语义Web模式下综合科技资源的关联策略研究[J].现代图书情报技术,2011,(6):32-38.
52.王思丽,祝忠明.利用关联数据实现机构知识库的语义扩展研究[J].现代图书情报技术,2011(11):17-23.
53.王涛.基于关联数据的馆藏信息资源聚合研究[J].图书馆学刊,2012(8):44-46.
54.吴玥,李占羽.基于关联数据开放政府数据[J].电脑知识与技术,2010,6(31):8688-8691.
55.夏翠娟,刘炜等.关联数据发布技术及其实现——以Drupal为例[J].中国图书馆学报,2012,(1):49-57
56.鲜国建,孟宪学,常春.农业科学叙词表的OWL表示研究.中国农业科学,2007,42(增刊2):91～95
57.鲜国建,孟宪学,常春.基于农业本体的智能检索原型系统设计与实现.中国农学通报,2008,24(6):470-474.
58.熊太纯.基于SKOS的网络信息资源主题标引[J].图书馆学研究,2009(7):63-66.
59.徐华,曾微泊,王旭东.关联数据：图书馆学研究的新领域[J].南华大学学报,2011,12(6):107-109.
60.徐华.关联数据在国外图书馆中的应用及其借鉴意义[J].图书馆学研究,2011,(8):87-89.
61.徐雷. SPARQL查询优化[J],现代图书情报技术,2012,(10):42-48.
62.游毅,成全.基于关联数据的科研数据资源共享[J].情报杂志,2012,31(10):146-151.
63.喻非.《中国分类主题词表》网络化研究:从MARC到SKOS［C］.网络环境下信息组织的创新与发展:全国第五次情报检索语言发展方向研讨会论文集.北京:国家图书馆出版社,2009:139-147.
64.张继东,尹群.简单知识组织系统SKOS及其应用研究[J].现代情报,2008,28(11):20-25.
65.张继东,余以胜.利用叙词表构建本体的方法研究.现代图书情报技术,2006,(12):82-85.
66.张士男,宋文.《科图法》SKOS描述方案设计[J］.现代图书情报技术,2010(6):7-11.
67.张晓林.颠覆数字图书馆的大趋势[J].中国图书馆学报,2011,37(5):4-12.
68.赵瑞雪,寇远涛,鲜国建等.领域科研信息环境构建研究[J].数字图书馆论坛.2012(12):22-27.
69.周国民.农业科学数据共享中心通过国家认定[EB/OL].(2011-12-02)[2013-03-27].http://aii.caas.cn/bsdt/kyjz/551.htm.
70.周晓英.数据密集型科学研究范式的兴起与情报学的应对[J].情报资料工作,2012,(2):5-11.
71. Agricultural Thesaurus and Glossary Home Page [EB/OL].(2013-01-04)[2013-04-9].http://agclass.nal.usda.gov
72. Alexander K, Cyganiak R, Hausenblas M, etal. Describing Linked Datasets-On the Design and Usage of voiD, the“Vocabulary Of Interlinked Datasets”[C]. In: Proceedings of LDOW2009,April20,2009, Madrid, Spain.
73. Archer P, Goedertier S and Loutas N. Study on persistent URIs, with identification of best practices andrecommendations on the topic for the MSs and the EC[ER/OL].(2012-12-17)[2013-05-274].https://joinup.ec.europa.eu/sites/default/files/D7.1.3%20-%20Study%20on%20persistent%20URIs_4.pdf.
74. Auer S, Martin M, Frischmuth P, etal. Facilitation the publication of Open Governmental Data with the LOD2Stack.[EB/OL].[2012-12-17]. http://share-psi.eu/papers/LOD2.pdf
75. Baker T and Keizer J. Linked Data for Fighting Global Hunger: Experiences in setting standards for AgriculturalInformation Management. In: D. Wood (ed.), Linking Enterprise Data,2010:177-201.
76. Barnaghi, P, Presser, M and Moessner, K. Publishing linked sensor data[C]. In: ISWC2010,2010-11-07,Shanghai,China.
77. BBC Linked Data Journey.[EB/OL].(2010-05-27)[2012-12-20]. http://www.slideshare.net/rjw/bbc-linked-data-journey
78. Becker C and Bizer C. DBpedia Mobile: A Location-Enabled Linked Data Browser. In: Proceedings of the1stWorkshop about Linked Data on the Web (LDOW2008).
79. Belhajjame K, Cheney J, Garijo D, etal. The PROV Ontology: Model and Formal Semantics. Technical report2011[EB/OL].(2011-12-13)[2013-03-20]. http://www.w3.org/TR/2011/D-prov-o-20111213
80. Berrueta D, Brickley D, Decker S, etal. SIOC Core Ontology Specification.[EB/OL].(2007-06-12)[2013-03-04].http://rdfs.org/sioc/spec/
81. Bizer C, Cyganiak R and Heath T. How to publish Linked Data on the Web［EB/OL］.(2007-07-20［)2013-03-10］.http://sites.wiwiss.fu-berlin.de/suhl/bizer/pub/LinkedDataTutorial/20070727
82. Bizer C, Heath T and Lee TB. Linked Data-The Story So Far. In: Heath, T, Hepp, M, and Bizer, C (eds.).Special Issue on Linked Data, International Journal on Semantic Web and Information Systems (IJSWIS2009).
83. Bizer C, Heath T, Idehen K, etal. Linked data on the web (LDOW2008) Proceeding of the Seventeenthinternational conference on World Wide Web, Beijing, China.2008. pp.1265–1266.
84. Bizer, C. The Emerging Web of Linked Data[J]. Intelligent Systems, IEEE,2009,24(5):87-92.
85. Bizera C, Lehmannb J, Kobilarova G, etal. DBpedia-A crystallization point for the Web of Data. Web Semantics:Science, Services and Agents on the World Wide Web,2009,7(3):154-165.
86. Brickley D and Miller L. FOAF Vocabulary Specification.[EB/OL].(2010-01-01)[2012-01-03].http://xmlns.com/foaf/spec/20100101.html.
87. Carl L. The oreChem Project: Integrating Chemistry Scholarship with the Semantic Web. In: Proceedings of theWebSci'09: Society On-Line,18-20March2009, Athens, Greece.
88. Cheng G and Qu Y. Searching Linked Objects with Falcons: Approach, Implementation and Evaluation. Int. J.Sem. Web Inf. Sys.2009,5(3),49–70.
89. Codd, EF. A Relational Model of Data for Large Shared Data Banks[J]. Communications of the ACM,1970,13(6):377-387.
90. Collins, J P. The Fourth Paradigm Data-Intensive Scientific Discovery. Science,327,5972(Mar192010),1455-1456.
91. Corlosquet S. How to build Linked Data sites with Drupal7and RDFa.SemTech2010.［EB/OL］.[2012-05-10］.http://www.slideshare.net/scorlosquet/how-to-build-linked-datasites-with-drupal-7-and-rdfa.
92. Corlosquet S. Produce and consume Linked Data with Drupal［EB/OL］.[2012-05-22]. http://openspring.net/sites/openspring.net/files/corl-etal-2009iswc.pdf
93. D2R Server-Publishing Relational Databases on the Semantic Web.[EB/OL].(2010-02-16)[2012-02-15].http://www4.wiwiss.fu-berlin.de/bizer/d2r-server/
94. Data.gov Concept of Operations.[EB/OL].(2011-11-17)[2012-02-23]. http://www.data.gov/documents/data_gov_conops_v1.0.pdf
95. Datasets in the next LOD Cloud.[EB/OL].(2012-01-20)[2012-02-26]. http://www4.wiwiss.fu-berlin.de/lodcloud/
96. DC-2011, the eleventh International Conference on Dublin Core and Metadata Applications.[EB/OL].(2011-09-21)[2011-12-25]. http://dcevents.dublincore.org/index.php/IntConf/dc-2011
97. DCMI Metadata Terms [EB/OL].(2012-06-14)[2013-02-03]. http://dublincore.org/documents/2012/06/14/dcmi-terms/
98. Delbru R, Polleres A, Tummarello G, etal. Context Dependent Reasoning for Semantic Documents in Sindice. In:Proceedings of the4th InternationalWorkshop on Scalable Semantic Web Knowledge Base Systems (SSWS2008)(2008)
99. Dewey Decimal Classification-Linked Data［EB/OL］.(2012-06-12)［2013-03-02］.http://dewey.info
100. Dodds L and Davis I. Linked Data Patterns: A pattern catalogue for modelling, publishing, and consuming LinkedData[EB/OL].(2012-05-31)[2013-03-29]. http://patterns.dataincubator. org/book/linked-data-patterns.pdf
101. Dolan-Gavitt B, Leek T, Zhivich M, etal. Virtuoso: Narrowing the Semantic Gap in Virtual MachineIntrospection[C].Security and Privacy (SP),2011IEEE Symposium Berkeley CA: IEEE,2011:297-312
102. EuroVoc, the EU's multilingual thesaurus[EB/OL].(2012-12-18)[2013-04-09].http://eurovoc. uropa.eu/drupal/
103. FerréS, Hermann A and DucasséM. Semantic faceted search: Safe and expressive navigation in RDF graphs.Research report, IRISA (2011), http://hal.inria.fr/inria-00410959/PDF/PI-1964.pdf
104. FIELDING RT and TAYLOR RN. Principled design of the modern Web architecture[J]. ACM Transactions onInternet Technology,2002,2(2):115-150.
105. Getoor L. Link Mining: A New Data Mining Challenge [J]. Sigkdd Explorations,2003,5(1):84-89.
106. Glimm B. Using SPARQL with RDFS and OWL entailment, In proceedings of7th International Summer Schoolon Reasoning Web: Semantic Technologies for the Web of Data,2011, Lecture Notes in Computer Science, pp.137-201.
107. Golbeck J. Weaving a web of trust. Science.2008,321(5896):1640-1641.
108. Government HM. Putting the Frontline First: Smarter Government.[R/OL].(2009-12-07)[2012-01-06].http://www.hmg.gov.uk/media/52788/smarter-government-final.pdf.AGROVOC Linked Open Data [EB/OL].(2013-03-20)[2013-04-09]. http://aims.fao.org/standards/agrovoc/linked-open-data.
109. Hannemann J and Kett J. Linked Data for Libraries[C]. World Library and Information Congress:76th IFLAGeneral Conference and Assembly,10-15August2010, Gothenburg, Sweden.
110. Hartig O and Zhao J. Publishing and consuming provenance metadata on the web of linked data. In Proceedings ofIPAW2010,2010. https://cs.uwaterloo.ca/~ohartig/files/HartigZhao_Provenance_IPAW2010_Preprint.pdf
111. Haslhofer B and Schandl B. The OAI2LOD Server: Exposing OAI-PMH Metadata as Linked Data[C]. In:Proceedings of LDOW2008, Beijing China.
112. Hausenblas M. Linked Data Applications-The Genesis and the Challenges of Using Linked Data on the Web.[EB/OL].(2009-07-26)[2013-03-26]. http://wtlab.um.ac.ir/parameters/wtlab/filemanager/LD_resources/other/lod-app-tr-2009-07-26_0.pdf
113. Heath T and Bizer C. Linked Data: Evolving the Web into a Global Data Space[M]. Vol.1. Morgan&Claypool,2011,1-136.
114. Heath T and Motta E. Revyu: Linking reviews and ratings into the Web of Data. Web Semantics: Science, Servicesand Agents on the World Wide Web,2008,6(4):266-273.
115. Hey T, Tansler S, Tolle K, editors. The Fourth Paradigm: Data Intensive Scientific Discovery [M]. MicrosoftResearch Publishing,2009.
116. Hitzler P, Krotzsch M and Rudolph S. Foundations of Semantic Web Technologies. Chapman&Hall/CRC,2009.
117. Isaac A and Summers E. SKOS simple knowledge organization system primer.[EB/OL].(2008-2-21)[2012-01-04]. http://www.w3.org/TR/skos-primer/
118. Isele R,Jentzsch A and Bizer C. Silk Server-Adding Missing Links While Consuming Linked Data[C].In:Proceedings of the1st International Workshop on Consuming Linked Data, Shanghai,China,2010.
119. Jentzsch A, Zhao J, Hassanzadeh O, etal. Linking Open Drug Data. Proceedings of the Second TriplificationChallenge2009, Graz, Austria.2009
120. LC Linked Data Service (Library of Congress)[EB/OL].(2012-12-18)[2013-04-09]. http://id.loc.gov/
121. Lee TB, Chen Y, Chilton L, etal. Tabulator: exploring and analyzing Linked Data on the Semantic Web.Proceedings of the Third International Semantic Web User Interaction Workshop, Athens, Georgia, USA.2006.
122. Lee TB. Linked Data-Design Issues.[EB/OL].(2006-07-27)[2012-10-11]. http://www.w3.org/DesignIssues/LinkedData.html
123. Lee TB. Semantic Web-XML2000.[EB/OL].(2000-12-06)[2012-10-21]. http://www.w3.org/2000/Talks/1206-xml2k-tbl/Overview.html
124. Levenshtein V I. Binary Codes Capable of Correcting Deletions, Insertions and Reversals [J]. Doklady AkademiiNauk SSSR,1965,163(4):845-848.
125. Liang A, Sini M, Chang C, etal.(2006):The Mapping Schema from Chinese Agricultural Thesaurus toAGROVOC; New review of hypermedia and multimedia, vol.12, no1, pp.51-62, fromhttp://www.fao.org/docrep/008/af241e/af241e00.htm#Contents.
126. Linked data at OCLC [EB/OL].[2013-02-27]. http://www.oclc.org/data.htm1.
127. Linking Open Data.[EB/OL].(2012-01-19)[2013-02-16]. http://www.w3.org/wiki/SweoIG/TaskForces/CommunityProjects/LinkingOpenData
128. Lucene-SKOS-A SKOS Analyzer Module for Apache Lucene and Solr [EB/OL].[2012-07-20].https://github.com/behas/lucene-SKOS
129. Maali F, Cyganiak R and Peristeras V. Re-using Cool URIs: Entity Reconciliation Against LOD Hubs [C].Proceedings of LDOW2011, March29,2011, Hyderabad, India.
130. Malmsten M.将图书馆目录纳入语义万维网.李静雯译.现代图书情报技术,2009,3(3):2-8.
131. Manyika J, Chui M, Brown B, etal. Big data: The next frontier for innovation, competition, andproductivity[EB/OL].(2011-05-01)[2013-04-12]. http://www.mckinsey.com/insights/business_technology/big_data_the_next_frontier_for_innovation
132. Melanon B. Bringing Linked Data to Drupal;bringing the Semantic Web to theworld[EB/OL].(2008-10-15)[2012-05-22]. http://data.agaric.com/node/2700.
133. Melanon B. RDF's long lineage in Drupal.[EB/OL].(2008-09-21)[2012-05-22]. http://data.agaric.com/rdfs-long-lineage-drupal.
134. Momtchev V, Peychev D, Primov T, etal. Expanding the pathway and interaction knowledge in linked life data[C].In Proceedings of International Semantic Web Challenge,2009.
135. Myers J. Semantic Web and Linked Data “Coming of Age”.[EB/OL].(2010-07-20)[2012-12-22].http://www.slideshare.net/jaymmyers/semtech-maine.
136. Ngomo AN and Auer S. LIMES-A Time-Efficient Approach for Large-Scale Link Discovery on the Web ofData[C]. In: Proceedings of LDOW2011, March29,2011, Hyderabad, India.
137. OpenLink Data Explorer.[EB/OL].(2011-10-11)[2012-01-05]. http://www.w3.org/wiki/OpenLinkDataExplorer
138. Panzer M. DDC,SKOS and Linked Data on the Web [EB/OL].[2012-03-21]. http://www.oclc.org/news/events/presentations/2008/ISKO/20080805-deweyskos-panzer.ppt.
139. Phipps J. Linked Data Standards (SKOS), In: ASIS&T2010. October25,2010. Pittsburgh, PA, USA.
140. Prud’hommeaux E and Seaborne A. SPARQL Query Language for RDF[EB/OL].(2008-01-15)[2012-05-23].http://www.w3.org/TR/rdf-sparql-query/
141. Raimond Y, Sutton C and Sandler M. Automatic Interlinking of Music Datasets on the Semantic Web[C]. In:Proceedings of LDOW2008, Beijing China.
142. RDF-Semantic Web Standards.[EB/OL].(2004-02-10)[2012-03-17]. http://www.w3.org/RDF/
143. Reynolds D, Cayzer S, Dickinson I, etal. SWAD-Europe: Semantic web applications-analysis and selection[EB/OL］.(2010-12-18)［2013-03-02］. http://www.w3.org/2001/sw/Europe/reports/open_demonstrators/hp-applications-survey
144. Sauermann L and Cyganiak R. Cool URIs for the Semantic Web[EB/OL].(2008-12-03)[2013-03-29].http://www.w3.org/TR/cooluris/
145. Schultz A and Bizer C. The R2R Framework-Transforming RDF Datasets[EB/OL](2011-07-21)[2013-04-14].http://www4.wiwiss.fu-berlin.de/bizer/r2r/spec
146. Sderbck A, Malmsten M. LIBRIS Linked Library Data[J]. Nodalities,2008,(5):19-20.
147. SEMTECH2011: The Semantic Technology Conference.[EB/OL].(2011-10-20)[2012-02-25].http://semtech2011.semanticweb.com/
148. Sheng H, Chen HJ, Yu T, etal. Linked data based semantic similarity and data mining[C]. Information Reuse andIntegration (IRI),2010IEEE International Conference on,4-6Aug.2010.
149. Shotton D and Peroni S. FaBiO, the FRBR-aligned Bibliographic Ontology[EB/OL].(2012-12-20)[2013-03-03].http://purl.org/spar/fabio/.
150. Smith DA, Popov I and Schraefel MC. Data Picking Linked Data: Enabling Users to create Faceted Browsers[C].At Web Science Conference2010, Raleigh, NC, USA,26-27Apr2010.
151. Studer R, Benjamins R and Fensel D. Knowledge Engineering: Principles and Methods. Data and KnowledgeEngineering,1998,25（12）:161～197.
152. Summers E, Isaac A, Redding C, etal. LCSH, SKOS和关联数据[J].现代图书情报技术,2009(3):8-14.
153. Sure Y, Bloehdorn S, Haase P, etal.The SWRC ontology-Semantic Web for research communities. In Proceedingsof the12th Portuguese Conference on Artificial Intelligence (EPIA2005). Springer, Covilha, Portugal, December2005.
154. SWAD-Europe: Semantic Web Applications-Analysis and Selection[EB/OL］.［2012-03-02］.http:///www.w3.org/2001/sw/Europe/reports/open_demonstrators/hp-applications-survey
155. The D2RQ Platform–Accessing Relational Databases as Virtual RDF Graphs.[EB/OL].[2012-05-22].http://d2rq.org/
156. The Linked Data Service of the German National Library.[EB/OL].(2010-09-28)[2012-01-06].http://files.d-nb.de/pdf/linked_data_e.pdf
157. Third International Workshop on Consuming Linked Data (COLD2012)[EB/OL].(2012-11-12)[2013-01-06].http://km.aifb.kit.edu/ws/cold2012/
158. Thomas K. Presentation at the OpenCalais Workshop at WeMedia2010: Optimizing Content with Semantic Tech.[EB/OL].(2010-05-10)[2012-12-20]. http://www.slideshare.net/KristaThomas/open-calais-workshop-at-wemedia-2010/
159. Tim F, Li D, Rong P,etal. Swoogle: Searching for knowledge on the Semantic Web. Proc.20th NationalConference on Artificial Intelligence and17th Innovative Applications of Artificial Intelligence Conference, AAAIPress/The MIT Press, Pittsburgh, Pennsylvania, USA (Jul2005),1682-1683.
160. Toni G, Christoph B and Felix N. Holistic and Scalable Ontology Alignment for Linked Open Data[C]. In:Proceedings of LDOW2012, April16,2012, Lyon, France.
161. Tony Hey等著,潘教峰等译.第四范式:数据密集型科学发现[M].科学出版社,12年6月.
162. VIAF: The Virtual International Authority File.[EB/OL].(2010-06-15)[2012-2-21]. http://viaf.org/
163. Volz J, Bizer C, Gaedke M, etal. Silk–A Link Discovery Framework for the Web of Data. In: Linked Data on theWeb workshop at WWW2009,2009
164. W3C Provenance Incubator Group. Provenance Vocabulary Mappings. Technical report,2010.http://www.w3.org/2005/Incubator/prov/wiki/Provenance_Vocabulary_Mappings, Released on August06,2010.
165. Xian GJ and Zhao RX. A Review and Prospects on Collaborative Ontology Editing Tools[C].2010InternationalSymposium on Agricultural Ontology Service, October30-31,2010Beijing, China.
166. Xian L, Li D and James A. Study Supreme Court Decision Making with Linked Data. Web Science Conf.2010,April26-27,2010, Raleigh, NC, USA.
167. Yu HQ, Dietze S, Li N, etal. A linked data-driven&service-oriented architecture for sharing educational resources.In:1st International Workshop on eLearning Approaches for Linked Data Age (Linked Learning2011),8thExtended Semantic Web Conference (ESWC2011),29May2011, Heraklion, Greece.
168. Zeng ML and Fan W. SKOS and Its Application in Transferring Traditional Thesauri into Networked KnowledgeOrganization Systems ［EB/OL］.(2008-08-05)［2013-03-25］.https://www.oclc.org/content/dam/oclc/news/events/presentations/2008/ISKO/200808-SKOS-zeng.pdf.
169. Zhang Y, Chen T, W You, etal. A New Efficient Semantic Web Platform Based on the Solr, SIREn and RDF[J].Lecture Notes in Information Technology,2012,25:1-7.”
170. Zhao J and Hartig O. Towards Interoperable Provenance Publication on the Linked Data Web [C]. In: Proceedingsof LDOW2012, April16,2012, Lyon, France.
171. Zhao J. The Open Provenance Model Vocabulary.Technical report,2010.http://purl.org/et/opmv/ns