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New Technology of Library and Information Service  2010, Vol. 26 Issue (1): 41-45    DOI: 10.11925/infotech.1003-3513.2010.01.08
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Research on Mashup Tools
Ji Shanshan1,2   Li Yu1   Zhou Qiang1
1(National Science Library, Chinese Academy of Sciences, Beijing 100190, China)
2(Graduate University of Chinese Academy of Sciences, Beijing 100049, China)
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Abstract  

After revealing the current research status and features of Mashup tools, this paper introduces some relevant technologies and classification models of Mashup tools. And based on this, the paper designs a new classification model composed of Data Mashup tool, Presentation Mashup tool and Enterprise Mashup tool. In the same time, it analyzes the main functions and crucial technologies of typical Mashup tools.

Key wordsMashup tool      Classification      Enterprise Mashup      Architecture       
Received: 16 October 2009      Published: 25 January 2001
: 

G250.7

 
Corresponding Authors: Shanshan Ji     E-mail: jishanshan@mail.las.ac.cn
About author:: Ji Shanshan,Li Yu,Zhou Qiang

Cite this article:

Ji Shanshan,Li Yu,Zhou Qiang. Research on Mashup Tools. New Technology of Library and Information Service, 2010, 26(1): 41-45.

URL:

http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.1003-3513.2010.01.08     OR     http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2010/V26/I1/41

[1] Wikipedia[DB/OL].[2009-09-10].
http://en.wikipedia.org/wiki/Mashup_(web_application_hybrid).
[2]Koschmider A, Torres V, Pelechano V. Elucidating the Mashup Hype: Definition, Challenges,
Methodical Guide and Tools for Mashups[R/OL].[2009-09-10].
http://www.integror.net/mem2009/papers/paper14.pdf.
[3] Housingmaps[EB/OL].[2009-09-10].http://www.housingmaps.com/.
[4] Forrester: Enterprise Mashups to Hit $700 Million by 2013[EB/OL].
[2009-09-10].http://www.readwriteweb.com/archives/forrester_enterprise_Mashups.php.
[5] SIMILE Project[EB/OL].[2009-08-24].http://simile.mit.edu/.
[6] Introducing OpenAjax Hub 2.0 and Secure Mashups[EB/OL].[2009-09-10].
http://www.openajax.org.
[7] Sohei Ikeda, Takakazu Nagamine, Tomio Kamada. Application Framework with
Demand-Driven Mashup for Selective Browsing[C].In:Proceedings of the 10th International
Conference on Information Integration and Web-based Applications & Services,Linz, Austria.
New York, NY, USA: ACM,2008:33-40. 
[8]Wang G L,Yang S H, Han Y B. Mashroom: End-user Mashup Programming Using Nested
Tables[DB/OL].[2009-07-28]. http://www2009.org/proceedings/pdf/p861.pdf.
[9]Atwood M,Balfanz D,Bounds D, et al. OAuth Core 1.0 Revision [EB/OL].[ 2009-09-10].
http://oauth.net/core/1.0a.
[10] 李峰,李春旺.Mashup关键技术研究[J].现代图书情报技术,2009 (1): 44-49.
[11] ICT ROMULUS Report: D4.1-Annual Report on Mashup Integration[R/OL].
[2009-08-24]. http://www.ict-romulus.eu/c/document_library/get_file?p_l_id=2266&folderId=29495&name=DLFE-4583.pdf.
[12] Hoyer V,  Fischer M. Market Overview of Enterprise Mashup Tools[C]. In:Proceedings
of the 6th International Conference on Service-oriented Computing,Sydney, Australia. Berlin,
Heidelberg:Springer  Verlag,2008:708-721.
[13] Giusy Di Lorenzo, Hakim Hacid, Hye-Young Paik,et al. Data Integration in Mashups
[EB/OL]. [2009-08-24]. http://www.sigmod.org/sigmod/record/issues/0903/p59.surveys.hacid.pdf.
[14] 李春旺,肖伟.集成融汇:概念、模式与应用[J].现代图书情报技术,2008(12):22-26.
[15] Apatar[EB/OL].[2009-09-10]. http://www.apatar.com/.
[16] Netvibes Overview 2009[EB/OL].[2009-09-10]. http://www.slideshare.net/culturebuzz/netvibes-overview-09.
[17] Hoyer V,  Stanoesvka-Slabeva K,  Janner T, et al. Enterprise Mashups: Design Principles
Towards the Long Tail of User Needs[EB/OL]. [2009-08-24].
http://iknow.seforge.org/classic_bib/classic_paper/672a52067c7b76846587732e/inproceedingsreference.2009-04-22.7620820818.
[18] Reference Architecture for Enterprise ‘Mashups’[EB/OL]. [2009-08-24].
http://liquidbriefing.com/pub/Harmonia/IndustryAnalysts/reference_architecture_for_e_151491.pdf.
[19] Javier López, Alberto Pan, Fernando Bellas, et al. Towards a Reference Architecture for
Enterprise Mashups[EB/OL]. [2009-08-24]. http://www.sistedes.ess/TJISBD/Vol-2/No-2/articles/Lopez.pdf.
[20] JackBe Presto: The Enterprise Mashup Platform[EB/OL].[2009-08-24].
http://www.jackbe.com/downloads/Jackbe_Presto_Overview.pdf.

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