Abstract
In recent years, data has become vital in supporting our everyday lives. Along with large volumes of open data available on the web, various types of public, private, and enterprise data are stored in the cloud or distributed over multiple devices. The value of this data would increase drastically if we were able to integrate it. This would enable more sophisticated presentation and analysis of previously disparate data. So far, however, it is challenging for non-expert users to efficiently make use of such data because (i) data heterogeneity hampers integration of different kinds of data that are stored in various formats and spread among storage infrastructures; (ii) manual data integration processes are typically neither reproducible, nor reusable; and (iii) the lack of support for exploration does not allow for the integration of arbitrary data sources. This paper tackles these challenges by introducing a mashup platform that combines semantic web and mashup concepts to help users obtain insights and make informed decisions. To this end, we leverage a semantic model of mashup components for automated techniques that support the user in exploring available data. Moreover, we introduce a collaborative and distributed model to create and execute mashups. This facilitates distributed ad-hoc integration of heterogeneous data contributed by multiple stakeholders.
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Notes
- 1.
https://www.gov.uk/government/publications/open-data-charter/g8-open-data-charter-and-technical-annex (accessed October 7, 2016).
- 2.
http://www.apatar.com/ (accessed October 7, 2016).
- 3.
http://www.fluidops.com/en/portfolio/information_workbench/ (accessed October 7, 2016).
- 4.
http://www.husky.fer.hr/ (accessed October 7, 2016).
- 5.
http://mdc.jackbe.com/enterprise-mashup (accessed October 7, 2016).
- 6.
http://www.w3.org/TR/widgets/ (accessed October 7, 2016).
- 7.
http://www.w3.org/TR/json-ld/ (accessed October 7, 2016).
- 8.
https://www.wunderground.com/ (accessed October 7, 2016).
- 9.
https://www.w3.org/TR/vocab-data-cube (accessed October 7, 2016).
- 10.
http://linkedwidgets.org/serverwidgets/ExcelSheet.jar (accessed October 7, 2016).
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Appendices
A Mashup Feature Checklist
Mashup Type
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Data mashups
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Logic mashups
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User Interface (UI) mashups
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Hybrid mashups
Component Types
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Data components
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Logic components
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UI components
Runtime Location
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Client-side only
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Server-side only
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Both Client and Server
Integration Logic
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UI-based integration
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Orchestrated integration (local and hybrid mashups)
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Choreographed integration (distributed server-side mashups)
Instantiation Lifecycle
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Stateless
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Short-living
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Long-living (persistent mashups)
B Mashup Tool Feature Checklist
Targeted End-User
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Local Developers
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Non Programmers
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Expert Programmers
Automation Degree
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Full Automation
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Semi-automation
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Manual
Liveness Level
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Level 1 (Non-Executable Prototype Mockup)
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Level 2 (Explicit Compilation and Deployment Steps)
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Level 3 (Automatic Compilation and Deployment, requires Re-initialization)
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Level 4 (Dynamic Modification of Running Mashup)
Interaction Technique
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Editable Example
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Form-based
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Programming by Demonstration
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Spreadsheets
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Textual DSL
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Visual Language (Iconic)
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Visual Language (Wiring, Implicit Control Flow)
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Visual Language (Wiring, Explicit Control Flow)
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WYSIWYG
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Natural Language
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Other
Online User Community
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None
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Private
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Public
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Trinh, TD., Wetz, P., Do, BL., Kiesling, E., Tjoa, A.M. (2017). Linked Widgets Platform for Rapid Collaborative Semantic Mashup Development. In: Daniel, F., Gaedke, M. (eds) Rapid Mashup Development Tools. RMC 2016. Communications in Computer and Information Science, vol 696. Springer, Cham. https://doi.org/10.1007/978-3-319-53174-8_4
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DOI: https://doi.org/10.1007/978-3-319-53174-8_4
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