=Paper=
{{Paper
|id=Vol-470/paper-2
|storemode=property
|title=Reputation Based Self-Service Environments
|pdfUrl=https://ceur-ws.org/Vol-470/paper2.pdf
|volume=Vol-470
}}
==Reputation Based Self-Service Environments==
https://ceur-ws.org/Vol-470/paper2.pdf
ComposableWeb'09
Reputation-Based Self-Service Environments
Donato Barbagallo, Cinzia Cappiello, Chiara Francalanci, Maristella Matera
Dipartimento di Elettronica e Informazione, Politecnico di Milano,
Via Ponzio 34/5, 20133 Milano, Italy
{barbagallo, cappiello, francala, matera}@elet.polimi.it
Abstract. The availability of a huge amount of information on the Web raises a
set of issues concerning the research, the selection, and the representation of
trustworthy sources and services. This paper describes a new research, which
we have recently started and that aims at developing a platform to support users
in the creation of mashup-based personalized self-service environments, where
the users can access dependable services, selected on the basis of their
reputation. This paper illustrates the motivations behind our research, and
introduces some preliminary ideas about the platform design.
Keywords: Self-Service Environments, Mashups, Reputation, Quality.
1 Introduction
The Web is a huge and heterogeneous source of information. Web 2.0 technologies
have enabled an active role of the users, who can create and make available their
contents very easily [7]. This allows people to express their opinions, and to distribute
them through several means, such as forums, blog posts and comments, and social
networks. It therefore becomes possible to access other people opinions, direct
witnesses and spread ideas bypassing traditional and official sources of information
such as corporate websites. Of course, the availability of such an amount of
information raises a set of issues concerning the research, the selection, and the
representation of trustworthy sources and services. The information retrieved on the
Web is indeed often characterized by inconsistent, incomplete, and erroneous data,
and users are not able to distinguish the right or the most suitable data along their
needs. Furthermore, all the accessible sources could be better exploited if they are
combined in a mashup wise, so that to obtain a tangible added value. To respond to
the previous needs, this paper discusses some issues behind the provision of
personalized self-service environments where users can build their view over the Web
information space, by integrating trustworthy services for information access.
The remainder of this paper is organized as follows. Section 2 illustrates a scenario
that clarifies the novel requirements addressed by our research. Section 3 describes
the architecture of the platform that we want to build, while Sections 4 and 5 discuss
the two salient themes addressed by our project, namely reputation assessment and the
construction of self-service environments based on mashup technologies. Finally
Section 6 outlines future work.
2 A Reference Scenario
To understand the idea at the basis of our research, let us consider a usage scenario in
the context of patient empowerment. We suppose that an individual with a health
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problem is searching for a dependable source of information, such as a forum where
to get advice on his/her specific problem. This raises a number of issues: (i) the
selection of the most dependable forum, (ii) understanding who other participants are
trustworthy, and eventually (iii) integrating different answers from multiple forums
and dynamically monitor the most reliable sources of information on specific
subjects. In addition to discovering the best sources of information, the individual
might also add new value to the identified dependable sources by combining different
trusted services for creating his/her personalized information access, e.g. combining
the identified forum with a map service showing the location of the hospitals
mentioned in the forum, as well as with services for accessing rankings, news, and
images. This implies the availability of methods for easy service aggregation, which
can be based on mashup technologies.
To the state of the art, the current technology does not exhaustively cover the
previous needs. Our aim is therefore to provide a platform satisfying them.
3 Platform Architecture
The previous scenario highlights two fundamental needs: (i) to select dependable
services that can fulfil specific information needs and quality requirements and (ii) to
provide users with tools to compose on-demand personalized applications by means
of the selected dependable services.
To respond to these needs, we aim at designing a platform providing self-service
mashup functionalities, to help people create a personalized Web access environment.
Based on a user profile, the platform searches for the “best” information sources,
selects relevant and authoritative information, and then wraps it as data services. Data
services are then mixed with other services, typically mashup components [8], to
create a personalized environment based on mashup technologies.
Figure 1 illustrates the main components of the proposed platform. The Service
Registry stores a catalogue of services that can be used for the creation of the
personalized user environment. They can be data services, providing a binding with a
dependable data source through a description of the data structure, generic Web
services enabling the retrieval of some relevant information, or also UI components
[8]. The registry is populated by a domain expert, who is in charge of scouting
relevant data sources. A Reputation Monitor evaluates the services from the
catalogue, and assigns measures based on objective reputation criteria (e.g.,
institutional reputation). Such assessment is continuously updated: periodically, the
Reputation Monitor verifies and updates the quality level of the data sources. The
output of the assessment activity is a Reputation Descriptor, which stores the result of
the computation of the reputation measures.
The Broker selects the services that best match the specified user’s settings (e.g.,
information needs expressed in the queries that the user submits to the platform) and
the user’s profile. The services selected by the broker are then used by the self-service
environment that helps users create their personal information access environment.
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Figure 1- Platform architecture
The Self-Service Environment is centred on the availability of a mashup engine,
through which the user can select some relevant components from the Mashup
Component Repository and combine them to generate new value. The components
available in the repository are those previously selected by the broker. In order to be
combined into a mashup, these services need to be componentized, i.e. each service
must be associated with a descriptor highlighting the properties useful for
combination and choreography purposes.
When the services selected by the broker are not provided with a proper user
interface, as it happens for pure data services, the componentization process also
requires the generation of a presentation layer. This process implies the selection of
some visualization widgets (from a widget repository) that best match the operations
and the exchanged data as indicated by the service descriptors (WSDL descriptor,
API, or also additional service profiles). The previous functionalities raise the
research challenges described in the following sections.
4 Reputation Assessment
The selection of the “best” sources, the assessment of their trustworthiness, and the
integration of the relevant contents are all based on the ability to assess the reputation
of the information sources. The concept of reputation is the result of the assessment of
several quality properties of information sources, including correctness, completeness,
timeliness, dependability, and consistency [3]. The literature provides consolidated
data quality techniques in the case of structured data. For example, a classical
approach to data brokering in the context of syndicated data is represented in [1],
where data are structured and query answers are fully integrated and returned to users
as a table (or a set of tables), as with traditional databases. This work has been
subsequently extended with the concept of reputation [2]. In a multi-source context, it
proposes to assess the reputation of each information source by means of i) an a-priori
assessment of the reputation of the information source, based on the source’s
authority in a given field and ii) an assessment of the source’s ability to offer relevant
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answers to user queries based on historical data on the source collected by the broker
as part of its service. This approach is original since it defines reputation as a context-
and time-dependent characteristic of information sources, and leverages the ability of
the broker to keep a track record of each source’s reputation over time, but it should
be extended with dimensions related to the quality of mashup components to be
integrated into the final self-service environment. Quality criteria for the different
aspects of traditional software applications have been proposed and thoroughly
analyzed in the literature, but the adaptability, dynamicity, and heterogeneity that
characterize the mashup ecosystem require a separate and focused analysis.
Our research goal is therefore to define an assessment of the reputation of an
information source, e.g., a Web page, based on the assessment of a number of
properties of the sources along the traditional data and software quality dimensions,
and also on the indirect assessment of the information sources and contributors that
the original source includes. This involves the selection of relevant quality
dimensions, their operating definition, their metrics, and their composition into an
overall assessment of reputation that leverages the historical and contextual
knowledge base of the broker.To understand the methodological approach that we
will implement in our platform, let us assume that the Web page belongs to a forum.
First of all, the Reputation Monitor in Figure 1 must provide an evaluation of the
forum’s reputation as information source. A source’s completeness represents a
fundamental quality dimension. The completeness of the information provided by a
forum could be defined as the breadth of the forum in terms of number of users and
issues raised, which, in turn, would lead to the operating definition of completeness as
the total number of subscribers/contributors and their participation rate in terms of
number of posts per day. Then, we could evaluate the forum’s reputation along the
dependability dimension in terms of the probability with which a post receives an
answer, which leads to define dependability as the number of answers per post. This
metric could be corrected with a semantic analysis of the relevance of responses.
Subjective measures should also be considered, such as comments on the quality of a
contribution that the site records explicitly, as different types of ratings, which can be
internal to the forum, or external, i.e., stored by sites that aggregate and rate other
sites’ news. Numerous time-dependent measures of reputation could also be defined,
for example along the timeliness dimension, by considering metrics such as the
frequency of update of a site, its age, etc.
Behind assessing the reputation of the information sources, the broker must be able
to evaluate the quality of the mashup components that must provide access to the
information source in the self-service environment, also trying to assess the overall
quality of possible integrations of multiple components. For this purpose, quality
criteria for the different aspects of traditional software applications already proposed
in the literature can be exploited, but the adaptability and dynamicity that characterize
the mashup ecosystem require a separate and focused analysis. In fact, mashups
integrate heterogeneous components available on the Web, such as RSS/Atom feeds,
Web services, wrapped content or programmable APIs (e.g., Google Maps). It is self-
evident that the quality of the final combination is strongly influenced by the quality
of each single component. If we look at components as standalone modules, then we
can say that their quality is determined by the attributes that traditionally characterize
software quality. However, it is necessary to consider that the publication of mashup
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components through APIs hides their internal complexity and, therefore, also their
internal details. Given that from the outside component-internal properties cannot be
assessed, a novel quality model is required in order to characterize an “external”
quality model. Selected quality attributes should be able capture the specific
requirements deriving from the components' intended use, i.e., their combination
within mashups. In fact, after a component has been deployed, external quality factors
are the only criteria able to drive the evaluation of its suitability into mashup
compositions. We have already defined a preliminary model of external quality to fill
the literature gaps discussed above [4]. Further work is however needed to extend the
broker for the coverage of such new quality requirements.
5 Self-Service Environments
Mashups are innovative applications that create new value out of the services they
integrate, in that they combine them in a novel, value-adding manner and thereby
provide a functionality that was not there before. A variety of mashup tools (e.g.,
Yahoo Pipes, Google Mashup Editor, Intel Mash Maker, Microsoft Popfly, and IBM
QEDWiki - now part of IBM Mashup Center) have recently emerged. Their principal
goal is to facilitate the combination of components via simple, graphical user
interfaces, sets of predefined components, and abstractions from technicalities.
However, they all assume the existence of ready-to-use components published on the
Web, while they neglect the ensemble of issues related to the creation and selection of
trusted components.
Our research project will exploit the availability of a consolidate mashup
environment, Mixup [8], which supports the fast development of Web applications
based on the mashup of UI components. The distinguishing characteristic of Mixup is
that it focuses on the integration of components at the presentation layer, leaving
application and data management logic inside components. It also makes use of
component and composition models that are inspired by the research on Web services
and the service-oriented architecture (SOA). The component model specifies the
events that a component can generate and that communicate to the outside world
changes in the internal state. It also specifies the operations which enable the outside
world to modify the internal state of a component. Given such abstract component
description, the composition logic is then described through an event-driven
composition model, where events from one component may be mapped to operations
of one or more other components; mappings are expressed by means of so-called
listeners. In addition to the direct mapping of events to operations, listeners also
support data transformations in form of XSLT transformations, and the specification
of more complex mapping logics via inline JavaScript. The definition of listeners
represents the composition logic, while the layout of a composite application is
specified by means of a suitable HTML template that contains placeholders, which
can be used at runtime to embed and execute components, thereby re-using their UIs.
Within this project, we will exploit Mixup as the basic engine for allowing users to
mashup their self-service environment. The new issues to be investigated are related
to the componentization of trusted services. We want to define some techniques to
turn services providing dependable information (Web services, data services, but also
Web applications publishing relevant and trusted information) into components for
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mashup combination. In [5], we already investigated a technique for turning Web
applications into mashup components. The idea is that the HTML of generic
(dynamic) Web pages can be augmented with annotations for event and operation
tagging and combined with a descriptor specifying such events and operations. A
wrapper then provides programmatic access to the application, i.e., an API. Under
particular conditions, both the descriptor and the wrapper can be automatically
generated from the HTML tags.
We expect to further improve the previous results by introducing techniques for the
componentization of generic Web and data services. Such may require mechanisms
for the automatic selection of visualization widgets suitable for rendering the service
data. Based on the semantic description of services, suitable UI widgets are used to
display the data (e.g., a regional map is used to display postal addresses, 2D graphs
are used to display historical financial data, graphs with nodes and arcs are used for
depicting social networks). For this purpose, a registry of UI widgets, together with
their semantic descriptions, will be designed and implemented. This feature, which
will go beyond the provision of a mere Web programming environment exploiting
ready-to-use components, is to our knowledge still unexplored.
6 Conclusion and Future Work
This paper has presented some ideas about a new research project that deals with the
construction of self-service environments for the access to dependable information
services. We are now working at the platform development, acting on two different
fronts that reflect the two fundamental themes also discussed in this paper. On the one
hand we are extending the quality broker with techniques for reputation assessment
and for the assessment of the quality of mashup components [4]. On the other hand,
we are developing an environment for the easy creation of mashup components, based
on an automated technique for user interface construction. Our research is still in its
infancy. However, given the recent trends in Web information access, we believe it is
very promising and we hope to get soon sound results.
References
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selecting and provisioning high quality syndicated data. In: 10th International Conference
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data. Technical Report n. 12/2009, DEI - Politecnico di Milano, Jan. 2009.
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assessment and improvement. ACM Comp. Surveys, 41(3), Sept. 2009.
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