Exchanging Data Agreements in the DaaS Model

Truong, Hong-Linh; Dustdar, Schahram; Götze, Joachim; Fleuren, Tino; Müller, Paul; Tbahriti, Salah-Eddine; Mrissa, Michaël; Ghédira, Chirine

doi:10.1109/apscc.2011.59

Cited by 17 publications

(9 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In fact, they present a data contracts compatibility evaluation algorithm and they define how to construct, compose and exchange a data contract. In [20], they introduce their model for exchanging data agreements in the Data-as-a-Service (DaaS) based on a new type of services which is called Data Agreement Exchange as a Service (DAES). This model is called DEscription MOdel for DaaS (DEMODS) [21].…”

Section: Related Workmentioning

confidence: 99%

“…Indeed, we find several works [19], [20], [21] [22] [23], [24] enabling an application to negotiate its Data Management Contract (DMC), often referred to as data agreement or data license, with various clouds and to bind to the specific DBMSs according to its DMC. Truong et al [19], [20], [21] propose to model and specify data concerns in data contracts to support concern-aware data selection and utilization. For this purpose, they define an abstract model to specify a data contract and the main data contract terms.…”

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Supporting Multi Data Stores Applications in Cloud Environments

Sellami

Bhiri

Defude

2016

IEEE Trans. Serv. Comput.

View full text Add to dashboard Cite

International audienceThe production of huge amount of data and the emergence of cloud computing have introduced new requirements for data management. Many applications need to interact with several heterogeneous data stores depending on the type of data they have to manage: traditional data types, documents, graph data from social networks, simple key-value data, etc. Interacting with heterogeneous data models via different APIs, and multiple data store applications imposes challenging tasks to their developers. Indeed, programmers have to be familiar with different APIs. In addition, the execution of complex queries over heterogeneous data models cannot, currently, be achieved in a declarative way as it is used to be with mono-data store application, and therefore requires extra implementation efforts. Moreover, developers need to master and deal with the complex processes of cloud discovery, and application deployment and execution. In this paper we propose an integrated set of models, algorithms and tools aiming at alleviating developers task for developing, deploying and migrating multiple data stores applications in cloud environments. Our approach focuses mainly on three points. First, we provide a unifying data model used by applications developers to interact with heterogeneous relational and NoSQL data stores. Based on that, they express queries using OPEN-PaaS-DataBase API (ODBAPI), a unique REST API allowing programmers to write their applications code independently of the target data stores. Second, we propose virtual data stores, which act as a mediator and interact with integrated data stores wrapped by ODBAPI. This run-time component supports the execution of single and complex queries over heterogeneous data stores. Finally, we present a declarative approach that enables to lighten the burden of the tedious and non-standard tasks of (1) discovering relevant cloud environment and (2) deploying applications on them while letting developers to simply focus on specifying their storage and computing requirements. A prototype of the proposed solution has been developed and is currently used to implement use cases from the OpenPaaS projec

show abstract

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Supporting Multi Data Stores Applications in Cloud Environments

Sellami

Bhiri

Defude

2016

IEEE Trans. Serv. Comput.

View full text Add to dashboard Cite

show abstract

“…For the DaaS research [1,3,4,7,11,13,17,19,22,[25][26][27], papers were discarded when they were focused on security or structural aspects of the service. As our focus where aimed at data aspects of the service, we had to maintain twelve papers that were mapped into the bubble chart in Figure 2.…”

Section: Literature Surveymentioning

confidence: 99%

MIDAS: A Middleware to Provide Interoperability between SaaS and DaaS

Marinho¹,

Cidreira²,

Claro³

et al. 2016

Anais Do Simpósio Brasileiro De Sistemas De Informação (SBSI)

View full text Add to dashboard Cite

Software as a Service (SaaS) and Data as a Service (DaaS) proves to be two promising areas of research in the cloud computing field, however interoperability among different cloud providers is yet poorly explored. Today, clients looking for content or services from different providers need extra time and resources to learn and implement the required adaptations from the other parties. In this paper we propose MIDAS, a novel middleware to interoperate SaaS and DaaS services seamlessly and independently from provider. That is, SaaS applications will be able to get data from DaaS datasets by sending a query to our middleware and letting it mediate the communication and return the expected results. We evaluate our proposal by developing a prototype from two case studies and by analyzing the time effort to query through our middleware. Our results presented that no important overhead were required from providers nor to the final user.

show abstract

“…Several works have been introduced to support data licensing, such as Dalheimer and Pfreundt (2009) and Götze et al (2010). In Truong et al (2011a), a data agreement exchange service has been developed. In this paper, we do not address the issue of exchanging data contracts.…”

Section: Related Workmentioning

confidence: 99%

“…The resulting contracts can be extracted into different formats, such as XML, JSON and RDF. These contracts can be associated with data assets, managed by DaaS, stored in other services [such as a data agreement exchange service for data marketplaces (Truong et al, 2011a)], or stored into data contract knowledge service as common, shared data contracts. In our current prototype, Data Contract Knowledge Service includes common terms, categories, and contracts (based on data contracts in Table 1).…”

Section: Prototypementioning

confidence: 99%

Data contracts for cloud-based data marketplaces

Truong¹,

Comerio

Paoli

et al. 2012

IJCSE

Self Cite

View full text Add to dashboard Cite

Currently, rich and diverse data types have been increasingly provided using the dataas-a-service (DaaS) model, a form of cloud computing services and the core element of data marketplaces. This facilitates the on-the-fly data composition and utilisation for several dataintensive applications in e-science and business domains. However, data offered by DaaS are constrained by several data concerns that, if not automatically being reasoned properly, will lead to a wrong way of using them. In this paper, we support the view that data concerns should be explicitly modelled and specified in data contracts to support concern-aware data selection and utilisation. We perform a detailed analysis of current techniques for data contracts in the cloud. Instead of relying on a specific representation of data contracts, we introduce an abstract model for data contracts that can be used to build different types of data contracts for specific types of data. Based on the abstract model, we propose several techniques for evaluating data contracts that can be integrated into data service selection and composition frameworks. We also illustrate our approach with some real-world scenarios and show how data contracts can be integrated into data agreement exchange services in the cloud.

show abstract

Exchanging Data Agreements in the DaaS Model

Cited by 17 publications

References 6 publications

Supporting Multi Data Stores Applications in Cloud Environments

Supporting Multi Data Stores Applications in Cloud Environments

MIDAS: A Middleware to Provide Interoperability between SaaS and DaaS

Data contracts for cloud-based data marketplaces

Contact Info

Product

Resources

About