Context: Cloud Computing is an emerging technology where present IT is trending towards it. Many enterprises and users are still uncomfortable to adopt Cloud Computing as it uncovers many potential and critical threats which remind the most concerned security issue to consider. As data is migrated between different data centers dispersed globally, security for data is a very important issue. In Cloud environment Cloud user should be aware of the physical location of the data to ensure whether their data reside within certain jurisdiction as there are different data privacy laws. Evaluating different data localization frameworks in Amazon Web Services by deploying web application in Amazon availability zones (US, Europe and Asia) is the main context of this study. Objectives: In this study we investigate which strategic data localization frameworks have been proposed, can be used to identify data location of web application resource deployed in Cloud and validate those considered three frameworks by conducting experiment in a controlled environment. Methods: Literature Review is performed by using search string in data bases like Compendex, IEEE, Inspec, ACM digital Library, Science Direct and Springer Link to identify the data location frameworks. Later these data location frameworks are evaluated by conducting a controlled Experiment. Experiment is performed by following the guidelines proposed by Wohlin, C [66]. Results: Three data localization frameworks out of ten, obtained from literature study are considered for the evaluation. The evaluation of these frameworks in Amazon Web Services resulted that replication of three data localization studies is possible, predicting the location of data in US, Europe and Asia close enough accurate and the factors considered from the frameworks are valid. Conclusions: We conclude that from the identified ten frameworks, three data location frameworks are considered for evaluation in which one framework allows verifying the location of data by trusting the information provided by cloud provider and second framework is to verify the location of cloud resources without need of trusting cloud provider, finally the third framework is to identify the replicated files in cloud however this framework also does not need trusting the Cloud provider. These frameworks address the data location problem but in a different way. Now the identified three frameworks are validated by performing a controlled experiment. The activities performed from the three frameworks in the experiment setup allow identifying the data location of web application deployed in US, Europe and Asia. The evaluation of these frameworks in Amazon Cloud environment allowed proposing a checklist that should be considered to manage the web application deployed in cloud regarding data location. This checklist is proposed based on the activities performed in the experiment. Moreover, authors conclude that there is a need for further validation, whether the proposed checklist is applicable for real Cloud user who deploys and manages Cloud resources.