Data Ownership: Analysis Of Ownership Models And Creating A Data Ownership Policy

We have examined how data gathering has increased exponentially over the past few years. For this paper, you should consider who should own the data being gathered.

Provide and ethical analysis supporting your conclusion, and take into consideration the implication of your position – e.g., if you think there should be a change in the way data ownership is handled, how will the proposed change affect our interactions with the companies that are currently creating large databases?

Data ownership generally refers to the process of having rights that are legal along with having an overall control of a particular portion of the data or over the dataset elements. Data ownership is associated with providing information about the entities who are the rightful owner of the data assets and the acquisition, along with the usage and distribution of the policies which assets that determined by the data owners.

Data ownership can also be considered to be the primary data governance process that is responsible for providing information or details about the legal ownership that the organization is having upon the data spread all across the enterprise [1]. The particular organization or the data owners are having the capability of creating editing, modifying sharing and lastly restricting the data access. Data ownership is also associated with defining the ability of the data owners to assign or share or surrender all the privileges to the third-party users.

Implementation of this concept is seen in organization of different sizes which ranges from medium to large enterprise which are having huge repositories of distributed or centralized data elements. The data owners are also associated with claiming the possession as well as the copyright of such type of data so as to make sure that they are having control over the data and to have the right of taking legal actions in cases when the ownership is illegitimately breached by entities both external as well as internal.

There are several issues which come forward when the ownership is being distributed throughout an enterprise [2]. A model has been proposed regarding the ownership where the critical point revolves around the values.

The centralized ownership models are consisting a single entity who are entirely accountable for owning all the data of an enterprise. Centralization is associated with the implication of the fact that all the activities related to the ownership activities is to be coordinated from one single control point. Besides this the metadata coordination, along with sourcing of the information and many more are also done from a single control point. The benefits of the centralized ownership include added values along with the determining if the costs that is related to the centralization [3]. The costs mainly involves the increased overhead management, integration of the system, bureaucracy and many others. The major benefit of this standardization of the enterprise regarding the data and the systems, the capability of using the merged data so as to discover more knowledge and increase in the leverage while dealing with the suppliers of external data.

The decentralized model would be consisting of the different roles of ownership which are assigned to the entities having various areas of interest. Decisions needed for choosing the decentralization is mainly associated with the implication of the fact that, the services which are having added value and are received from the centralized data control is greater than the offset provided by the costs related to it. Contrarily it is observed that the organization are not explicitly opting for the decentralized control. So, the major question that is put forward due to this reason is that the weather the migration form the decentralized ownership model to the centralized ownership model would be associated with increasing the value that the enterprise knowledge base is having or not.

Solution to the question sated above is very easy. For doing that a process of identification is to be involved for the parties interested and are associated with all the data sets [4]. Besides this the interest of each party is to be identified along with the roles which are related to all the sets of data. Followed by this is the analysis of the roles and responsibilities so as to assign them to the right parties. All these activities need to be included in the data ownership policies which would be responsible for the incorporation of all the governance rules related to data ownership and usage in a particular enterprise.

The data ownership policy is nothing but a tool that is utilized for the purpose of establishing certain roles and responsibilities that are associated with the data ownership as well as the data accountability. The major reason lying behind the usage of the data ownership policy is, avoidance of the various type of complications along with hashing out the various strict definitions related to ownership [5]. Some of the important features that must be enumerated by the data ownership policy includes the following:

• Managers present at the senior level should be associated with providing support to the enforcement of the policies that has been enumerated.
• Each and every sets of data should be covered under the data policy.
• Presences of an ownership model for each of the data set.
• The roles which are associated with the data ownership
• The responsibilities that each of the role is having
• Process of providing solution to any kind of disputes

Certain steps exist which are need for providing definition to the data ownership policies and these steps includes the following:

• Identification of the parties or the stakeholders who are interested and are associated with the data of an enterprise [6]. Which means this mainly includes the identification of the managers of senior level who would be associated with providing support to the policy enforcement
• The data sets which are covered under the policy should be cataloged.
• Determination of the ownership model that is being used along with determining if the model is to be used continuously or is to be replaced.
• Determination of the roles and responsibilities which have been implemented and which not has been implemented [7]. Proper assigning of the responsibilities for each of the roles needs to be done along with assigning the roles to the parties who are interested.
• Maintenance of a registry which would be helping in keeping track of the policies along with the roles, and all other information which are relevant.

Various roles would be included in the reporting structure in which a clear line of responsibilities would be provided that is correspondent to the ownership degree. It is to be noted that assigning of certain responsibilities to multiple roles is done and this causes overlapping of the role, whose governance is necessarily to be included in the reporting structure [8]. During this type of phase, the senior manager who is responsible for the roles and responsibilities of the ownership is to be different form the stakeholders of the organization.

Conclusion:

Creation of the ownership registry by making use of the catalogue for data and assigning of the roles is to be done. It is possible to query the enterprise log so as to determine who is ultimately having the responsibility of the data set. Access to the ownership registry is to be provided to all the parties interested specially when there is a requirement of new data or when ever a conflict arises that needs to be resolved.

Managing the ownership registry would be including the requirement of keeping a pulse upon the enterprises and the major reason and the major reason behind this is that it is not usual for the turnover the employee to have an effect upon the data management structure. Additionally, it is also to be noted that whenever a set of data that is totally new and is being added to the governance should be associated with following the policies of data ownership. Along with this taking of decisions related to the entry of new sets data should be necessarily be included in the registry so as to make the entire process remain ethical.

References:

• Mikk, K.A., Sleeper, H.A. and Topol, E., Patient Data Ownership—Reply. Jama, 319(9), pp.935-936, 2018.
• Mursaleen, L.R., Stamford, J.A., Jones, D.A., Windle, R. and Isaacs, T., Attitudes Towards Data Collection, Ownership and Sharing Among Patients with Parkinson’s Disease. Journal of Parkinson's disease, 7(3), pp.523-531, 2017.
• Roski, J., Bo-Linn, G.W. and Andrews, T.A., Creating value in health care through big data: opportunities and policy implications. Health affairs, 33(7), pp.1115-1122, 2014.
• Perkmann, M. and Schildt, H., Open data partnerships between firms and universities: The role of boundary organizations. Research Policy, 44(5), pp.1133-1143, 2015.
• Kostkova, P., Brewer, H., de Lusignan, S., Fottrell, E., Goldacre, B., Hart, G., Koczan, P., Knight, P., Marsolier, C., McKendry, R.A. and Ross, E., Who owns the data? Open data for healthcare. Frontiers in public health, 4, p.7, 2016.
• Anheier, H.K., Nonprofit organizations: Theory, management, policy. Routledge, 2014.
• Powers, K. and Henderson, A.E., Linking Planning, Ownership, Governance, and Execution: Fundamental Steps in Building an Effective Data Culture. In Cultivating a Data Culture in Higher Education(pp. 30-44). Routledge, 2018.
• Görg, C., Wittmer, H., Carter, C., Turnhout, E., Vandewalle, M., Schindler, S., Livorell, B. and Lux, A., Governance options for science–policy interfaces on biodiversity and ecosystem services: comparing a network versus a platform approach. Biodiversity and Conservation, 25(7), pp.1235-1252, 2016.