Managing Data for Scholarly Communications, Part Two: Technical Management

Introduction

Dataset Identification & Citation: DataCite and EZID

One of the challenges researchers face is consistently finding, citing, and getting credit for their research datasets. Persistent identifiers, and the establishment of best practices for citing well-preserved datasets, offer a solution to this problem. Joan will introduce the work of DataCite, an international organization that works to improve the scholarly infrastructure around datasets, and EZID, a service built for simple identifier management, including DataCite DOIs, other long-term identifiers.

Digital Library Services in the Cloud

The Texas Digital Library (TDL) is a consortium of higher education institutions in Texas that provides shared services in support of research and teaching. For his presentation, Mark will describe how TDL recently moved a variety of services to the Amazon cloud. The primary reason for TDL's initial work using cloud services was as a DRP (disaster recovery plan) for a planned data center move. The centerpiece of this DRP was the duplication of services in the Amazon EC2 cloud (Amazon 2011b) -- an extension of the idea of having an off-site backup for data -- as in the cloud duplication case, TDL also has an off-site backup of the services themselves. Other motivations were that the elastic nature of cloud services (both compute and storage) would allow TDL to pay only for what it actually uses, as opposed to using its own hardware, which incurs cost regardless of utilization. Finally, TDL also envisioned a potential personnel savings: owning hardware requires an organization to staff competencies (e.g., network architecture expertise) that it could effectively outsource by using cloud services. Even if staffing these competencies were still necessary, the resources committed to those skills could potentially be reduced.

Data Governance and Legal Interoperability

Sharing and integrating data are common requirements of research projects but are often difficult for a variety of technical, cultural, policy and legal reasons. Data governance is the system of decision rights and accountabilities that describe who can take what actions with what data, and when, under what circumstances, using what methods. It includes laws and policies associated with data, as well as strategies for data quality control and management, in the context of organizations. It includes the processes that insure important data are formally managed throughout an organization, including business processes and risk management. Data governance ensures that data can be trusted and that people can be made accountable for actions affecting the data. While the community is making progress on the technical and cultural issues, the data governance issues around data are only now being recognized and addressed.