Data Management: The Data Life Cycle

The scientific site of Kiel provides support for projects with data management requirements due to project size or interdisciplinarity. This infrastructure is the Kiel Data Management Infrastructure (KDMI) and was initially created by SFB574, SFB754, Excellence Cluster ‘The Future Ocean‘ and the GEOMAR | Helmholtz Centre for Ocean Research Kiel. To achieve public data availability from publicly funded projects by the end of the funding period it is necessary to initiate the data acquisition during the data creation process. Accordingly the KDMI uses a three level approach to achieve this goal in SOPRAN III. Data management is al- ready involvedin the planning of expeditions or experiments. The resulting schedule for data files can be used by the project coordinationto increase the efficeny of data sharing within SOPRAN III. The scientists provide files with basic metainformation, which are available within the virtual research environment as soon as possible to all project members. Final data will be transferred to PANGAEA for long term availability when the data are analysed and interpreted in a scientific publication or by the end of SOPRAN III. The Kiel Data Management Team offers a portal for all GEOMAR and University Kiel marine projects. This portal will be used in SOPRAN III in combination with PANGAEA to fulfill the project’s data management requirements and to enhance the data sharing within SOPRAN III by a file sharing environment for preliminary data not yet suitable for PANGAEA

NHEP Data Management Plan

A goal of the New Hampshire Estuaries Project (NHEP) and its monitoring program is to promote a cooperative effort by all agencies and organizations who participate in monitoring activities, in order to maximize the usefulness of current monitoring efforts and available data. To achieve this goal, it is necessary to effectively manage the large volume of existing information as well as new information that will be developed through the NHEP monitoring program. Data and information about NH’s estuaries now exists in multiple formats within a variety of organizations. Existing monitoring programs are designed to meet the missions of the various implementing organizations. The organizations use different procedures and protocols for data collection, analysis, storage, and reporting. Coordination of data management among organizations is currently limited. This Data Management Plan contains protocols for data reporting to the NHEP to facilitate data integration. Different protocols will be applied to different types of data (e.g., chemical, geospatial, and biological). The protocols will be considered contract requirements for NHEP monitoring programs and recommended guidelines for other partners. This plan also includes protocols for conducting quality assurance tests on water quality data to ensure the integrity of the NHEP indicators

Data set management

The data sets currently supported by the Pilot Climate Data System (PCDS) are listed, many of which are Level II and Level III NImbus-7 data sets. Those data sets planned for future access through the PCDS were also listed, and their current installation status was stated. The tasks involved in supporting data sets within the PCDS were identified and described. After a data set is approved for implementation into the system and communication with the data producers is established, the information for the detailed catalog entry is gathered. This information then is reviewed with the scientists involved before producing a catalog summary. Once this is done, the catalog information can be provided to users, even before the data set is installed. The next several tasks involve software development and can prove to be the most time-consuming aspect in the data set support. These tasks can be simplified if the data producers provide complete and accurate documentation of their product. Software for reading and interpreting the data sets is developed and the data sets, or portions therefore, that will be made available for use within the PCDS are inventoried. Users can access this information via the INVENTORY Subsystem of the PCDS

Data management for earth observations

The management of NASA earth observation data is discussed. User requirements are identified, as well as means to facilitate data acquisition. It is shown that LANDSAT data can be preprocessed to condense data into a more accessible format, thus reducing data acquisition costs

Data Management Roles for Librarians

In this Chapter:● Looking at data through different lenses● Exploring the range of data use and data support ● Using data as the basis for informed decision making ● Treating data as a legitimate scholarly research produc

Cherenkov Telescope Array Data Management

Very High Energy gamma-ray astronomy with the Cherenkov Telescope Array (CTA) is evolving towards the model of a public observatory. Handling, processing and archiving the large amount of data generated by the CTA instruments and delivering scientific products are some of the challenges in designing the CTA Data Management. The participation of scientists from within CTA Consortium and from the greater worldwide scientific community necessitates a sophisticated scientific analysis system capable of providing unified and efficient user access to data, software and computing resources. Data Management is designed to respond to three main issues: (i) the treatment and flow of data from remote telescopes; (ii) "big-data" archiving and processing; (iii) and open data access. In this communication the overall technical design of the CTA Data Management, current major developments and prototypes are presented.Comment: 8 pages, 2 figures, In Proceedings of the 34th International Cosmic Ray Conference (ICRC2015), The Hague, The Netherlands. All CTA contributions at arXiv:1508.0589

Redundant data management system

Redundant data management system solves problem of operating redundant equipment in real time environment where failures are detected, isolated, and switched in simple manner. System consists of quadruply-redundant computer, input/output control units, and data buses. System inherently contains failure detection, isolation, and switching function

Exploring sensor data management

The increasing availability of cheap, small, low-power sensor hardware and the ubiquity of wired and wireless networks has led to the prediction that `smart evironments' will emerge in the near future. The sensors in these environments collect detailed information about the situation people are in, which is used to enhance information-processing applications that are present on their mobile and `ambient' devices.\ud \ud Bridging the gap between sensor data and application information poses new requirements to data management. This report discusses what these requirements are and documents ongoing research that explores ways of thinking about data management suited to these new requirements: a more sophisticated control flow model, data models that incorporate time, and ways to deal with the uncertainty in sensor data