Data management

About: Data management is a research topic. Over the lifetime, 31574 publications have been published within this topic receiving 424326 citations.

Modular scalable system for managing data in a heterogeneous environment with generic structure for control repository access transactions

Abstract: A Data Management System has a plurality of data managers and is of a layered architecture. The system performs with a data manager and with a user input via an API a plurality of process on data residing in heterogeneous data repositories of said computer system including promotion, check-in, check-out, locking, library searching, setting and viewing process results, tracking aggregations, and managing parts, releases and problem fix data under management control of a virtual control repository having one or more physical heterogeneous repositories. The system provides for storing, accessing, tracking data residing in said one or more data repositories managed by the virtual control repository. User Interfaces provide a combination of command line, scripts, GUI, Menu, Web Browser, and other interactive means which maps the user's view to a PFVL paradigm. Configurable Managers include a query control repository for existence of peer managers and provide logic switches to dynamically interact with peers. A control repository access layer provides a common process interface across all managers, which utilizes a virtual table paradigm to standardize communication with the control repository. Command translators map the generic control repository accesses into the appropriate format for interfacing with the underlying physical embodiment of the control repository.

Data management system for automatically accessing, maintaining, propagating user data among plurality of communities, each of which contains plurality of members

Abstract: The present community membership data management system identifies each user and their associated communities of interest. Each community has a user defined permission to access a subset of the user's data, which data is shared among some or all of the members of that community. When the user's data is updated, the update is automatically propagated to all of the identified associated communities of interest and the members of those communities who have permission to receive that data. Thus, each user of the present community membership data management system has their computerized calendar and address book system automatically populated with data, which data is continuously and automatically updated. The confidentiality and security of the user data is maintained by defining a set of permissions among the communities, members of communities and for each user to ensure that the user maintains control of the propagation of their data. Each user therefore maintains a “virtual user image” in each of the communities, where the members of that community view only one aspect of the user's personal data.

Answering Queries using Humans, Algorithms and Databases

Abstract: For some problems, human assistance is needed in addition to automated (algorithmic) computation. In sharp contrast to existing data management approaches, where human input is either ad-hoc or is never used, we describe the design of the first declarative language involving human-computable functions, standard relational operators, as well as algorithmic computation. We consider the challenges involved in optimizing queries posed in this language, in particular, the tradeoffs between uncertainty, cost and performance, as well as combination of human and algorithmic evidence. We believe that the vision laid out in this paper can act as a roadmap for a new area of data management research where human computation is routinely used in data analytics.

Method and system for e-commerce and related data management, analysis and reporting

Abstract: A system transacting e-commerce and related data management, analysis and reporting includes a database, first and second clients, and first through fourth servers communicatively connected to an internet network. The database stores a variety of information relating to customers and has a cost reduction database portion storing cost reduction information. The first and second client have access to the on-line system. The first server maintains a commercial website. The second server supports a consultant interface on the internet network. The third server imports financial information into the database. The fourth server receives purchasing and financial information. The filter generates purchasing options and calculates a purchase price. A first program dynamically displays a cost reduction list. A second program analyzes a customer's purchasing history for cost effectiveness and forecasts future plans for improved purchasing implementation. A default pricing mechanism selectively uses default pricing values to generate a bid.

Sharing health data: good intentions are not enough

Abstract: Epidemiologists and public health researchers are moving very slowly in the data sharing revolution, and agencies that maintain global health databases are reluctant to share data too. Once investments in infrastructure have been made, recycling and combining data provide access to maximum knowledge for minimal additional cost. By refusing to share data, researchers are slowing progress towards reducing illness and death and are denying a public good to taxpayers who support most of the research. Funders of public health research are beginning to call for change and developing data sharing policies. However they are not yet adequately addressing the obstacles that underpin the failure to share data. These include professional structures that reward publication of analysis but not of data, and funding streams and career paths that continue to undervalue critical data management work. Practical issues need to be sorted out too: how and where should data be stored for the long term, who will control access, and who will pay for those services? Existing metadata standards need to be extended to cope with health data. These obstacles have been known for some time; most can be overcome in the field of public health just as they have been overcome in other fields. However no institution has taken the lead in defining a work plan and carving up the tasks and the bill. In this round table paper, we suggest goals for data sharing and a work plan for reaching them, and challenge respondents to move beyond well intentioned but largely aspirational data sharing plans.