Data management

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

The EBI SRS server—recent developments

Abstract: Motivation: The current data explosion is intractable without advanced data management systems. The numerous data sets become really useful when they are interconnected under a uniform interface—representing the domain knowledge. The SRS has become an integration system for both data retrieval and applications for data analysis. It provides capabilities to search multiple databases by shared attributes and to query across databases fast and efficiently. Results: Here we present recent developments at the EBI SRS server (http://srs.ebi.ac.uk). The EBI SRS server contains today more than 130 biological databases and integrates more than 10 applications. It is a central resource for molecular biology data as well as a reference server for the latest developments in data integration. One of the latest additions to the EBI SRS server is the InterPro database—Integrated Resource of Protein Domains and Functional Sites. Distributed in XML format it became a turning point in low level XML–SRS integration. We present InterProScan as an example of data analysis applications, describe some advanced features of SRS6, and introduce the SRSQuickSearch JavaScript interfaces to SRS. Availability: SRS6 is a licensed product of LION Bioscience AG freely available for academics. The EBI SRS server (http://srs.ebi.ac.uk) is a free central resource for molecular biology data as well as a reference server for the latest developments in data integration.

Knowledge management: what makes complex implementations successful?

Abstract: Purpose – The purpose of this article is to provide an overview of generic knowledge management critical success factors, in conjunction with an overview of the factors that has been found to be critical in implementation journeys in selected South African companies.Design/methodology/approach – Literature research was used.Findings – Most of these factors are very specific to the organizational context and have had a significant impact on the success of implementations. These unique factors include the creation of a shared understanding of the concept of knowledge management, identifying the value of co‐creation of the knowledge management strategy, and positioning of knowledge management as strategic focus area in the organization.Originality/value – Knowledge management is a complex discipline with many factors contributing to successful implementation. The factors that contribute to successful implementation of knowledge management are highly dependent on the environment and specific context, and can ...

Ocean FAIR data services

Abstract: Well-founded data management systems are of vital importance for ocean observing systems as they ensure that essential data are not only collected but also retained and made accessible for analysis and application by current and future users. Effective data management requires collaboration across activities including observations, metadata and data assembly, quality assurance and control (QA/QC), and data publication that enables local and interoperable discovery and access and secures archiving that guarantees long-term preservation. To achieve this, data should be findable, accessible, interoperable, and reusable (FAIR). Here, we outline how these principles apply to ocean data and illustrate them with a few examples. In recent decades, ocean data managers, in close collaboration with international organizations, have played an active role in the improvement of environmental data standardization, accessibility, and interoperability through different projects, enhancing access to observation data at all stages of the data life cycle and fostering the development of integrated services targeted to research, regulatory, and operational users. As ocean observing systems evolve and an increasing number of autonomous platforms and sensors are deployed, the volume and variety of data increase dramatically. For instance, there are more than 70 data catalogs that contain metadata records for the polar oceans, a situation that makes comprehensive data discovery beyond the capacity of most researchers. To better serve research, operational, and commercial users, more efficient turnaround of quality data in known formats and made available through Web services is necessary. In particular, automation of data workflows will be critical to reduce friction throughout the data value chain. Adhering to the FAIR principles with free, timely, and unrestricted access to ocean observation data is beneficial for the originators, has obvious benefits for users, and is an essential foundation for the development of new services made possible with big data technologies.

Big data: extending the business strategy toolbox

Abstract: The business world is rapidly digitizing as companies embrace sensors, mobile devices, radio frequency identi- fication, audio and video streams, software logs, and the Internet to predict needs, avert fraud and waste, understand relationships, and connect with stakeholders both internal and external to the firm. Digitization creates challenges because for most companies it is unevenly distributed throughout the organization: in a 2013 survey, only 39% of company-wide investment in digitization was identified as being in the IT budget (Weill and Woerner, 2013a). This uneven, discon-necked investment makes it difficult to consolidate and simplify the increasing amount of data that is one of the outcomes of digitization. This in turn makes it more difficult to derive insight – and then proceed based on that insight. Early big data research identified over a dozen characteristics of data (e.g., location, network associations, latency, structure, softness) that challenge extant data management practices (Santos and Singer, 2012).