Implementation of Collaborative Workspace for Petrophysics Asset Teams By Promoting Centralized Project Data Management

2019 ◽  
Author(s):  
Abdul Fareed ◽  
Aqeel Tariq ◽  
Usman Sani ◽  
Musab Abdul Rehman ◽  
Arshad Hussain Palekar ◽  
...  
Keyword(s):  
Data Management ◽  
Collaborative Workspace ◽  
Project Data

Integrating GIS and Data Management Within the Project Environment

2008 ◽  
Author(s):  
Hugo Guerrero
Keyword(s):  
Data Management ◽  
Project Teams ◽  
The Other ◽  
Geospatial Technology ◽  
Right Of Way ◽  
Project Environment ◽  
Other Hand ◽  
Project Data ◽  
Minimum Work ◽  
Project Level

Today, much of the focus on integrating Geospatial technology and data has been on the operations side of the business. Not much attention has been paid to the workflow within the project environment even though most of the data that is used to populate enterprise datasets is created or prepared as a requirement of a project; that said; it is early on at the project level when geospatial integration needs to be implemented and incorporated into the project workflow. On the other hand, project teams have historically focused on strictly satisfying the needs of the project. This is typically limited to the minimum work required to design, permit & build a given work scope. This approach has left many companies with the task of paying high costs for the project data to be translated, captured or in some cases recreated after the fact. Too many times, Gas Company X hires multiple consultants with different disciplines responsible for different project scope items (i.e. Environmental, Right-of-way, Engineering, etc...). Each company has established methods for preparing and organizing their respective data without ever thinking how Gas Company X intends on using the data for other enterprise needs during the project and after the project has been completed. This presentation outlines methods by which companies can require that their project consultants produce project data with geospatial integration in mind. This includes identification of required resources & workflows to specify and manage the data that is prepared and/or collected in a structured environment that is geospatially & data aware.

scholarly journals Data Management

2021 ◽  
pp. 193-225
Author(s):  
Carolin Helbig ◽  
Uwe-Jens Görke ◽  
Mathias Nest ◽  
Daniel Pötschke ◽  
Amir Shoarian Sattari ◽  
...  
Keyword(s):  
Data Management ◽  
Research Project ◽  
Entire Data ◽  
Data Lifecycle ◽  
Project Data ◽  
Institutional Unit

AbstractData management includes the development and use of architectures, guidelines, practices and procedures for accurate managing of data during the entire data lifecycle of an institutional unit or a research project. Data are defined as different information units such as numbers, alphabetic characters, and symbols that are particularly formatted and can be processed by computer. The data in the project is provided by various actors which can be GeomInt partners, their legal representatives, employees, and external partners.

scholarly journals The 1000 Genomes Project: data management and community access

2012 ◽  
Vol 9 (5) ◽  
pp. 459-462 ◽  
Author(s):  
Laura Clarke ◽  
◽  
Xiangqun Zheng-Bradley ◽  
Richard Smith ◽  
Eugene Kulesha ◽  
...  
Keyword(s):  
Data Management ◽  
1000 Genomes Project ◽  
1000 Genomes ◽  
Project Data ◽  
Community Access

Research data management services for a multidisciplinary, collaborative research project

2015 ◽  
Vol 49 (4) ◽  
pp. 494-512 ◽  
Author(s):  
Constanze Curdt ◽  
Dirk Hoffmeister
Keyword(s):  
Data Management ◽  
Data Storage ◽  
Research Data ◽  
Research Project ◽  
Content Type ◽  
Research Data Management ◽  
Metadata Schema ◽  
Interdisciplinary Research Project ◽  
Project Data ◽  
User Friendly

Purpose – Research data management (RDM) comprises all processes, which ensure that research data are well-organized, documented, stored, backed up, accessible, and reusable. RDM systems form the technical framework. The purpose of this paper is to present the design and implementation of a RDM system for an interdisciplinary, collaborative, long-term research project with focus on Soil-Vegetation-Atmosphere data. Design/methodology/approach – The presented RDM system is based on a three-tier (client-server) architecture. This includes a file-based data storage, a database-based metadata storage, and a self-designed user-friendly web-interface. The system is designed in cooperation with the local computing centre, where it is also hosted. A self-designed interoperable, project-specific metadata schema ensures the accurate documentation of all data. Findings – A RDM system has to be designed and implemented according to requirements of the project participants. General challenges and problems of RDM should be considered. Thus, a close cooperation with the scientists obtains the acceptance and usage of the system. Originality/value – This paper provides evidence that the implementation of a RDM system in the provided and maintained infrastructure of a computing centre offers many advantages. Consequently, the designed system is independent of the project funding. In addition, access and re-use of all involved project data is ensured. A transferability of the presented approach to another interdisciplinary research project was already successful. Furthermore, the designed metadata schema can be expanded according to changing project requirements.

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