Embedded Files
Large-scale and collaborative research is becoming more commonplace, with many research projects taking a cross-national and interdisciplinary approach to research.
Collaborative Research
Collaborative Research
Setting up a collaborative research environment
Setting up a collaborative research environment
The list of typical requirements for researchers working in a collaborative environment.
Storage and the sharing of documents, plus data files.
The ability to organise documents and data files into folders.
An access control system, which allows authentication and authorisation to be easily managed.
Version control of documents and data files.
File locking to prevent users from simultaneously working on the same file.
Ideally, a discussion platform utilising a forum or wiki format.
Storage and the sharing of documents, plus data files
Storage and the sharing of documents, plus data files
Efficient and effective collaborative research environments require management of document sharing and storage.
The more commonly used resources include GoogleDocs, Google Drive, Microsoft OneDrive, and Dropbox
Advantages: Each of these applications are easy to set up and to use.
Disadvantages: Limited storage capacity; file and backup security concerns
The ability to organise documents and data files into folders
The ability to organise documents and data files into folders
Collaborators should use the same agreed-upon data capture formats
This allows for quick discovery and access to the data
Version control of documents and files
Version control of documents and files
Collaborators should use the same agreed-upon data capture formats
This allows for quick discovery and access to the data
An access control system, which allows authentication and authorisation to be easily managed
An access control system, which allows authentication and authorisation to be easily managed
This is particularly important for sensitive data
File locking to prevent users from simultaneoulsy working on the same file
File locking to prevent users from simultaneoulsy working on the same file
File locking allows changes to be made to documents and data by one person at a time. The advantage of this practice is to ensure the changes to be read first by colleagues before they in turn edit the work.
Use a discussion platform; preferably one that allows for forum/chat functionality
Use a discussion platform; preferably one that allows for forum/chat functionality
An institutional or departmental drive where secure access can be provided to external researchers – for example, a share accessed via a virtual private network (VPN). UK Data Service
A Virtual Research Environment (VRE) or portal environment, such as Basecamp, Huddle, Clinked or MS Sharepoint. UK Data Service
The more common online discussion platforms:
Facebook Dotstorming Flipgrid
StatPlanet Miro Slack
Research data ownership
Research data ownership
Copyright is essential for data sharing and fair dealing
When data are shared or archived, the original copyright owner retains the copyright. UK Data Service
A data archive cannot archive data unless all rights holders are identified and give their permission for the data to be shared. Secondary users need to obtain copyright clearance before data can be reproduced. However, exceptions exist under the fair dealing concept. UK Data Service
Creative Commons is a nonprofit organization that helps overcome legal obstacles to the sharing of knowledge and creativity to address the world’s pressing challenges.
Authors give away the copyright rights to their work to the publisher when the article is published in the traditional publication process.
However, when authors publish their work via the Open Access process, they retain the copyright of that work. It is important that authors assign a Creative Commons license to determine how their work may be used and shared.
Discover, Integrate & Analyse
Discover, Integrate & Analyse
This stage of the Research Process is a time for reviewing the RDM plan
New data discovery and data creation
Integration of new data into current data
Data analysis
Attributions of original data sets
Data discovery
Data discovery
Data discovery is the process of visually navigating data and applying analytics in order to detect patterns, gain insight, answer specific questions, and derive value from the data.
Data integration is the process of combining data from multiple source systems to create unified sets of information for both operational and analytical uses. Source: Techtarget
The primary objective is to produce consolidated data sets that are clean and consistent and meet the information needs of different end users.
Data analysis
Data analysis
Data interpretation and analysis is the process of assigning meaning to the gathered information and ascertaining “the conclusions, significance, and implications of the findings
Source: University of Pittsburgh & University of Oxford
Data visualisation
Data visualisation
Data Visualisation is the visual representation of data, and is used to enable people to both understand and communicate information through:
graphical (Data visualization is the graphical representation of information and data. By using visual elements like charts, graphs, and maps, data visualization tools provide an accessible way to see and understand trends, outliers, and patterns in data )
schematic (It means that right data must be identified before. Semantic technologies provide new ways for accessing data and acquiring knowledge. The underlying structures allow finding information easier, gathering meanings and associations of the data entities and associating the data to users' knowledge)
Data visualisation tools
Data visualisation tools
A variety of tools are available that support data discovery, integration, analysis, and visualization
Therefore the tools enable
tracing the use of data sets and data elements
attribution to the creators of the original data sets, and
identifying effects of errors in the original data sets or elements of those sets on derived data sets
UK Data Service Training opportunity
Today social scientists use software in the majority of their research. Learn more about the most commonly used software tools and start using them. Includes guidance and links to Nesstar, QualiBank, UKDS.Stat, R, Stata, SPSS, Python and more.
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