The History Data Management Lifecycle (HDML) model

The History Data Management Lifecycle (HDML) model

5. History Data Management Lifecycle (HDML)

5.3 Research

Preserve 

The research phase incorporates several aspects of the data management process.

Preservation of the data is crucial to the availability and accessibility during the project, and possibly beyond.

  • Identify how the data or material will be maintained during the project
  • Consider whether maintenance is required after the end of the project
  • Generate a plan to secure the data for the required period

 

Example:

“File will be stored on laptop, on a backup drive, a USB data stick and the University Server. The data will be required for at least 3 years after the end of the project; the University has agreed to preserve the data for this period.”

 

Conceptualise

Plan how the data will be generated, created or incorporated into the research. Consider how the data will be captured, and how/where it will be stored.

 

Example:

“Images (photographs) taken on location will require an eight megapixel camera, reasonable lighting and reasonable weather conditions. Several attempts may need to be made to capture the relevant images. The images will be formatted into .jpg format and saved on a local laptop, a USB drive and the institution server.”

 

Create or Receive

As part of the research process, new and innovative data may be created. Similarly, data new to the project may come to light and be received for incorporation into the project. These forms of data will need to be processed in much the same way as other data. A clear description needs to be provided, preservation needs to be considered, and a concept of how the data will be included in the project needs to be formed.

 

Example:

“Data generated from the logbooks and diaries will be entered into a database which will be saved in a format to be agreed with the project supervisor. It is envisaged that the database will not exceed 2000 entries and total about 1 Mb in size. The resulting database, once populated will be used to extract tables for inclusion in the thesis as appropriate.

 

 “Similarly, data identified as the project develops will be saved in a useable and robust format (e.g. PDF files).”

 

Appraise and Select

Data must be evaluated to determine its validity for the research process. It is vital that documented guidance, policies and legal requirements are adhered to.

 

Example:

“The proposed oral history interviews will require research into local [institution] policies to ensure compliance with local regulations, and to act in accordance with applicable laws such as the Data Protection Act. This information will be acquired from Supervisors, Project Managers and Research Leads.”

 

Ingest

Data gathered or created will need to be placed into an archive, repository or data centre. This goes beyond simply holding data on a local computer or a data stick. Transfer to a robust repository is strongly recommended. Again, local institution policies must be adhered to when data is transferred.

 

Example:

“Apart from storage on a  local computer, the data will be stored on a institution server. The data transfer will be facilitated by IT Services and/or Library/Archive services. Policies relating to volumes and formats will be adhered to.”

       

 

Preservation Action

Based on the planning carried out in the previous review phase, the long-term preservation of the data must be enacted. This may require the researcher to comply with a strict file naming process, removing inappropriate, irrelevant and/or repeated information. The file structures and integrity of the data must be checked and verified.

 

Example:

            “A specific file naming format will be applied in the following form:- NumericDate_ProjectName_FileDetails.filetypeextension

> 20131204_ENACT_localawarenessofarchives.doc

> 20131213_ENACT_michaelbirdinterview.wav

 

“Files will be checked (read/listened to/viewed/run) to verify their integrity, and accurately named as shown above. Any repeats or varying versions will attract different numeric dates, while repeated or irrelevant data may be deleted.”

 

 

Storage

Once the relevant checks have been carried out, the data should be stored in the appropriate location.

 

Example:

“Institutional repository or server as indicated by IT Services.”