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User:He3525/Digital Curation Centre

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Throughout its history the DCC has been an active organisation in the realm of digital preservation. In partnership with other institutions, the DCC has created and developed tools for tackling issues in digital preservation and curation. Such tools include a lifecycle model for data curation[1], a risk assessment for digital repositories[2][3], and an interview protocol to assist institutions in understanding their research data collections.[4][5]

Developments[edit]

Curation Lifecycle Model[edit]

The Curation Lifecycle Model, developed by the DCC, was first published in 2007 and finalised in 2008. It is a graphic which describes the overarching digital curation process with archival and preservation processes being only portions of this overall digital curation process. The model outlines various curation actions. There are full lifecycle actions, which include description and representation information, preservation planning, community watch and participation, and curate and preserve. There are sequential actions, which include conceptualise; create or receive; appraise and select; ingest; preservation action; store; access, use, and reuse; and transform.[1][6] Finally, there are occasional actions, which include dispose, reappraise, and migrate.[7][6]

Full lifecycle actions are reoccurring actions that pertain to each phase of a digital object or databases’ lifecycle and curation process.[1][6][7] The full lifecycle actions indicate the need to create quality metadata to represent a digital object, the importance of planning how to preserve an object throughout the entirety of the curation process, the necessity of collaborating with a community in order to adapt new standards, and the essential task of adhering to any preconceived steps to manage the curation and preservation of the digital object.[6][8]

Sequential actions, unlike full lifecycle actions, occur in a particular order as part of a digital object’s curation lifecycle. These steps are always performed in order, though can be repeated indefinitely as long as the object’s curation continues to be a priority.[1][6][7]

Occasional actions including dispose, reappraise, and migrate represent activities undertaken only when certain criteria regarding the object’s lifecycle are met. For example, when an object is appraised (a sequential action that always occurs in the lifecycle of a digital object’s curation) if it adheres to or, more aptly, doesn’t adhere to certain institutional curation policies, it can be disposed of or reappraised—both of which are occasional actions in the lifecycle.[1][6][7]

The DCC Curation Lifecycle Model is especially relevant to three key participants in the digital curation process: data creators, data archivists, and data reusers. The model highlights the importance of data creation, such as metadata, in successful, sustainable curation practices. This is relevant to data creators. Data archivists will find the model beneficial as an outline of the necessary processes to guarantee the thoroughness of their curation actions. Finally, because the model outlines the aforementioned steps, it prompts the successful curation of data and, therefore, the ability of that data to be accessed in the future and reused.[1]

Digital Repository Audit Method Based on Risk Assessment[edit]

DRAMBORA or the Digital Repository Audit Method Based on Risk Assessment is another development of both the DCC and DigitalPreservationEurope. This is a tool, published in 2007, which can be used by digital repositories to self-assess their own organisations and the preservation activities undertaken therein.[2] It was developed in the aspiration of working toward a standardised certification of all digital repositories. The DRAMBORA methodology acts as a checklist to ensure that a particular institution adheres to a set of standards. The self-assessment undertaken using the DRAMBORA methodology is intended to determine weaknesses within a digital repository that could affect its credibility.[3]

Data Asset Framework[edit]

The Data Asset Framework or DAF is a data audit methodology developed by HATII at the University of Glasgow in conjunction with the Digital Curation Centre. Originally the Data Audit Framework, the Data Asset Framework is an interview protocol utilised by educational institutions to better understand their growing research data collections. With this tool, institutions can learn to manage their data more effectively.[4] The audit allows institutions to assess their data collections, determine their state, and measure the worth of the data through the assessment of “five core questions:

1.     What data assets currently exist?

2.     Where are these assets located?

3.     How have these been managed to date?

4.     Which of these assets need to be maintained in the long term?

5.     Do current data management practices place these assets at risk?”[5]

By performing this audit, a comprehensive registry of data assets is compiled, which can then be used by the institution to improve their management of those assets. The intent of DAF is to raise awareness within an institution regarding their data management practices. Auditing data assets creates a better understanding of the digital collections owned by an institution and allows them to more efficiently organise their data, structure their data, and determine accountability for said data, all while minimising the potential loss of assets in the future and increasing accessibility.[5] The goal of the Data Asset Framework is to create a standard for the management of a library’s research data that can then be utilised industry-wide.[4]

References[edit]

  1. ^ a b c d e f Oliver, G., & Harvey, D. R. (2016). Digital curation (2nd ed.). Neal-Schuman.
  2. ^ a b Brown, A. (2013). Practical digital preservation: A how-to guide for organizations of any size. Facet Publishing.
  3. ^ a b Bermès, E. (2007). Risk management and digital repositories: The case of DRAMBORA. International Preservation News, (41), 8.
  4. ^ a b c Ogier, A., Hall, M., Bailey, A., & Stovall, C. (2014). Data management inside the library: Assessing electronic resources data using the Data Asset Framework methodology. Journal of Electronic Resources Librarianship, 26(2), 101-113. https://doi.org/10.1080/1941126X.2014.910406
  5. ^ a b c Jones, S., Ross, S., Ruusalepp, R., & Dobreva-McPherson, M. (2009). Data Audit Framework Methodology. HATII, University of Glasgow. https://doi.org/10.13140/RG.2.1.3389.0969
  6. ^ a b c d e f Constantopoulos, P., Dallas, C., Androutsopoulos, I., Angelis, S., Deligiannakis, A., Gavrilis, D., Kotidis, Y., & Papatheodorou, C. (2009). DCC&U: An extended digital curation lifecycle model. International Journal of Digital Curation 4(1), 34-45. https://doi.org/10.2218/ijdc.v4i1.76
  7. ^ a b c d Mason, S. (2018). Digital preservation at Oxford and Cambridge training programme pilot. University of Oxford. Retrieved December 16, 2021, from https://libguides.bodleian.ox.ac.uk/digitalpreservation/digitalcurationlifecycle
  8. ^ Iris, X., & Krystyna, M. K. (2016). Discover digital libraries. Elsevier. http://dx.doi.org/10.1016/B978-0-12-417112-1.00011-9