Identifying Threats to Successful Digital Preservation: the SPOT Model for Risk Assessment

Identifying Threats to Successful Digital Preservation: the SPOT Model for Risk Assessment. Sally Vermaaten, Brian Lavoie, Priscilla Caplan.  D-Lib Magazine. September/October 2012.

A successful digital preservation strategy accounts for and lessens the impact of various threats to the digital materials over time. Typologies of threats are practical tools that can aid in the development of preservation strategies. This paper proposes the Simple Property-Oriented Threat (SPOT) Model for Risk Assessment. It defines six essential properties of successful digital preservation.

1. Available for long-term use.
2. Identity allows an object to be discovered and retrieved.
3.  Persistence means objects are intact and can be read from the storage media.
4. Renderability is that the object can be used and retain the significant characteristics. 
5. Understandable by its intended users.
6. Authenticity in that it is what it purports to be.

This model is intended to provide a framework to carry out a risk assessment on the repository contents. Use of the model can help repositories identify previously unaddressed threats, perform ongoing monitoring of key threats, and demonstrate that a repository complies with accepted standards by appropriately managing risks.

Digital preservation threats can be divided into two categories:

1. threats to archived digital content, and 
2. threats to the custodial organization itself.

 The SPOT Model is intended to be a practical tool for repository managers to help identify the sources of risk and develop strategies to mitigate these risks over time. It can be a checklist for identifying threats.
 

Digital Preservation Matters.

The Data Conservancy Instance: Infrastructure and Organizational Services for Research Data Curation

The Data Conservancy Instance: Infrastructure and Organizational Services for Research Data Curation. Matthew S. Mayernik, et al. D-Lib Magazine. September/October 2012.
Digital research data can only be managed and preserved over time through a sustained institutional commitment. Digital research data, if curated and made broadly available, promise to enable researchers to ask new kinds of questions and use new kinds of analytical methods in the study of critical scientific and societal issues. 

The Data Conservancy, a community organized around data curation research, technology development, and community building, is driven by a common theme: the need for institutional solutions to digital research data collection, curation and preservation challenges.
The four main activities of the Data Conservancy are:

1. A focused research program to examine research practices across multiple disciplines in order to understand the data curation tools and services needed to support interdisciplinary research
2. An infrastructure development program for data management and curation services
3. Data curation educational and professional development programs 
4. Development of sustainability models for long term data curation.

Data curation solutions for research institutions must address both technical and organizational challenges. These include context, hardware and software infrastructure, services, and sustainable strategy.

The features needed include a preservation-ready system, customizable user interfaces, flexible data model, ingest and search interface,  and data examination processes.