What are the most effective data archiving software options for research?

2 Data Archiving Format

Data archiving format is the way data is structured and encoded for storage and transmission. It affects the quality, compatibility, and longevity of the data. There are two main types of data archiving format: proprietary and open. Proprietary formats are owned and controlled by a specific company or organization, and may require a license or a specific software to access them. Open formats are publicly available and standardized, and can be accessed by various software and platforms. Proprietary formats may offer better performance, security, or functionality, but they also pose the risk of obsolescence, lock-in, or loss. Open formats may offer better interoperability, transparency, or preservation, but they also pose the risk of inconsistency, complexity, or compromise. Some examples of proprietary data archiving formats are DOCX, MP3, and JPEG. Some examples of open data archiving formats are ODF, FLAC, and PNG.

3 Data Archiving Platform

Data archiving platform is the system or service that hosts and delivers archived data. It affects the availability, reliability, and discoverability of the data. There are two main types of data archiving platform: local and cloud. Local platforms are located within the researcher's own institution or organization, and may offer more control, security, or customization. Cloud platforms are located on the internet, and may offer more scalability, accessibility, or collaboration. Local platforms may require more investment, maintenance, or expertise, but they also offer more autonomy, privacy, or compliance. Cloud platforms may require less cost, space, or resources, but they also offer less ownership, protection, or accountability. Some examples of local data archiving platforms are hard drives, servers, and repositories. Some examples of cloud data archiving platforms are Dropbox, Google Drive, and Zenodo.

4 Data Archiving Standards

Data archiving standards are the rules and guidelines that govern the quality, consistency, and ethics of data archiving. They affect the credibility, usability, and impact of the data. There are two main types of data archiving standards: technical and social. Technical standards are the specifications and protocols that define the format, structure, and metadata of the data. Social standards are the principles and policies that regulate the access, sharing, and citation of the data. Technical standards may ensure more interoperability, compatibility, or preservation, but they also require more compliance, documentation, or verification. Social standards may ensure more transparency, accountability, or recognition, but they also require more consent, attribution, or responsibility. Some examples of technical data archiving standards are XML, Dublin Core, and OAIS. Some examples of social data archiving standards are FAIR, DMP, and DOI.

5 Data Archiving Benefits

Data archiving benefits are the advantages and outcomes that result from data archiving. They affect the value, relevance, and contribution of the data. There are two main types of data archiving benefits: internal and external. Internal benefits are the benefits that accrue to the researcher or the research team, such as improving data quality, enhancing data analysis, or facilitating data reuse. External benefits are the benefits that accrue to the research community or the society, such as advancing knowledge, supporting innovation, or informing policy. Internal benefits may increase more efficiency, productivity, or creativity, but they also demand more time, effort, or skill. External benefits may increase more visibility, impact, or reputation, but they also entail more collaboration, dissemination, or evaluation. Some examples of internal data archiving benefits are data validation, data integration, and data mining. Some examples of external data archiving benefits are data publication, data citation, and data sharing.

6 Data Archiving Challenges

Data archiving challenges are the difficulties and obstacles that hinder data archiving. They affect the feasibility, suitability, and sustainability of the data. There are two main types of data archiving challenges: technical and social. Technical challenges are the issues and limitations that relate to the software, format, and platform of the data archiving. Social challenges are the issues and limitations that relate to the standards, benefits, and stakeholders of the data archiving. Technical challenges may involve more complexity, diversity, or volatility, but they also offer more opportunities, solutions, or innovations. Social challenges may involve more uncertainty, variability, or conflict, but they also offer more incentives, agreements, or collaborations. Some examples of technical data archiving challenges are data size, data quality, and data security. Some examples of social data archiving challenges are data ownership, data ethics, and data culture.

7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?