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  DATA CURATION PRESERVATION (ORGANISATIONAL ISSUES): THE HIDDEN CRISIS IN DATA PRESERVATION Figure 1: The Data Curation Preservation Issues Introduction In cases where the organisation loses valuable research data, the first thought to come to mind will be technological problems such as hardware failure or outdated software. However, there is a growing body of research showing that the real reason why data is lost is organisational issues rather than technological ones. The Accountability Vacuum Data governance within research organisations is seriously underdeveloped. A groundbreaking study from 2003 on e-Science data curation noted that there can be uncertainty as to institutional responsibilities for long-term data management, leading to significant deficiencies in preservation procedures (Digital Archiving Consultancy, 2003). Almost twenty years later, the same issue still applies. Despite organisations' investments in their technological infrastructure, questions related to...

DATA CURATION PRESERVATION ISSUES  The Silent Decay: Confronting Preservation Threats in Digital Materials   The idea that digital materials last forever persist, even though some evidence suggest otherwise. Digital files cannot simply be stored untouched and survive like some old paper documents (Vandecreek, 2012). This post examines the major threats to digital preservation and argues why solid curation plans based on tested methods are urgently needed. The Physical Vulnerability of Digital Media First, digital storage media are physically fragile. Although many assume digital information is safer than paper, it is actually remarkably vulnerable. Digital objects deteriorate over time, just like any physical artifact (Vandecreek, 2012, para. 4). This slow breakdown, often called bit rot , affects disks, servers, and hard drives alike. A case from Harvard illustrates the severity of this problem. Archivists discovered floppy disks stored in warmer climates covered in...

USING AND REUSING DATA At first, I thought that data curation only involved such tasks as keeping data secure and backed up, migrating data formats when necessary, and nothing more. In truth, I was completely off the mark in my assessment. Having data stored on some server is of no value if no one can access it. Data usage Data usage is rather simple. This would be a case of a biologist analysing her field observations. It would also involve a student retrieving data and comparing them with data presented in the study. Now, data reuse is something more complicated and more challenging. Reusing data implies taking data from another source and applying it to solve a problem unknown to the original producers of the dataset. This can mean using census data for migration analysis, combining three clinical studies for a meta-analysis, etc. Data re-use According to Lee & Stvilia (2017), majority of the users engage in activities such as searching, browsing, downloading of content fr...

  STORING DATA: THE CURATOR'S CRUCIAL STEP A data repository may come into mind in terms of a passive digital storage, a mere place for the data to stay there and collect digital dust. Nevertheless, this view is far away from reality. Storing data in a repository is not only an ultimate administrative task but also an important process which will preserve current scientific achievements for future generations. If data is not stored properly, no matter how well a curator cleans the dataset, the latter will become obsolete and useless within several years. How does a repository differ from the cloud storage of personal drive on one's computer? This difference lies in the element of trustworthiness. Trustworthy data repository incorporates FAIR Principles of Findability, Accessibility, Interoperability, and Reusability (Wilkinson et al., 2016), thus providing data a much longer lifespan than the initial research work. The research I undertook made me realize that establishin...

Selecting Research Data for Curation By Cosmas Fletcher Mbewe As a novice in research data management, one of my naive assumptions was that saving all data would require nothing more than purchasing additional hard drives. Lee and Stvilia (2017), however, soon shattered that illusion. In their survey of institutional repository staff, Lee and Stvilia (2017) make it clear that while well-endowed universities are willing to store just about any form of data, there is no established process for assessing which types of data should be stored in the long term. For instance, one interviewee reported that the university had a ten-year retention policy, but none of the datasets had ever reached that mark. But what prevents us from keeping everything then? There is an important counterargument presented by Whyte and Wilson (2010), which refutes my earlier view of the "storage is cheap" concept. The fact is that while the cost of storage decreases, the expenses related to metadata gene...

  DATA COLLECTION AND REPOSITORIES: TOPIC SUMMARY Anyone who has ever done data collection for their research project understands well the chaos of data collection process. One day questionnaires, next day interviews recorded on the laptop, then another two weeks to figure out the meaning behind the strange file name. It is precisely for this reason that knowing how to collect data and work with repositories is so crucial in the MLIS sphere, particularly in regard to the issue of data duration (Borgman, 2015). I shall begin with data collection process. It is a process of obtaining data for its further analysis. Surveys, interviews, observation and automation are some of the methods of data collection widely used in LIS. All of those techniques have their pros and cons, however, one must remember that whatever way one chooses data should be obtained with full observance of ethical principles. Such important issues like informed consent, privacy, and anonymisation should alway...