Access To Digital Data Research Articles

Measuring Digital Data Security Awareness: The Case of Higher Education Institution

Digital data security is of critical importance for individuals and institutions today and encompasses a range of practices and policies aimed at ensuring the confidentiality, integrity and accessibility of digital data. This study aimed to examine the awareness levels of students as well as academic and administrative staff at Ardahan University regarding digital data security and the factors affecting this awareness. A digital data security awareness scale was applied to 324 participants within the scope of the study. The digital data security awareness scale measures the participants' knowledge and behaviors on issues such as password security, safe internet use, data backup and software updates. The data obtained show that the participants generally have a medium to high level of awareness regarding digital data security. It is thought that the results of the research are important in terms of showing that students, as well as academic and administrative staff working at the university, are aware of the protection and security of digital data. In addition, the study reveals the current status of digital data security awareness throughout the university by covering both academic and administrative staff as well as students. This broad scope is intended to help universities better understand the needs of different groups when creating their digital data security policies.

Digital Extended Specimens: Enabling an Extensible Network of Biodiversity Data Records as Integrated Digital Objects on the Internet.

The early twenty-first century has witnessed massive expansions in availability and accessibility of digital data in virtually all domains of the biodiversity sciences. Led by an array of asynchronous digitization activities spanning ecological, environmental, climatological, and biological collections data, these initiatives have resulted in a plethora of mostly disconnected and siloed data, leaving to researchers the tedious and time-consuming manual task of finding and connecting them in usable ways, integrating them into coherent data sets, and making them interoperable. The focus to date has been on elevating analog and physical records to digital replicas in local databases prior to elevating them to ever-growing aggregations of essentially disconnected discipline-specific information. In the present article, we propose a new interconnected network of digital objects on the Internet—the Digital Extended Specimen (DES) network—that transcends existing aggregator technology, augments the DES with third-party data through machine algorithms, and provides a platform for more efficient research and robust interdisciplinary discovery.

Capturing the Silences in Digital Archaeological Knowledge

The availability and accessibility of digital data are increasingly significant in the creation of archaeological knowledge with, for example, multiple datasets being brought together to perform extensive analyses that would not otherwise be possible. However, this makes capturing the silences in those data—what is absent as well as present, what is unknown as well as what is known—a critical challenge for archaeology in terms of the suitability and appropriateness of data for subsequent reuse. This paper reverses the usual focus on knowledge and considers the role of ignorance—the lack of knowledge, or nonknowledge—in archaeological data and knowledge creation. Examining aspects of archaeological practice in the light of different dimensions of ignorance, it proposes ways in which the silences, the range of unknowns, can be addressed within a digital environment and the benefits which may accrue.

Levels of knowledge for object extraction

A paradigm for image interpretation and object extraction that deals explicitly with the levels of abstraction of such processes is described. The central new feature of this paradigm is two intermediate-level processes that deal with construction of symbolic image tokens and with symbolic descriptions of quantities. These intermediate-level processes have access to digital data but produce symbolic, abstract tokens and descriptions. The object extraction system is controlled by a higher-level symbolic process that uses knowledge-based reasoning.