Data Documentation and Informed Consent in Research

Introduction

The authenticity of research outcome, more than ever before is predicated on certain extended variables or scale of measurement which research itself brought about by its continued scientific approach. Until recently, validity and reliability of a research work was silent on issues such as ethics in research, particularly as it affects human subject research method. During the past few years an increasing sensitivity has emerged to the importance of data documentation and availability, especially in education and the social sciences. Most recently, Huschka and Wagner (2012) have shown that data documentation and its availability are requirements not only for good scientific practice but also for good methodological work. Many researchers, however, still lack experience with data management and documentation. Since funding organizations and professional associations are increasingly expecting researchers to share all scientific outcomes (including data) from publicly funded projects, data documentation and informed consent in research have become important cross-disciplinary issues. Even though several institutions have called for the professionalization of research data management, precise knowledge of effective data documentation is still missing (Walters, 2009). However, in contrast to other disciplines, education, social sciences and humanities are confronted with specific challenges that currently prevent effective data management and documentation. These challenges include, e.g., privacy issues and the particular properties of qualitative data (non-standardized, context-sensitive, and informed consents etc.). Hence, as studies move on and researches meet with challenges bordering on authenticity defense and ethic violation, ethical solutions have since been sought which generated new research frontiers for scholars in areas like moral imagination, shareholders consultation, dialogue and other frontiers with a view to solving the problems several crises like lack of credibility and risk of data loss which modern scientific and academic research currently face (Büttner, Hobohm & Müller, 2011; Gläser & Laudel, 2008).