Scientists are often steered by common convention, funding agencies, and journal guidelines into a hypothesis-driven experimental framework, despite Isaac Newton's dictum that hypotheses have no place in experimental science. Some may think that Newton's cautionary note, which was in keeping with an experimental approach espoused by Francis Bacon, is inapplicable to current experimental method since, in accord with the philosopher Karl Popper, modern-day hypotheses are framed to serve as instruments of falsification, as opposed to verification. But Popper's "critical rationalist" framework too is problematic. It has been accused of being: inconsistent on philosophical grounds; unworkable for modern "large science," such as systems biology; inconsistent with the actual goals of experimental science, which is verification and not falsification; and harmful to the process of discovery as a practical matter. A criticism of the hypothesis as a framework for experimentation is offered. Presented is an alternative framework-the query/model approach-which many scientists may discover is the framework they are actually using, despite being required to give lip service to the hypothesis.
"First, hypothesis-driven research makes the researcher prone to subjectivity and even bias, because he enthusiastically wants to confirm his own ideas (Greenwald et al. 1986; Glass 2010; Jewett 2005; Firestein 2012). Second, although empirical studies are usually presented in a confirmatory or test-based fashion, they are in fact often question-driven, iterative and exploratory in nature (Feelders 2002; Glass 2010; Henseler et al. 2014; Rigdon 2012; Sarstedt et al. 2014). In that sense, our study is thus not so fundamentally different from mainstream research, except for the fact that we openly acknowledge its iterative nature. "
[Show abstract][Hide abstract] ABSTRACT: Academics and practitioners have made various claims regarding the benefits that Enterprise Architecture (EA) delivers for both individual projects and the organization as a whole. At the same time, there is a lack of explanatory theory regarding how EA delivers these benefits. Moreover, EA practices and benefits have not been extensively investigated by empirical research, with especially quantitative studies on the topic being few and far between. This paper therefore presents the statistical findings of a theory-building survey study (n = 293). The resulting PLS model is a synthesis of current implicit and fragmented theory, and shows how EA practices and intermediate benefits jointly work to help the organization reap benefits for both the organization and its projects. The model shows that EA and EA practices do not deliver benefits directly, but operate through intermediate results, most notably compliance with EA and architectural insight. Furthermore, the research identifies the EA practices that have a major impact on these results, the most important being compliance assessments, management propagation of EA, and different types of knowledge exchange. The results also demonstrate that projects play an important role in obtaining benefits from EA, but that they generally benefit less than the organization as a whole.
Information Systems Frontiers 01/2015; DOI:10.1007/s10796-014-9542-1 · 1.08 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Single protein biomarkers measured with antibody-based affinity assays are the basis of molecular diagnostics in clinical practice today. There is great hope in discovering new protein biomarkers and combinations of protein biomarkers for advancing medicine through monitoring health, diagnosing disease, guiding treatment, and developing new therapeutics. The goal of high-content proteomics is to unlock protein biomarker discovery by measuring many (thousands) or all (∼23,000) proteins in the human proteome in an unbiased, data-driven approach. High-content proteomics has proven technically difficult due to the diversity of proteins, the complexity of relevant biological samples, such as blood and tissue, and large concentration ranges (in the order of 10(12) in blood). Mass spectrometry and affinity methods based on antibodies have dominated approaches to high-content proteomics. For technical reasons, neither has achieved adequate simultaneous performance and high-content. Here we review antibody-based protein measurement, multiplexed antibody-based protein measurement, and limitations of antibodies for high-content proteomics due to their inherent cross-reactivity. Finally, we review a new affinity-based proteomic technology developed from the ground up to solve the problem of high content with high sensitivity and specificity. Based on a new generation of slow off-rate modified aptamers (SOMAmers), this technology is unlocking biomarker discovery.
[Show abstract][Hide abstract] ABSTRACT: Enterprise Architecture (EA) is rapidly becoming an established discipline. However, this does not mean that the practice of EA is already fully standardized. Practitioners as well as researchers report various techniques being used in the EA practice. And although EA has various potential benefits, evidence of real benefits is only just emerging. This paper presents empirical evidence of the relations between EA techniques used and EA benefits perceived, as well as the influence of contextual factors. The evidence is based on the results of a survey (n=293) held among both architects and stakeholders of EA in a wide variety of organizations. Employing multivariate regression analysis we found that the combination of project compliance, EA choices being explicitly linked to business goals and organized knowledge exchange between architects is a strong predictor for EA being perceived as a good instrument. We also established that significant differences exist in EA practice effectiveness between different economic sectors. Government appears to reap less benefits from EA than other sectors. The empirical evidence furthermore shows only a small influence of organizational size and number of architects on EA effectiveness.
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