PMCC PMCC

Search tips
Search criteria

Advanced
Results 1-3 (3)
 

Clipboard (0)
None
Journals
Authors
Year of Publication
Document Types
jtitle_s:("auto Exp")
1.  Design preferences and cognitive styles: experimentation by automated website synthesis 
Background
This article aims to demonstrate computational synthesis of Web-based experiments in undertaking experimentation on relationships among the participants' design preference, rationale, and cognitive test performance. The exemplified experiments were computationally synthesised, including the websites as materials, experiment protocols as methods, and cognitive tests as protocol modules. This work also exemplifies the use of a website synthesiser as an essential instrument enabling the participants to explore different possible designs, which were generated on the fly, before selection of preferred designs.
Methods
The participants were given interactive tree and table generators so that they could explore some different ways of presenting causality information in tables and trees as the visualisation formats. The participants gave their preference ratings for the available designs, as well as their rationale (criteria) for their design decisions. The participants were also asked to take four cognitive tests, which focus on the aspects of visualisation and analogy-making. The relationships among preference ratings, rationale, and the results of cognitive tests were analysed by conservative non-parametric statistics including Wilcoxon test, Krustal-Wallis test, and Kendall correlation.
Results
In the test, 41 of the total 64 participants preferred graphical (tree-form) to tabular presentation. Despite the popular preference for graphical presentation, the given tabular presentation was generally rated to be easier than graphical presentation to interpret, especially by those who were scored lower in the visualization and analogy-making tests.
Conclusions
This piece of evidence helps generate a hypothesis that design preferences are related to specific cognitive abilities. Without the use of computational synthesis, the experiment setup and scientific results would be impractical to obtain.
doi:10.1186/1759-4499-4-2
PMCID: PMC3386886  PMID: 22748000
2.  OpenKnowledge for peer-to-peer experimentation in protein identification by MS/MS 
Background
Traditional scientific workflow platforms usually run individual experiments with little evaluation and analysis of performance as required by automated experimentation in which scientists are being allowed to access numerous applicable workflows rather than being committed to a single one. Experimental protocols and data under a peer-to-peer environment could potentially be shared freely without any single point of authority to dictate how experiments should be run. In such environment it is necessary to have mechanisms by which each individual scientist (peer) can assess, locally, how he or she wants to be involved with others in experiments. This study aims to implement and demonstrate simple peer ranking under the OpenKnowledge peer-to-peer infrastructure by both simulated and real-world bioinformatics experiments involving multi-agent interactions.
Methods
A simulated experiment environment with a peer ranking capability was specified by the Lightweight Coordination Calculus (LCC) and automatically executed under the OpenKnowledge infrastructure. The peers such as MS/MS protein identification services (including web-enabled and independent programs) were made accessible as OpenKnowledge Components (OKCs) for automated execution as peers in the experiments. The performance of the peers in these automated experiments was monitored and evaluated by simple peer ranking algorithms.
Results
Peer ranking experiments with simulated peers exhibited characteristic behaviours, e.g., power law effect (a few dominant peers dominate), similar to that observed in the traditional Web. Real-world experiments were run using an interaction model in LCC involving two different types of MS/MS protein identification peers, viz., peptide fragment fingerprinting (PFF) and de novo sequencing with another peer ranking algorithm simply based on counting the successful and failed runs. This study demonstrated a novel integration and useful evaluation of specific proteomic peers and found MASCOT to be a dominant peer as judged by peer ranking.
Conclusion
The simulated and real-world experiments in the present study demonstrated that the OpenKnowledge infrastructure with peer ranking capability can serve as an evaluative environment for automated experimentation.
doi:10.1186/1759-4499-3-3
PMCID: PMC3377912  PMID: 22192521
3.  Welcome to Automated Experimentation: a new open access journal 
Modern experimental science provides more opportunities for yet larger series of experiments. Demand for experimental results also has become more diverse, requiring results that have direct connections to systems outside the laboratory. With this has come an ability to automate many areas of experimental science, not only the experiments themselves but also the larger processes that contribute to experimentation and analysis more broadly. As automated experimentation becomes more widely used and understood, we launch this journal to provide a proper publication channel for this new breed of interdisciplinary research as well as a bridge to all significant groundwork research that would facilitate possible automated experimentation. With this in mind, we are interested in publishing all kinds of research into scientific experimentation, including research where the potential for automation is at proof or concept or early deployment stage.
doi:10.1186/1759-4499-1-1
PMCID: PMC2809325  PMID: 20098588

Results 1-3 (3)