MOLES Information Model

The Metadata Objects for Linking Environmental Sciences (MOLES) model has been developed within the Natural Environment Research Council (NERC) DataGrid project [NERC DataGrid] to fill a missing part of the ¿metadata spectrum¿. It is a framework within which to encode the relationships between the tools used to obtain data, the activities which organised their use, and the datasets produced. MOLES is primarily of use to consumers of data, especially in an interdisciplinary context, to allow them to establish details of provenance, and to compare and contrast such information without recourse to discipline-specific metadata or private communications with the original investigators [Lawrence et al 2009]. MOLES is also of use to the custodians of data, providing an organising paradigm for the data and metadata. The work described in this paper is a high-level view of the structure and content of a recent major revision of MOLES (v3.3) carried out as part of a NERC DataGrid extension project. The concepts of MOLES v3.3 are rooted in the harmonised ISO model [Harmonised ISO model] - particularly in metadata standards (ISO 19115, ISO 19115-2) and the ¿Observations and Measurements¿ conceptual model (ISO 19156). MOLES exploits existing concepts and relationships, and specialises information in these standards. A typical sequence of data capturing involves one or more projects under which a number of activities are undertaken, using appropriate tools and methods to produce the datasets. Following this typical sequence, the relevant metadata can be partitioned into the following main sections ¿ helpful in mapping onto the most suitable standards from the ISO 19100 series. ¿ Project section ¿ Activity section (including both observation acquisition and numerical computation) ¿ Observation section (metadata regarding the methods used to obtained the data, the spatial and temporal sampling regime, quality etc.) ¿ Observation collection section The key concepts in MOLES v3.3 are: a) the result of an observation is defined uniquely from the property (of a feature-of-interest), the sampling-feature (carrying the targeted property values), the procedure used to obtain the result and the time (discrete instant or period) at which the observation takes place. b) an ¿Acquisition¿ and a ¿Computation¿ can serve as the basis for describing any observation process chain (procedure). The ¿Acquisition¿ uses an instrument ¿ sensor or human being ¿ to produce the results and is associated with field trips, flights, cruises etc., whereas the ¿Computation¿ class involves specific processing steps. A process chain may consist of any combination of ¿Acquisitions¿ and/or ¿Computations¿ occurring in parallel or in any order during the data capturing sequence. c) The results can be organised in collections with significantly more flexibility than if one used the original project alone d) the structure of individual observation collections may be domain-specific, in general; however we are investigating the use of CSML (Climate Science Modelling Language) for atmospheric dataJRC.DDG.H.6-Spatial data infrastructure

Iron and the ecology of marine microbes

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Biological Engineering, 2013Cataloged from PDF version of thesis.Includes bibliographical references.Iron is a cofactor of a number biochemical reactions that are essential for life. In the marine environment, this micronutrient is a scarce resource that limits processes of global importance such as photosynthesis and nitrogen fixation. Given that marine microorganisms play a central role in modulating such biogeochemical cycles, understanding how their distribution, diversity and activity may be affected by changes in iron availability is key. This thesis explores how the availability of iron affects the ecology of marine microbial populations and communities. At the population level, I characterized the prevalence and diversity of iron acquisition strategies in specific populations of marine vibrios with distinct micro-habitat preferences. Using a combination of genomics and functional screens, I showed that siderophore-based iron acquisition is not conserved at the organismlevel but represents a stable trait at the population level. This population-level trait further appears to play a role in driving the diversification of specific vibrio populations, especially of those that are thought to prefer particles as a micro-habitat. At the community level, I measured whole microbial community responses to iron addition in microcosm experiments in different regions of the Pacific Ocean. Using metagenomics, I characterized the impact of iron availability on the microbial community structure of the Central Equatorial Pacific Ocean. This study showed that addition of iron to an iron-limited ecosystem triggers a phytoplankton bloom dominated by Pseudo-nitZschia-like diatoms, which in turn stimulate a Bacteroidetes population functionally distinct from the ambient free-living population. In the North Pacific Subtropical Gyre, I explored how iron availability impacts microbial community gene expression dynamics. Using a metatranscriptomic approach I showed that in that environment, the impact of iron was tightly connected to the supply of other limiting macronutrients, and seems to mostly affect photosynthetic organisms. This initial study paves the way for more in depth and longer-term studies to further investigate the effects of iron on the dynamics of the microbial community in the North Pacific Subtropical Gyre. Taken together data and analyses presented in this thesis demonstrate how iron availability can shape the ecology of marine microorganisms at population, community and functional levels.by Laure-Anne Ventouras.Ph.D

MOLES3: implementing an ISO standards driven data catalogue

ISO19156 Observations and Measurements (O&M) provides a standardised framework for organising information about the collection of information about the environment. Here we describe the implementation of a specialisation of O&M for environmental data, the Metadata Objects for Linking Environmental Sciences (MOLES3). MOLES3 provides support for organising information about data, and for user navigation around data holdings. The implementation described here, “CEDA-MOLES”, also supports data management functions for the Centre for Environmental Data Archival, CEDA. The previous iteration of MOLES (MOLES2) saw active use over five years, being replaced by CEDA-MOLES in late 2014. During that period important lessons were learnt both about the information needed, as well as how to design and maintain the necessary information systems. In this paper we review the problems encountered in MOLES2; how and why CEDA-MOLES was developed and engineered; the migration of information holdings from MOLES2 to CEDA-MOLES; and, finally, provide an early assessment of MOLES3 (as implemented in CEDA-MOLES) and its limitations. Key drivers for the MOLES3 development included the necessity for improved data provenance, for further structured information to support ISO19115 discovery metadata export (for EU INSPIRE compliance), and to provide appropriate fixed landing pages for Digital Object Identifiers (DOIs) in the presence of evolving datasets. Key lessons learned included the importance of minimising information structure in free text fields, and the necessity to support as much agility in the information infrastructure as possible without compromising on maintainability both by those using the systems internally and externally (e.g. citing in to the information infrastructure), and those responsible for the systems themselves. The migration itself needed to ensure continuity of service and traceability of archived assets

Independent Component Analysis for Source Localization of EEG Sleep Spindle Components

Sleep spindles are bursts of sleep electroencephalogram (EEG) quasirhythmic activity within the frequency band of 11–16 Hz, characterized by progressively increasing, then gradually decreasing amplitude. The purpose of the present study was to process sleep spindles with Independent Component Analysis (ICA) in order to investigate the possibility of extracting, through visual analysis of the spindle EEG and visual selection of Independent Components (ICs), spindle “components” (SCs) corresponding to separate EEG activity patterns during a spindle, and to investigate the intracranial current sources underlying these SCs. Current source analysis using Low-Resolution Brain Electromagnetic Tomography (LORETA) was applied to the original and the ICA-reconstructed EEGs. Results indicated that SCs can be extracted by reconstructing the EEG through back-projection of separate groups of ICs, based on a temporal and spectral analysis of ICs. The intracranial current sources related to the SCs were found to be spatially stable during the time evolution of the sleep spindles

Behavioral and brain pattern differences between acting and observing in an auditory task

<p>Abstract</p> <p>Background</p> <p>Recent research has shown that errors seem to influence the patterns of brain activity. Additionally current notions support the idea that similar brain mechanisms are activated during acting and observing. The aim of the present study was to examine the patterns of brain activity of actors and observers elicited upon receiving feedback information of the actor's response.</p> <p>Methods</p> <p>The task used in the present research was an auditory identification task that included both acting and observing settings, ensuring concurrent ERP measurements of both participants. The performance of the participants was investigated in conditions of varying complexity. ERP data were analyzed with regards to the conditions of acting and observing in conjunction to correct and erroneous responses.</p> <p>Results</p> <p>The obtained results showed that the complexity induced by cue dissimilarity between trials was a demodulating factor leading to poorer performance. The electrophysiological results suggest that feedback information results in different intensities of the ERP patterns of observers and actors depending on whether the actor had made an error or not. The LORETA source localization method yielded significantly larger electrical activity in the supplementary motor area (Brodmann area 6), the posterior cingulate gyrus (Brodmann area 31/23) and the parietal lobe (Precuneus/Brodmann area 7/5).</p> <p>Conclusion</p> <p>These findings suggest that feedback information has a different effect on the intensities of the ERP patterns of actors and observers depending on whether the actor committed an error. Certain neural systems, including medial frontal area, posterior cingulate gyrus and precuneus may mediate these modulating effects. Further research is needed to elucidate in more detail the neuroanatomical and neuropsychological substrates of these systems.</p

Mismatch task conditions and error related ERPs

<p>Abstract</p> <p>Background</p> <p>The N200 component of event related potentials (ERPs) is considered an index of monitoring error related responses. The aim of the present work was to study the effect of mismatch conditions on the subjects' responses in an auditory identification task and their relation to the N200 of stimulus-locked ERPs.</p> <p>Methods</p> <p>An auditory identification task required to correctly map a horizontal slider onto an active frequency range by selecting a slider position that matched the stimulus tone in each trial. Fourteen healthy volunteers participated in the study and ERPs were recorded by 32 leads.</p> <p>Results</p> <p>Results showed that the subjects' erroneous responses were equally distributed within trials, but were dependent on mismatch conditions, generated by large differences between the frequencies of the tones of consecutive trials. Erroneous trials showed a significantly greater negativity within the time window of 164-191 ms after stimulus, located mainly at the Cz and Fz electrodes. The LORETA solution showed that maximum activations, as well as maximum differences, were localized mainly at the frontal lobe.</p> <p>Conclusions</p> <p>These findings suggest that the fronto-central N200 component, conceived an index of "reorientation of attention", represents a correlate of an error signal, being produced when representation of the actual response and the required response are compared. Furthermore the magnitude of the amplitude of the N200 rests on the relation between the present and the previous stimulus.</p

Classification of Event-Related Potentials Associated with Response Errors in Actors and Observers Based on Autoregressive Modeling

Event-Related Potentials (ERPs) provide non-invasive measurements of the electrical activity on the scalp related to the processing of stimuli and preparation of responses by the brain. In this paper an ERP-signal classification method is proposed for discriminating between ERPs of correct and incorrect responses of actors and of observers seeing an actor making such responses. The classification method targeted signals containing error-related negativity (ERN) and error positivity (Pe) components, which are typically associated with error processing in the human brain. Feature extraction consisted of Multivariate Autoregressive modeling combined with the Simulated Annealing technique. The resulting information was subsequently classified by means of an Artificial Neural Network (ANN) using back-propagation algorithm under the “leave-one-out cross-validation” scenario and the Fuzzy C-Means (FCM) algorithm. The ANN consisted of a multi-layer perceptron (MLP). The approach yielded classification rates of up to 85%, both for the actors’ correct and incorrect responses and the corresponding ERPs of the observers. The electrodes needed for such classifications were situated mainly at central and frontal areas. Results provide indications that the classification of the ERN is achievable. Furthermore, the availability of the Pe signals, in addition to the ERN, improves the classification, and this is more pronounced for observers’ signals. The proposed ERP-signal classification method provides a promising tool to study error detection and observational-learning mechanisms in performance monitoring and joint-action research, in both healthy and patient populations