29,398 research outputs found
A posteriori metadata from automated provenance tracking: Integration of AiiDA and TCOD
In order to make results of computational scientific research findable,
accessible, interoperable and re-usable, it is necessary to decorate them with
standardised metadata. However, there are a number of technical and practical
challenges that make this process difficult to achieve in practice. Here the
implementation of a protocol is presented to tag crystal structures with their
computed properties, without the need of human intervention to curate the data.
This protocol leverages the capabilities of AiiDA, an open-source platform to
manage and automate scientific computational workflows, and TCOD, an
open-access database storing computed materials properties using a well-defined
and exhaustive ontology. Based on these, the complete procedure to deposit
computed data in the TCOD database is automated. All relevant metadata are
extracted from the full provenance information that AiiDA tracks and stores
automatically while managing the calculations. Such a protocol also enables
reproducibility of scientific data in the field of computational materials
science. As a proof of concept, the AiiDA-TCOD interface is used to deposit 170
theoretical structures together with their computed properties and their full
provenance graphs, consisting in over 4600 AiiDA nodes
Semantic Modeling of Analytic-based Relationships with Direct Qualification
Successfully modeling state and analytics-based semantic relationships of
documents enhances representation, importance, relevancy, provenience, and
priority of the document. These attributes are the core elements that form the
machine-based knowledge representation for documents. However, modeling
document relationships that can change over time can be inelegant, limited,
complex or overly burdensome for semantic technologies. In this paper, we
present Direct Qualification (DQ), an approach for modeling any semantically
referenced document, concept, or named graph with results from associated
applied analytics. The proposed approach supplements the traditional
subject-object relationships by providing a third leg to the relationship; the
qualification of how and why the relationship exists. To illustrate, we show a
prototype of an event-based system with a realistic use case for applying DQ to
relevancy analytics of PageRank and Hyperlink-Induced Topic Search (HITS).Comment: Proceedings of the 2015 IEEE 9th International Conference on Semantic
Computing (IEEE ICSC 2015
Towards structured sharing of raw and derived neuroimaging data across existing resources
Data sharing efforts increasingly contribute to the acceleration of
scientific discovery. Neuroimaging data is accumulating in distributed
domain-specific databases and there is currently no integrated access mechanism
nor an accepted format for the critically important meta-data that is necessary
for making use of the combined, available neuroimaging data. In this
manuscript, we present work from the Derived Data Working Group, an open-access
group sponsored by the Biomedical Informatics Research Network (BIRN) and the
International Neuroimaging Coordinating Facility (INCF) focused on practical
tools for distributed access to neuroimaging data. The working group develops
models and tools facilitating the structured interchange of neuroimaging
meta-data and is making progress towards a unified set of tools for such data
and meta-data exchange. We report on the key components required for integrated
access to raw and derived neuroimaging data as well as associated meta-data and
provenance across neuroimaging resources. The components include (1) a
structured terminology that provides semantic context to data, (2) a formal
data model for neuroimaging with robust tracking of data provenance, (3) a web
service-based application programming interface (API) that provides a
consistent mechanism to access and query the data model, and (4) a provenance
library that can be used for the extraction of provenance data by image
analysts and imaging software developers. We believe that the framework and set
of tools outlined in this manuscript have great potential for solving many of
the issues the neuroimaging community faces when sharing raw and derived
neuroimaging data across the various existing database systems for the purpose
of accelerating scientific discovery
Architecture for Provenance Systems
This document covers the logical and process architectures of provenance systems. The logical architecture identifies key roles and their interactions, whereas the process architecture discusses distribution and security. A fundamental aspect of our presentation is its technology-independent nature, which makes it reusable: the principles that are exposed in this document may be applied to different technologies
- …