Already significant value but now needs to be disseminated and advertised although maximal value to come from interdisciplinary/projective next version. Value is to detect quickly a paper/project of interest for its results and next step is trajectory of the field under types of interactions from diverse levels of oracles (subjects/objects) + from interdisciplinary context. Current Compute(System) Currently on OVH servers (mix shared + dedicated) Solutions Storage OVH Networking To be implemented with desired integration with others Software Current version with Symfony-PHP, Linux, MySQL Big Data Data Source Currently centralized, soon distributed per country Characteristics (distributed/centralized) and even per hosting institution interested by own platform Volume (size) Not significant : this is a metadata base, not big data Velocity Real time (e.g. real time) Variety Link to Big data still to be established in a (multiple datasets, relationship not yet implemented (with mashup) experimental databases and already 1st level related metadata) Variability (rate of Currently Real time, for further multiple locations change) and distributed architectures, periodic (such as nightly) Big Data Science Veracity (Robustness Methods to detect overall consistency, holes, errors, (collection, Issues, semantics) misstatements, known but mostly to be curation, implemented analysis, Visualization Multidimensional (hypercube) action) Data Quality (syntax) A priori correct (directly human captured) with sets of checking + evaluation processes partly implemented Data Types categories, PDFs ‘cluster displays’ (image), vectors, Data Analytics Big Data Specific Our goal is to contribute to Big 2 Metadata challenge by systematic Challenges (Gaps) reconciling between metadata from many complexity levels with ongoing input from researchers from ongoing research process. Current relationship with Richeact is to reach the interdisciplinary model, using meta-grammar itself to be experimented and its extent fully proven to bridge efficiently the gap between as remote complexity levels as semantic and most elementary (big) signals. Example with cosmological models versus many levels of intermediary models (particles, gases, galactic, nuclear, geometries). Others with computational versus semantic levels. Big Data Specific Appropriate graphic interface power Challenges in Mobility Security & Privacy Several levels already available and others planned, up to physical Requirements access keys and isolated servers. Optional anonymity, usual protected exchanges
Already significant value but now needs to be disseminated and advertised although maximal value to come from interdisciplinary/projective next version. Value is to detect quickly a paper/project of interest for its results and next step is trajectory of the field under types of interactions from diverse levels of oracles (subjects/objects) + from interdisciplinary context. Current Solutions Compute(System) Currently on OVH servers (mix shared + dedicated) Storage OVH Networking To be implemented with desired integration with others Software Current version with Symfony-PHP, Linux, MySQL Big Data Characteristics Data Source (distributed/centralized) Currently centralized, soon distributed per country and even per hosting institution interested by own platform Volume (size) Not significant : this is a metadata base, not big data Velocity (e.g. real time) Real time Variety (multiple datasets, mashup) Link to Big data still to be established in a relationship not yet implemented (with experimental databases and already 1st level related metadata) Variability (rate of change) Currently Real time, for further multiple locations and distributed architectures, periodic (such as nightly) Big Data Science (collection, curation, analysis, action) Veracity (Robustness Issues, semantics) Methods to detect overall consistency, holes, errors, misstatements, known but mostly to be implemented Visualization Multidimensional (hypercube) Data Quality (syntax) A priori correct (directly human captured) with sets of checking + evaluation processes partly implemented Data Types ‘cluster displays’ (image), vectors, categories, PDFs Data Analytics Big Data Specific Challenges (Gaps) Our goal is to contribute to Big 2 Metadata challenge by systematic reconciling between metadata from many complexity levels with ongoing input from researchers from ongoing research process. Current relationship with Richeact is to reach the interdisciplinary model, using meta-grammar itself to be experimented and its extent fully proven to bridge efficiently the gap between as remote complexity levels as semantic and most elementary (big) signals. Example with cosmological models versus many levels of intermediary models (particles, gases, galactic, nuclear, geometries). Others with computational versus semantic levels. Big Data Specific Challenges in Mobility Appropriate graphic interface power Security & Privacy Requirements Several levels already available and others planned, up to physical access keys and isolated servers. Optional anonymity, usual protected exchanges