Contributors | Affiliation | Role |
---|---|---|
Rauch, Shannon | Woods Hole Oceanographic Institution (WHOI BCO-DMO) | Principal Investigator |
York, Amber D. | Woods Hole Oceanographic Institution (WHOI BCO-DMO) | Co-Principal Investigator |
currently being processed
Parameter | Description | Units |
Cast | Cast identifier | unitless |
Lat_Start | Latitude at start of cast | degrees North |
Lon_Start | Longitude at start of cast (negative values = West) | degrees East |
ISO_DateTime_Start_UTC | Date and time (UTC) at start of cast | unitless |
altM | Altimeter | meters (m) |
avgsvCM | Average Sound Velocity (Chen-Millero) | meters per second (m/s) |
nbf | Number of bottles fired | unitless |
c0S_m | Conductivity | Siemens per meter (S/m) |
c1S_m | Conductivity, 2 | Siemens per meter (S/m) |
depSM | Depth (salt water) | meters (m) |
dz_dtM | Descent rate | meters per second (m/s) |
latitude | Latitude | degrees North |
longitude | Longitude (negative values = West) | degrees East |
sbeox0Mg_L | Oxygen, SBE 43 | milligrams per liter (mg/L) |
sbeox1Mg_L | Oxygen, SBE 43, 2 | milligrams per liter (mg/L) |
prDM | Pressure, Digiquartz | decibars (db) |
sal00 | Salinity, Practical | PSU |
svCM | Sound Velocity (Chen-Millero) | meters per second (m/s) |
t090C | Temperature (ITS-90) | degrees Celsius |
t190C | Temperature, 2 (ITS-90) | degrees Celsius |
timeS | Time elapsed | seconds |
CStarTr0 | Beam Transmission, WET Labs C-Star | percent (%) |
ph | pH | unitless (pH scale) |
flECO_AFL | Fluorescence, WET Labs ECO-AFL/FL | milligrams per cubic meter (mg/m^3) |
sal11 | Salinity, Practical, 2 | PSU |
secS_priS | Salinity, Practical, Difference, 2 - 1 | PSU |
pumps | Pump Status | unitless |
flag | Flag | unitless |
NSF Award Abstract:
Scientific research is intrinsically reliant upon the creation, management, analysis, synthesis, and interpretation of data. Once generated, data are essential to demonstrating the veracity and reproducibility of scientific results, and existing data hold great potential to accelerate scientific discovery through reuse. The Biological and Chemical Oceanography and Data Management Office (BCO-DMO) was created in 2006 to assemble, curate, and publicly serve all data and related products resulting from grants funded by the NSF core programs for Biological and Chemical Oceanography, and Office of Polar Programs. BCO-DMO provides limnological and marine chemical, biological, and physical data inventories from several large and intermediate-sized programs, as well as single-investigator projects to support cross-disciplinary collaboration to address pressing environmental questions, problems, and challenges that are exacerbated with the increasing pace of climate change. BCO-DMO is committed to data management capacity building efforts, improving data literacy and increasing science engagement in data management topics through education, training, and outreach. The project collaborates with academic institutions and teachers, where the BCO-DMO database is leveraged for oceanographic curricula, and engages in targeted training of informatics students, cross-pollinating their knowledge with geoscience domain data management.
BCO-DMO's goal is to facilitate the integration of its diverse datasets to enable researchers to achieve a deeper understanding of ocean ecological and biogeochemical systems. As a domain repository, BCO-DMO adds value and improves interoperability of data to support activities such as synthesis and modeling, and the reuse of oceanographic data for new research. Open access to the BCO-DMO database lowers barriers to allow economically challenged countries to gain access to research quality data for field decision support, policy-relevant issues, and educational purposes. The project takes an active role in the exchange of knowledge at national and international geoscience and informatics meetings and workshops, where standards development and adoption occur. BCO-DMO also participates in the development and use of open-source, standards-based technologies that enable interoperable data systems to exchange data and information that will foster next-generation research in all disciplines. While continuing to perform its core mission of data management, BCO-DMO will reconstitute its data infrastructure to mobilize a new adaptive data management strategy for addressing the evolutionary change coinciding with the big data revolution. Leveraging data semantics BCO-DMO will construct a knowledge graph for sustainably operating an adaptive data repository. This infrastructure will support dataset-level and repository-level metrics, an improved data submission experience and new data and metadata access capabilities. Through declarative workflows, the processing of contributed data will increase in efficiency, and result in actionable provenance records for complete transparency of data curation practices. Taking a holistic perspective on education, outreach and community engagement, formalized programs will be developed to promote data reuse and interest in oceanographic science.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Funding Source | Award |
---|---|
NSF Division of Ocean Sciences (NSF OCE) |