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81                      Data Management
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162            <p class="subtitle is-3">&nbsp;  </p>
163            <p class="subtitle is-3">&nbsp;  </p>
164            <h1 class="title is-2" style="color:#FFFFFF;">Data Management</h1>
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189    <p><strong>Data Management (DM) Working Group</strong> addresses data needs of the ESS Community:</p>
190
191<ul>
192  <li>Data Preservation, Sharing, and Publication</li>
193  <li>Common Data and Metadata Standards</li>
194  <li>Data Citation and Attribution</li>
195  <li>Data Federation across different data catalogs</li>
196  <li>Data Synthesis across ESS and other relevant data sources</li>
197  <li>Development of common Tools for data usage</li>
198  <li>QA/QC, processing, analysis, mining and visualizing data to prepare them for use, especially in new research applications such as AI.</li>
199</ul>
200
201<p>The <strong>Data Management Working Group</strong> collaborates with members of the ESS Community 
202by providing opportunities to interact with each other through quarterly and annual 
203meetings to ensure their short and long-term needs are met at ESS-DIVE and other DOE 
204data type specific repositories (i.e. ESGF, EMSL, JGI, AmeriFlux). The opportunity for 
205cross-project/institution/discipline interaction of our many forward-looking members 
206is invaluable since data management is central to virtually all aspects of Environmental 
207System Science and the ModEx cycle. By establishing shared, standard tools and workflows, 
208the archival of the rapidly-growing, diverse data is facilitated. These archived data 
209will inform model representations of environmental systems, and the model results and 
210analyses should guide future data collections. Towards these goals, ESS-DIVE is the primary 
211repository for archiving data generated by ESS projects following the guidance and 
212requirements of the <a href="https://doi.org/10.11578/2023DOEPublicAccessPlan">2023 DOE Public Access Plan</a>
213and the DOE Office of Science <a href="https://science.osti.gov/Funding-Opportunities/Digital-D
213ata-Management">Statement on Digital Management</a>.</p>
214
215<h1 id="data-management-leads">Data Management Leads</h1>
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217<table>
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219<tr>
220<td><img class="alignleft" src="/img/people/christianson.jpeg" alt="Danielle Svehla Christianson" width="150" height="150" /></td>
221<td valign="top"><strong>Danielle Svehla Christianson</strong><br />
222<a href="mailto: [email protected]">[email protected]</a><br />
223<em>Lawrence Berkeley National Laboratory</em></td>
224</tr>
225<tr>
226<td><img class="alignleft" src="/img/people/velliquette.jpeg" alt="Terri Velliquette" width="150" height="150" /></td>
227<td valign="top"><strong>Terri Velliquette</strong><br />
228<a href="mailto: [email protected]">[email protected]</a><br />
229<em>Oak Ridge National Laboratory</em></td>
230</tr>
231</tbody>
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233
234<p>Want to contribute? Ask the leads to join the Google Group: [email protected]</p>
235
236<h1 id="quarterly-meetings">Quarterly Meetings</h1>
237
238<p>The DM WG holds quarterly meetings in the 2nd month of the business quarter on 
239the 4th Thursday at 12:00 PT / 3:00 ET (unless rescheduled due to holidays/conflicts).</p>
240
241<p>Past meeting topic and session leaders:</p>
242
243<h3 id="fy2026">FY2026</h3>
244<p>Q1: What is AI-Ready Data? Part 2
245<br />Charuleka Varadharajan and ESS-DIVE team (LBNL)</p>
246
247<h3 id="fy2025">FY2025</h3>
248<p>Q4: What is AI-Ready Data?
249<br />Douglas Rao (NOAA National Centers for Environmental Information)</p>
250
251<p>Q3: ML/LLM/AI/Agentic-AI Working Group discussion
252<br />David Moulton (LANL)</p>
253
254<p>Q2: Experiences &amp; Improvements to Archiving Model Data Products
255<br />Zhi Li (PNNL), Rosemary Carroll (Desert Research Institute)</p>
256
257<p>Q1: ESS-DIVE Annual Data Workshop: Needs for ESS data discovery &amp; use
258<br />Danielle Christianson (LBNL), Terri Velliquette (ORNL)</p>
259
260<h3 id="fy2024">FY2024</h3>
261<p>Q4: Tools for implementing Reporting Formats (continued) 
262<br />Tom Ruggles, Terri Velliquette, (ORNL), Sigrid Dengel (LBNL) , Dylan O’Ryan (LBNL)</p>
263
264<p>Q3: Tools for implementing Reporting Formats
265<br />Gilberto Pastorello, Valerie Hendrix (LBNL), Brieanne Forbes, Amy Goldman (PNNL)</p>
266
267<p>Q2: BERAC Unified Data Report &amp; ESS-DIVE proposal input
268<br />Pamela Weisenhorn (ANL), Kjiersten Fagnan, Charu Varadharajan (LBNL)</p>
269
270<p>Q1: NMDC submission portal &amp; EMSL metadata template
271<br />Montana Smith (PNNL)</p>
272
273<h3 id="fy2023">FY2023</h3>
274<p>Q4: Data integration brainstorming for BERAC Unified Data RFI
275<br />Kjiersten Fagnan, Danielle Christianson (LBNL)</p>
276
277<p>Q3: ESS CI Annual Mtg follow up / BERAC Unified Data RFI
278<br />Kjiersten Fagnan (LBNL)</p>
279
280<p>Q2: Valuing Data and Software as Scientific Products
281<br />Pamela Weisenhorn (ANL), Tim Scheibe (PNNL)</p>
282
283<p>Q1: ESS-DIVE Community Reporting Formats
284<br />Charuleka Varadharajan, Joan Damerow, Emily Robles (LBNL)</p>
285
286<h3 id="fy2022">FY2022</h3>
287<p>Q4: Kickoff! Planning &amp; topic selection</p>
288
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