https://battery.knowledge-graph.eu/w/index.php?action=history&feed=atom&title=Item%3AOSW3dc790110508459489f954080a7bcb65 2026-05-10T17:19:08Z Revision history for this page on the wiki MediaWiki 1.39.5 https://battery.knowledge-graph.eu/w/index.php?title=Item:OSW3dc790110508459489f954080a7bcb65&diff=18514&oldid=prev 2025-05-28T11:38:07Z

<p></p> <table style="background-color: #fff; color: #202122;" data-mw="interface"> <col class="diff-marker" /> <col class="diff-content" /> <col class="diff-marker" /> <col class="diff-content" /> <tr class="diff-title" lang="en"> <td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">← Older revision</td> <td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Revision as of 11:38, 28 May 2025</td> </tr><tr><td colspan="2" class="diff-lineno" id="mw-diff-left-l1">Line 1:</td> <td colspan="2" class="diff-lineno">Line 1:</td></tr> <tr><td class="diff-marker" data-marker="−"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>The event featured a talk from Dr. Simon Clark with the title, &quot;{{Template:Viewer/Link|page=File:OSWe27032521f0b4d669eaa6e6f585ace46.pdf|url=|label=Putting the AI in FAIR: How Ontologies Unlock Battery Knowledge for the Agentic Era}}&quot;</div></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>The event featured a talk from <ins style="font-weight: bold; text-decoration: none;">{{Template:Viewer/Link|page=Item:OSW72e733f317ef4cf9b8ca53e906c9acb9|url=|label=</ins>Dr. Simon Clark<ins style="font-weight: bold; text-decoration: none;">}} </ins>with the title, &quot;{{Template:Viewer/Link|page=File:OSWe27032521f0b4d669eaa6e6f585ace46.pdf|url=|label=Putting the AI in FAIR: How Ontologies Unlock Battery Knowledge for the Agentic Era}}&quot;</div></td></tr> <tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br/></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br/></td></tr> <tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>Abstract: As AI systems become more autonomous, they require structured and machine-actionable knowledge to reason, plan, and make informed decisions. Ontologies provide the semantic foundation that enables AI to work with battery data beyond simple pattern recognition-allowing for automated reasoning and cross-domain integration. While large language models (LLMs) can extract insights from unstructured data, they lack explicit relationships, logical constraints, and the ability to perform reliable, standards-based reasoning. By embedding battery knowledge into FAIR (Findable, Accessible, Interoperable, and Reusable) ontologies, we enable AI to move from text prediction to intelligent action and drive new breakthroughs in battery science.</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>Abstract: As AI systems become more autonomous, they require structured and machine-actionable knowledge to reason, plan, and make informed decisions. Ontologies provide the semantic foundation that enables AI to work with battery data beyond simple pattern recognition-allowing for automated reasoning and cross-domain integration. While large language models (LLMs) can extract insights from unstructured data, they lack explicit relationships, logical constraints, and the ability to perform reliable, standards-based reasoning. By embedding battery knowledge into FAIR (Findable, Accessible, Interoperable, and Reusable) ontologies, we enable AI to move from text prediction to intelligent action and drive new breakthroughs in battery science.</div></td></tr> </table>

0000-0002-8758-6109 https://battery.knowledge-graph.eu/w/index.php?title=Item:OSW3dc790110508459489f954080a7bcb65&diff=18510&oldid=prev 2025-05-28T11:33:53Z

<p></p> <table style="background-color: #fff; color: #202122;" data-mw="interface"> <col class="diff-marker" /> <col class="diff-content" /> <col class="diff-marker" /> <col class="diff-content" /> <tr class="diff-title" lang="en"> <td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">← Older revision</td> <td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Revision as of 11:33, 28 May 2025</td> </tr><tr class="mw-diff-slot-header" lang="en"><th colspan="4">jsondata</th></tr><tr><td colspan="2" class="diff-lineno" id="mw-diff-left-l27">Line 27:</td> <td colspan="2" class="diff-lineno">Line 27:</td></tr> <tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>     &quot;attachments&quot;: [</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>     &quot;attachments&quot;: [</div></td></tr> <tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>         &quot;File:OSWe27032521f0b4d669eaa6e6f585ace46.pdf&quot;</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>         &quot;File:OSWe27032521f0b4d669eaa6e6f585ace46.pdf&quot;</div></td></tr> <tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">    ],</ins></div></td></tr> <tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">    "project": [</ins></div></td></tr> <tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">        "Item:OSW6499d04ced9649f8bbc50f1e940a50c8"</ins></div></td></tr> <tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>     ]</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>     ]</div></td></tr> <tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>}</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>}</div></td></tr> </table>

0000-0002-8758-6109 https://battery.knowledge-graph.eu/w/index.php?title=Item:OSW3dc790110508459489f954080a7bcb65&diff=18509&oldid=prev 2025-05-28T11:33:18Z

<p></p> <table style="background-color: #fff; color: #202122;" data-mw="interface"> <col class="diff-marker" /> <col class="diff-content" /> <col class="diff-marker" /> <col class="diff-content" /> <tr class="diff-title" lang="en"> <td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">← Older revision</td> <td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Revision as of 11:33, 28 May 2025</td> </tr><tr><td colspan="2" class="diff-lineno" id="mw-diff-left-l1">Line 1:</td> <td colspan="2" class="diff-lineno">Line 1:</td></tr> <tr><td class="diff-marker" data-marker="−"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>The event featured a talk from Dr. Simon Clark with the title, &quot;Putting the AI in FAIR: How Ontologies Unlock Battery Knowledge for the Agentic Era&quot;</div></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>The event featured a talk from Dr. Simon Clark with the title, &quot;<ins style="font-weight: bold; text-decoration: none;">{{Template:Viewer/Link|page=File:OSWe27032521f0b4d669eaa6e6f585ace46.pdf|url=|label=</ins>Putting the AI in FAIR: How Ontologies Unlock Battery Knowledge for the Agentic Era<ins style="font-weight: bold; text-decoration: none;">}}</ins>&quot;</div></td></tr> <tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br/></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br/></td></tr> <tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>Abstract: As AI systems become more autonomous, they require structured and machine-actionable knowledge to reason, plan, and make informed decisions. Ontologies provide the semantic foundation that enables AI to work with battery data beyond simple pattern recognition-allowing for automated reasoning and cross-domain integration. While large language models (LLMs) can extract insights from unstructured data, they lack explicit relationships, logical constraints, and the ability to perform reliable, standards-based reasoning. By embedding battery knowledge into FAIR (Findable, Accessible, Interoperable, and Reusable) ontologies, we enable AI to move from text prediction to intelligent action and drive new breakthroughs in battery science.</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>Abstract: As AI systems become more autonomous, they require structured and machine-actionable knowledge to reason, plan, and make informed decisions. Ontologies provide the semantic foundation that enables AI to work with battery data beyond simple pattern recognition-allowing for automated reasoning and cross-domain integration. While large language models (LLMs) can extract insights from unstructured data, they lack explicit relationships, logical constraints, and the ability to perform reliable, standards-based reasoning. By embedding battery knowledge into FAIR (Findable, Accessible, Interoperable, and Reusable) ontologies, we enable AI to move from text prediction to intelligent action and drive new breakthroughs in battery science.</div></td></tr> </table>

0000-0002-8758-6109 https://battery.knowledge-graph.eu/w/index.php?title=Item:OSW3dc790110508459489f954080a7bcb65&diff=18508&oldid=prev 2025-05-28T11:32:33Z

<p>Edited with SimpleBatchUpload</p> <table style="background-color: #fff; color: #202122;" data-mw="interface"> <col class="diff-marker" /> <col class="diff-content" /> <col class="diff-marker" /> <col class="diff-content" /> <tr class="diff-title" lang="en"> <td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">← Older revision</td> <td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Revision as of 11:32, 28 May 2025</td> </tr><tr class="mw-diff-slot-header" lang="en"><th colspan="4">jsondata</th></tr><tr><td colspan="2" class="diff-lineno" id="mw-diff-left-l24">Line 24:</td> <td colspan="2" class="diff-lineno">Line 24:</td></tr> <tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>         &quot;Item:OSW72e733f317ef4cf9b8ca53e906c9acb9&quot;</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>         &quot;Item:OSW72e733f317ef4cf9b8ca53e906c9acb9&quot;</div></td></tr> <tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>     ],</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>     ],</div></td></tr> <tr><td class="diff-marker" data-marker="−"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>     &quot;name&quot;: &quot;PolisSeminarMay2025&quot;</div></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>     &quot;name&quot;: &quot;PolisSeminarMay2025&quot;<ins style="font-weight: bold; text-decoration: none;">,</ins></div></td></tr> <tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">    &quot;attachments&quot;: [</ins></div></td></tr> <tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">        &quot;File:OSWe27032521f0b4d669eaa6e6f585ace46.pdf&quot;</ins></div></td></tr> <tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">    ]</ins></div></td></tr> <tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>}</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>}</div></td></tr> </table>

0000-0002-8758-6109 https://battery.knowledge-graph.eu/w/index.php?title=Item:OSW3dc790110508459489f954080a7bcb65&diff=18504&oldid=prev 2025-05-28T11:29:35Z

<p></p> <table style="background-color: #fff; color: #202122;" data-mw="interface"> <col class="diff-marker" /> <col class="diff-content" /> <col class="diff-marker" /> <col class="diff-content" /> <tr class="diff-title" lang="en"> <td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">← Older revision</td> <td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Revision as of 11:29, 28 May 2025</td> </tr><tr><td colspan="2" class="diff-lineno" id="mw-diff-left-l1">Line 1:</td> <td colspan="2" class="diff-lineno">Line 1:</td></tr> <tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">The event featured a talk from Dr. Simon Clark with the title, "Putting the AI in FAIR: How Ontologies Unlock Battery Knowledge for the Agentic Era"</ins></div></td></tr> <tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br/></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br/></td></tr> <tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">Abstract: As AI systems become more autonomous, they require structured and machine-actionable knowledge to reason, plan, and make informed decisions. Ontologies provide the semantic foundation that enables AI to work with battery data beyond simple pattern recognition-allowing for automated reasoning and cross-domain integration. While large language models (LLMs) can extract insights from unstructured data, they lack explicit relationships, logical constraints, and the ability to perform reliable, standards-based reasoning. By embedding battery knowledge into FAIR (Findable, Accessible, Interoperable, and Reusable) ontologies, we enable AI to move from text prediction to intelligent action and drive new breakthroughs in battery science.</ins></div></td></tr> </table>

0000-0002-8758-6109 https://battery.knowledge-graph.eu/w/index.php?title=Item:OSW3dc790110508459489f954080a7bcb65&diff=18503&oldid=prev 2025-05-28T11:28:32Z

<p></p> <p><b>New page</b></p><div></div>

0000-0002-8758-6109