Report Structure

This notebook is available to use, reproduce, and validate the report-structure results for ClimateKG. Source notebook: report-structure.ipynb

This notebook is anchored to The Rock, the shared reference note for the ClimateKG ER model.

Key references: - ERM model README - Class instance counts notebook - The Rock reference

The canonical corpus hierarchy is:

Work (Q2) -> Report Series (Q3) -> Report (Q4) -> Text Division (Q5) -> Chapter (Q6)

The graph logic in the ER model is defined through P3 = Part of and P4 = Parts. The live Wikibase is checked against that intended model in order to record what actually exists today, not to assume the whole hierarchy is present.

Query UI: https://climatekg.tibwiki.io/query/

SPARQL endpoint: https://climatekg.tibwiki.io/query/proxy/sparql

Show code

import os
import pandas as pd
from SPARQLWrapper import JSON
from IPython.display import display

from wikibase_auth import DEFAULT_SPARQL_ENDPOINT, DEFAULT_WIKIBASE_URL, build_sparql_client

os.environ["CLIMATEKG_WIKIBASE_URL"] = "https://climatekg.tibwiki.io"
os.environ["CLIMATEKG_SPARQL_ENDPOINT"] = "https://climatekg.tibwiki.io/query/proxy/sparql"
os.environ.setdefault("CLIMATEKG_SPARQL_USERNAME", "ckg")
os.environ.setdefault("CLIMATEKG_SPARQL_PASSWORD", "fairdata")

SPARQL_ENDPOINT = os.getenv("CLIMATEKG_SPARQL_ENDPOINT", DEFAULT_SPARQL_ENDPOINT)
WIKIBASE_URL = os.getenv("CLIMATEKG_WIKIBASE_URL", DEFAULT_WIKIBASE_URL).rstrip("/")
ENTITY_NS = f"{WIKIBASE_URL}/entity/"
PROPERTY_NS = f"{WIKIBASE_URL}/prop/direct/"

print(f"Endpoint: {SPARQL_ENDPOINT}")
print("Libraries imported successfully")

print(f"Entity namespace (RDF prefix): {ENTITY_NS}")
print(f"Property namespace (RDF prefix): {PROPERTY_NS}")
print(f"Example item page: {WIKIBASE_URL}/wiki/Item:Q2")
print(f"Example property page: {WIKIBASE_URL}/wiki/Property:P1")

'ckg'

'fairdata'

Endpoint: https://climatekg.tibwiki.io/query/proxy/sparql
Libraries imported successfully
Entity namespace (RDF prefix): https://climatekg.tibwiki.io/entity/
Property namespace (RDF prefix): https://climatekg.tibwiki.io/prop/direct/
Example item page: https://climatekg.tibwiki.io/wiki/Item:Q2
Example property page: https://climatekg.tibwiki.io/wiki/Property:P1

Show code

class_query = f'''
PREFIX wd: <{ENTITY_NS}>
PREFIX wdt: <{PROPERTY_NS}>

SELECT ?class ?classLabel (COUNT(?item) AS ?count)
WHERE {{
  VALUES ?class {{ wd:Q2 wd:Q3 wd:Q4 wd:Q5 wd:Q6 }}
  OPTIONAL {{ ?item wdt:P1 ?class . }}
  SERVICE wikibase:label {{ bd:serviceParam wikibase:language "en". }}
}}
GROUP BY ?class ?classLabel
ORDER BY ?class
'''

sparql = build_sparql_client(SPARQL_ENDPOINT)
sparql.setQuery(class_query)
sparql.setReturnFormat(JSON)
class_results = sparql.query().convert()
class_rows = class_results.get("results", {}).get("bindings", [])
class_df = pd.DataFrame([{k: v["value"] for k, v in row.items()} for row in class_rows])

print(f"Class counts returned: {len(class_df)}")
display(class_df)

Class counts returned: 5

	class	classLabel	count
0	https://climatekg.tibwiki.io/entity/Q2	Work	2
1	https://climatekg.tibwiki.io/entity/Q3	Report Series	1
2	https://climatekg.tibwiki.io/entity/Q4	Report	7
3	https://climatekg.tibwiki.io/entity/Q5	Text Division	10
4	https://climatekg.tibwiki.io/entity/Q6	Chapter	87

Show code

hierarchy_model = pd.DataFrame([
    {"level": 1, "class": "Q2", "label": "Work", "role": "top-level corpus"},
    {"level": 2, "class": "Q3", "label": "Report Series", "role": "series container"},
    {"level": 3, "class": "Q4", "label": "Report", "role": "report container"},
    {"level": 4, "class": "Q5", "label": "Text Division", "role": "division / section"},
    {"level": 5, "class": "Q6", "label": "Chapter", "role": "leaf content unit"},
])

hierarchy_view = hierarchy_model.copy()
hierarchy_view["class_uri"] = hierarchy_view["class"].map(lambda v: f"{WIKIBASE_URL}/entity/{v}")
hierarchy_view = hierarchy_view.merge(
    class_df.rename(columns={"class": "class_uri", "classLabel": "current_label", "count": "items_in_graph"}),
    on="class_uri",
    how="left"
)
hierarchy_view["items_in_graph"] = pd.to_numeric(hierarchy_view["items_in_graph"], errors="coerce").fillna(0).astype(int)

print("Canonical report hierarchy model vs current graph")
display(hierarchy_view[["level", "label", "role", "items_in_graph"]].rename(columns={"label": "expected_label"}))
print("This view shows the intended hierarchy from Work down to Chapter together with the live count of items currently represented in the graph.")

Canonical report hierarchy model vs current graph

	level	expected_label	role	items_in_graph
0	1	Work	top-level corpus	2
1	2	Report Series	series container	1
2	3	Report	report container	7
3	4	Text Division	division / section	10
4	5	Chapter	leaf content unit	87

This view shows the intended hierarchy from Work down to Chapter together with the live count of items currently represented in the graph.

Relationship check

Note: this validation block is intentionally kept as a checkpoint. It confirms whether the live graph contains the expected P3 = Part of and P4 = Parts links before the hierarchy is interpreted more broadly. We will return to it when the model is checked against the current data.

This section is a follow-up validation step: it checks whether the graph actually contains the expected P3 / P4 structure that links the hierarchy together.

Show code

p3_query = f'''
PREFIX wd: <{ENTITY_NS}>
PREFIX wdt: <{PROPERTY_NS}>

SELECT ?item ?itemLabel ?itemType ?itemTypeLabel ?parent ?parentLabel
WHERE {{
  ?item wdt:P3 ?parent .
  OPTIONAL {{ ?item wdt:P1 ?itemType . }}
  SERVICE wikibase:label {{ bd:serviceParam wikibase:language "en". }}
}}
ORDER BY ?itemLabel
LIMIT 200
'''

p4_query = f'''
PREFIX wdt: <{PROPERTY_NS}>
SELECT ?parent ?parentLabel ?child ?childLabel
WHERE {{
  ?parent wdt:P4 ?child .
  SERVICE wikibase:label {{ bd:serviceParam wikibase:language "en". }}
}}
ORDER BY ?parentLabel ?childLabel
LIMIT 200
'''

p3 = build_sparql_client(SPARQL_ENDPOINT)
p3.setQuery(p3_query)
p3.setReturnFormat(JSON)
p3_results = p3.query().convert()
p3_rows = p3_results.get("results", {}).get("bindings", [])
p3_df = pd.DataFrame([{k: v["value"] for k, v in row.items()} for row in p3_rows])

p4 = build_sparql_client(SPARQL_ENDPOINT)
p4.setQuery(p4_query)
p4.setReturnFormat(JSON)
p4_results = p4.query().convert()
p4_rows = p4_results.get("results", {}).get("bindings", [])
p4_df = pd.DataFrame([{k: v["value"] for k, v in row.items()} for row in p4_rows])

print("Direct P3 edges found:")
display(p3_df)
print("Direct P4 edges found:")
display(p4_df)

Direct P3 edges found:

	item	parent	itemType	itemLabel	itemTypeLabel	parentLabel
0	https://climatekg.tibwiki.io/entity/Q2089	https://climatekg.tibwiki.io/entity/Q10	https://climatekg.tibwiki.io/entity/Q2087	1.5DS	Acronym	Special Report: Global Warming of 1.5°C
1	https://climatekg.tibwiki.io/entity/Q1167	https://climatekg.tibwiki.io/entity/Q77	https://climatekg.tibwiki.io/entity/Q1	1.5°C pathway	Category	Working Group I: Climate Change 2021 – The Phy...
2	https://climatekg.tibwiki.io/entity/Q1167	https://climatekg.tibwiki.io/entity/Q150	https://climatekg.tibwiki.io/entity/Q1	1.5°C pathway	Category	Working Group III: Climate Change 2022 – Mitig...
3	https://climatekg.tibwiki.io/entity/Q1168	https://climatekg.tibwiki.io/entity/Q10	https://climatekg.tibwiki.io/entity/Q1	1.5°C warmer worlds	Category	Special Report: Global Warming of 1.5°C
4	https://climatekg.tibwiki.io/entity/Q1169	https://climatekg.tibwiki.io/entity/Q77	https://climatekg.tibwiki.io/entity/Q1	13C	Category	Working Group I: Climate Change 2021 – The Phy...
...	...	...	...	...	...	...
195	https://climatekg.tibwiki.io/entity/Q2660	https://climatekg.tibwiki.io/entity/Q35	https://climatekg.tibwiki.io/entity/Q2087	AWD	Acronym	Special Report: Climate Change and Land
196	https://climatekg.tibwiki.io/entity/Q3069	https://climatekg.tibwiki.io/entity/Q77	https://climatekg.tibwiki.io/entity/Q2087	AZM	Acronym	Working Group I: Climate Change 2021 – The Phy...
197	https://climatekg.tibwiki.io/entity/Q1172	https://climatekg.tibwiki.io/entity/Q77	https://climatekg.tibwiki.io/entity/Q1	Ablation	Category	Working Group I: Climate Change 2021 – The Phy...
198	https://climatekg.tibwiki.io/entity/Q1173	https://climatekg.tibwiki.io/entity/Q77	https://climatekg.tibwiki.io/entity/Q1	Abrupt change	Category	Working Group I: Climate Change 2021 – The Phy...
199	https://climatekg.tibwiki.io/entity/Q1173	https://climatekg.tibwiki.io/entity/Q106	https://climatekg.tibwiki.io/entity/Q1	Abrupt change	Category	Working Group II: Climate Change 2022 – Impact...

200 rows × 6 columns

Direct P4 edges found:

Full hierarchy contents

This table shows the items currently populating the report hierarchy, with their class, direct parent/child links, and the corresponding wiki page when it exists. It is the complete live view of the structure that the model describes.

Show code

full_hierarchy_query = f'''
PREFIX wd: <{ENTITY_NS}>
PREFIX wdt: <{PROPERTY_NS}>

SELECT ?item ?itemLabel ?class ?classLabel ?parent ?parentLabel ?child ?childLabel
WHERE {{
  VALUES ?class {{ wd:Q2 wd:Q3 wd:Q4 wd:Q5 wd:Q6 }}
  ?item wdt:P1 ?class .
  OPTIONAL {{ ?item wdt:P3 ?parent . }}
  OPTIONAL {{ ?item wdt:P4 ?child . }}
  SERVICE wikibase:label {{ bd:serviceParam wikibase:language "en". }}
}}
ORDER BY ?class ?itemLabel
'''

full_hierarchy = build_sparql_client(SPARQL_ENDPOINT)
full_hierarchy.setQuery(full_hierarchy_query)
full_hierarchy.setReturnFormat(JSON)
full_hierarchy_results = full_hierarchy.query().convert()
full_hierarchy_rows = full_hierarchy_results.get("results", {}).get("bindings", [])
full_hierarchy_df = pd.DataFrame([
    {
        "class": None,
        "classLabel": None,
        "item": None,
        "itemLabel": None,
        "parent": None,
        "parentLabel": None,
        "child": None,
        "childLabel": None,
    } | {k: v["value"] for k, v in row.items()}
    for row in full_hierarchy_rows
])

if not full_hierarchy_df.empty:
    full_hierarchy_df["item_id"] = full_hierarchy_df["item"].str.rsplit("/", n=1, expand=True)[1]
    full_hierarchy_df["wiki_url"] = full_hierarchy_df["item_id"].map(lambda v: f"{WIKIBASE_URL}/wiki/Item:{v}")
    full_hierarchy_df["nested_structure"] = full_hierarchy_df.apply(
        lambda row: f"{row['parentLabel']} -> {row['itemLabel']}" if pd.notna(row.get('parentLabel')) else row['itemLabel'],
        axis=1,
    )
    full_hierarchy_df = full_hierarchy_df[[
        "classLabel",
        "itemLabel",
        "item",
        "parent",
        "item_id",
        "wiki_url",
        "parentLabel",
        "childLabel",
        "nested_structure",
    ]].rename(columns={
        'classLabel': 'class',
        'itemLabel': 'name',
        'item': 'item',
        'parent': 'parent',
        'item_id': 'P number',
        'wiki_url': 'wiki_link',
        'parentLabel': 'parent_label',
        'childLabel': 'part',
        'nested_structure': 'nested_structure',
    })
    display(full_hierarchy_df)
else:
    print("No items found for the canonical hierarchy in the current graph.")

print("This table shows the live population of the report hierarchy and how each item is nested within it.")

	class	name	item	parent	P number	wiki_link	parent_label	part	nested_structure
0	Work	IPCC Sixth Assessment Report	https://climatekg.tibwiki.io/entity/Q7	None	Q7	https://climatekg.tibwiki.io/wiki/Item:Q7	None	None	IPCC Sixth Assessment Report
1	Work	Report Series	https://climatekg.tibwiki.io/entity/Q3	None	Q3	https://climatekg.tibwiki.io/wiki/Item:Q3	None	None	Report Series
2	Report Series	IPCC Sixth Assessment Report	https://climatekg.tibwiki.io/entity/Q7	None	Q7	https://climatekg.tibwiki.io/wiki/Item:Q7	None	None	IPCC Sixth Assessment Report
3	Report	Climate Change 2023: Synthesis Report. Contrib...	https://climatekg.tibwiki.io/entity/Q189	https://climatekg.tibwiki.io/entity/Q7	Q189	https://climatekg.tibwiki.io/wiki/Item:Q189	IPCC Sixth Assessment Report	None	IPCC Sixth Assessment Report -> Climate Change...
4	Report	Special Report: Climate Change and Land	https://climatekg.tibwiki.io/entity/Q35	https://climatekg.tibwiki.io/entity/Q7	Q35	https://climatekg.tibwiki.io/wiki/Item:Q35	IPCC Sixth Assessment Report	None	IPCC Sixth Assessment Report -> Special Report...
...	...	...	...	...	...	...	...	...	...
102	Chapter	Tropical Forests	https://climatekg.tibwiki.io/entity/Q149	https://climatekg.tibwiki.io/entity/Q137	Q149	https://climatekg.tibwiki.io/wiki/Item:Q149	Cross-Chapter Papers (Text Division)	None	Cross-Chapter Papers (Text Division) -> Tropic...
103	Chapter	Urban Systems and Other Settlements	https://climatekg.tibwiki.io/entity/Q172	https://climatekg.tibwiki.io/entity/Q153	Q172	https://climatekg.tibwiki.io/wiki/Item:Q172	Chapters (Text Division)	None	Chapters (Text Division) -> Urban Systems and ...
104	Chapter	Water	https://climatekg.tibwiki.io/entity/Q116	https://climatekg.tibwiki.io/entity/Q110	Q116	https://climatekg.tibwiki.io/wiki/Item:Q116	Chapters (Text Division)	None	Chapters (Text Division) -> Water
105	Chapter	Water Cycle Changes	https://climatekg.tibwiki.io/entity/Q96	https://climatekg.tibwiki.io/entity/Q81	Q96	https://climatekg.tibwiki.io/wiki/Item:Q96	Chapters	None	Chapters -> Water Cycle Changes
106	Chapter	Weather and Climate Extreme Events in a Changi...	https://climatekg.tibwiki.io/entity/Q101	https://climatekg.tibwiki.io/entity/Q81	Q101	https://climatekg.tibwiki.io/wiki/Item:Q101	Chapters	None	Chapters -> Weather and Climate Extreme Events...

107 rows × 9 columns

This table shows the live population of the report hierarchy and how each item is nested within it.

Questions: Report structure

From the GitHub issue: https://github.com/TIBHannover/ClimateKG-Data-Bench/issues/1

Show me the full hierarchy of AR6, from the work down to its chapters.
Which chapters of the WGII report are licensed under CC-BY, and what are their DOIs?
For AR6 report items, retrieve licence (P11) and DOI (P10) details, including the licence link where present, and identify which reports are not Creative Commons.

Question 1

Show me the full hierarchy of AR6, from the work down to its chapters.

Show code

from IPython.display import HTML, display

hierarchy_q_map = {
    "Work": "Q2",
    "Report Series": "Q3",
    "Report": "Q4",
    "Text Division": "Q5",
    "Chapter": "Q6",
}

report_tree = full_hierarchy_df.copy()

if report_tree.empty:
    print("No report hierarchy rows available to list.")
else:
    report_tree["class_q"] = report_tree["class"].map(hierarchy_q_map).fillna("Q?")
    report_tree["item"] = report_tree.get("item", pd.Series("", index=report_tree.index)).fillna("")
    report_tree["parent"] = report_tree.get("parent", pd.Series("", index=report_tree.index)).fillna("")
    report_tree["name"] = report_tree["name"].fillna("")

    report_lookup = (
        report_tree[report_tree["class"] == "Report"]
        [["item", "name"]]
        .drop_duplicates(subset=["item"], keep="first")
        .set_index("item")["name"]
        .to_dict()
    )

    work_rows = report_tree[report_tree["class"] == "Work"].drop_duplicates(subset=["item"], keep="first").sort_values("name")
    work_rows = work_rows[~work_rows["item"].fillna("").str.endswith("/Q3", na=False)].copy()
    work_rows = work_rows[~work_rows["name"].fillna("").str.strip().eq("Report Series")].copy()
    series_rows = report_tree[report_tree["class"] == "Report Series"].drop_duplicates(subset=["item"], keep="first").sort_values("name")
    series_rows = series_rows[~series_rows["item"].fillna("").str.endswith("/Q3", na=False)].copy()
    series_rows = series_rows[~series_rows["name"].fillna("").str.strip().eq("Report Series")].copy()
    helper_q7_rows = report_tree[report_tree["item"].str.endswith("/Q7", na=False)].copy()
    helper_q7_rows = helper_q7_rows[~helper_q7_rows["name"].fillna("").str.strip().eq("Report Series")].copy()
    if not helper_q7_rows.empty:
        helper_q7_rows = helper_q7_rows[(helper_q7_rows["class"] == "Work") | (helper_q7_rows["class"] == "Report Series")].copy()
        helper_q7_rows["display_name"] = helper_q7_rows["name"].fillna("Q7")
        if series_rows.empty:
            series_rows = helper_q7_rows[["item", "display_name", "wiki_link"]].rename(columns={"display_name": "name"})
        if work_rows.empty:
            work_rows = helper_q7_rows[["item", "display_name", "wiki_link"]].rename(columns={"display_name": "name"})
    text_divisions = report_tree[report_tree["class"] == "Text Division"].copy()
    text_divisions["report_name"] = text_divisions["parent"].map(report_lookup).fillna("Unassigned")

    chapters = report_tree[report_tree["class"] == "Chapter"].copy()
    td_lookup = (
        text_divisions[["item", "name"]]
        .drop_duplicates(subset=["item"], keep="first")
        .set_index("item")["name"]
        .to_dict()
    )
    chapters["text_division_name"] = chapters["parent"].map(td_lookup).fillna("Unassigned")

    reports = (
        report_tree[report_tree["class"] == "Report"]
        .drop_duplicates(subset=["item"], keep="first")
        .sort_values("name")
    )

    def render_title(row, label_field="name"):
        label = row.get(label_field) or row.get("name") or "Unnamed item"
        item_ref = row.get("item")
        item_id = item_ref.rsplit("/", 1)[-1] if isinstance(item_ref, str) and "/" in item_ref else None
        if item_id:
            label = f"{label} ({item_id})"
        if pd.notna(row.get("wiki_link")) and str(row["wiki_link"]).strip():
            return f'<a href="{row["wiki_link"]}" target="_blank">{label}</a>'
        return str(label)

    html_parts = ['<div><strong>Work, report series, and nested report structure</strong><ul>']

    if work_rows.empty:
        html_parts.append('<li><em>No work items found.</em></li>')
    else:
        for _, work_row in work_rows.iterrows():
            work_title = render_title(work_row)
            html_parts.append(f'<li><strong>Work:</strong> {work_title}<ul>')

            display_series = series_rows[series_rows["item"] == work_row["item"]].copy()
            if display_series.empty and not helper_q7_rows.empty:
                display_series = helper_q7_rows[helper_q7_rows["item"] == work_row["item"]].copy()
            if display_series.empty:
                display_series = pd.DataFrame(columns=["item", "name", "wiki_link"])

            for _, series_row in display_series.iterrows():
                series_title = render_title(series_row)
                html_parts.append(f'<li><strong>Report Series:</strong> {series_title}<ul>')

                series_reports = reports[reports["parent"] == series_row["item"]].drop_duplicates(subset=["item"], keep="first").sort_values("name")
                if series_reports.empty:
                    series_reports = reports[reports["parent"] == work_row["item"]].drop_duplicates(subset=["item"], keep="first").sort_values("name")

                if series_reports.empty:
                    html_parts.append('</ul></li>')
                    continue

                for _, report_row in series_reports.iterrows():
                    report_uri = report_row["item"]
                    report_title = render_title(report_row)
                    html_parts.append(f'<li><strong>{report_title}</strong> -- {report_row["class"]} ({report_row["class_q"]})<ul>')

                    report_text_divisions = text_divisions[
                        text_divisions["parent"] == report_uri
                    ].drop_duplicates(subset=["item"], keep="first").sort_values("name")

                    if report_text_divisions.empty:
                        html_parts.append('<li><em>No text divisions nested under this report.</em></li>')
                    else:
                        for _, td in report_text_divisions.iterrows():
                            td_title = render_title(td)
                            html_parts.append(f'<li><strong>{td_title}</strong> -- {td["class"]} ({td["class_q"]})<ul>')

                            report_chapters = chapters[
                                (chapters["parent"] == td["item"]) | (chapters["item"] == td["item"])
                            ].drop_duplicates(subset=["item"], keep="first").sort_values("name")

                            if report_chapters.empty:
                                html_parts.append('<li><em>No chapters nested under this text division.</em></li>')
                            else:
                                for _, ch in report_chapters.iterrows():
                                    ch_title = render_title(ch)
                                    html_parts.append(f'<li>{ch_title} -- {ch["class"]} ({ch["class_q"]})</li>')

                            html_parts.append('</ul></li>')

                    html_parts.append('</ul></li>')

                html_parts.append('</ul></li>')

            if series_rows.empty and not reports[reports["parent"] == work_row["item"]].empty:
                direct_reports = reports[reports["parent"] == work_row["item"]].drop_duplicates(subset=["item"], keep="first").sort_values("name")
                if not direct_reports.empty:
                    html_parts.append('<li><strong>Reports directly under this work:</strong><ul>')
                    for _, report_row in direct_reports.iterrows():
                        report_title = render_title(report_row)
                        html_parts.append(f'<li>{report_title} -- {report_row["class"]} ({report_row["class_q"]})</li>')
                    html_parts.append('</ul></li>')

    html_parts.append('</ul></div>')
    display(HTML(''.join(html_parts)))

print("This view shows the full Report hierarchy, including Work and Report Series above the report entries.")

Work, report series, and nested report structure

Work: IPCC Sixth Assessment Report (Q7)
- Report Series: IPCC Sixth Assessment Report (Q7)
  - Climate Change 2023: Synthesis Report. Contribution of Working Groups I, II and III to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (Q189) -- Report (Q4)
    - Chapters (Text Division) (Q191) -- Text Division (Q5)
      - Longer Report (Q192) -- Chapter (Q6)
  - Special Report: Climate Change and Land (Q35) -- Report (Q4)
    - Chapters (Text Division) (Q42) -- Text Division (Q5)
      - Desertification (Q48) -- Chapter (Q6)
      - Food security (Q53) -- Chapter (Q6)
      - Framing and context (Q44) -- Chapter (Q6)
      - Interlinkages between desertification, land degradation, food security and greenhouse gas fluxes: Synergies, trade-offs and integrated response options (Q54) -- Chapter (Q6)
      - Land degradation (Q50) -- Chapter (Q6)
      - Land–climate interactions (Q45) -- Chapter (Q6)
      - Risk management and decision-making in relation to sustainable development (Q55) -- Chapter (Q6)
  - Special Report: Global Warming of 1.5°C (Q10) -- Report (Q4)
    - Chapters (Text Division) (Q18) -- Text Division (Q5)
      - Framing and Context (Q21) -- Chapter (Q6)
      - Impacts of 1.5°C Global Warming on Natural and Human Systems (Q26) -- Chapter (Q6)
      - Mitigation Pathways Compatible with 1.5°C in the Context of Sustainable Development (Q24) -- Chapter (Q6)
      - Strengthening and Implementing the Global Response (Q30) -- Chapter (Q6)
      - Sustainable Development, Poverty Eradication and Reducing Inequalities (Q33) -- Chapter (Q6)
  - Special Report: The Ocean and Cryosphere in a Changing Climate (Q57) -- Report (Q4)
    - Chapters (Text Division) (Q62) -- Text Division (Q5)
      - Changing Ocean, Marine Ecosystems, and Dependent Communities (Q72) -- Chapter (Q6)
      - Extremes, Abrupt Changes and Managing Risks (Q74) -- Chapter (Q6)
      - Framing and Context of the Report (Q64) -- Chapter (Q6)
      - High Mountain Areas (Q67) -- Chapter (Q6)
      - Polar Regions (Q69) -- Chapter (Q6)
      - Sea Level Rise and Implications for Low-Lying Islands, Coasts and Communities (Q71) -- Chapter (Q6)
    - Cross-Chapter Box (Text Division) (Q75) -- Text Division (Q5)
      - Integrative Cross-Chapter Box on Low-lying Islands and Coasts (Q76) -- Chapter (Q6)
  - Working Group I: Climate Change 2021 – The Physical Science Basis (Q77) -- Report (Q4)
    - Atlas (Text Division) (Q104) -- Text Division (Q5)
      - Atlas (Text Division) (Q104) -- Chapter (Q6)
    - Chapters (Q81) -- Text Division (Q5)
      - Changing State of the Climate System (Q85) -- Chapter (Q6)
      - Climate Change Information for Regional Impact and for Risk Assessment (Q103) -- Chapter (Q6)
      - Framing, Context, and Methods (Q83) -- Chapter (Q6)
      - Future Global Climate: Scenario-based Projections and Near-term Information (Q88) -- Chapter (Q6)
      - Global Carbon and Other Biogeochemical Cycles and Feedbacks (Q90) -- Chapter (Q6)
      - Human Influence on the Climate System (Q87) -- Chapter (Q6)
      - Linking Global to Regional Climate Change (Q100) -- Chapter (Q6)
      - Ocean, Cryosphere and Sea Level Change (Q98) -- Chapter (Q6)
      - Short-lived Climate Forcers (Q93) -- Chapter (Q6)
      - The Earth’s Energy Budget, Climate Feedbacks and Climate Sensitivity (Q95) -- Chapter (Q6)
      - Water Cycle Changes (Q96) -- Chapter (Q6)
      - Weather and Climate Extreme Events in a Changing Climate (Q101) -- Chapter (Q6)
  - Working Group II: Climate Change 2022 – Impacts, Adaptation and Vulnerability (Q106) -- Report (Q4)
    - Chapters (Text Division) (Q110) -- Text Division (Q5)
      - Africa (Q126) -- Chapter (Q6)
      - Asia (Q127) -- Chapter (Q6)
      - Central and South America (Q129) -- Chapter (Q6)
      - Cities, Settlements and Key Infrastructure (Q120) -- Chapter (Q6)
      - Climate Resilient Development Pathways (Q136) -- Chapter (Q6)
      - Decision-Making Options for Managing Risk (Q135) -- Chapter (Q6)
      - Europe (Q130) -- Chapter (Q6)
      - Food, Fibre and Other Ecosystem Products (Q117) -- Chapter (Q6)
      - Health, Wellbeing and the Changing Structure of Communities (Q123) -- Chapter (Q6)
      - Key Risks across Sectors and Regions (Q133) -- Chapter (Q6)
      - North America (Q131) -- Chapter (Q6)
      - Oceans and Coastal Ecosystems and Their Services (Q114) -- Chapter (Q6)
      - Point of Departure and Key Concepts (Q111) -- Chapter (Q6)
      - Poverty, Livelihoods and Sustainable Development (Q125) -- Chapter (Q6)
      - Small Islands (Q132) -- Chapter (Q6)
      - Terrestrial and Freshwater Ecosystems and Their Services (Q112) -- Chapter (Q6)
      - Water (Q116) -- Chapter (Q6)
    - Cross-Chapter Papers (Text Division) (Q137) -- Text Division (Q5)
      - Biodiversity Hotspots (Q140) -- Chapter (Q6)
      - Cities and Settlements by the Sea (Q141) -- Chapter (Q6)
      - Deserts, Semiarid Areas and Desertification (Q142) -- Chapter (Q6)
      - Mediterranean Region (Q143) -- Chapter (Q6)
      - Mountains (Q145) -- Chapter (Q6)
      - Polar Regions (Q146) -- Chapter (Q6)
      - Tropical Forests (Q149) -- Chapter (Q6)
  - Working Group III: Climate Change 2022 – Mitigation of Climate Change (Q150) -- Report (Q4)
    - Chapters (Text Division) (Q153) -- Text Division (Q5)
      - Accelerating the Transition in the Context of Sustainable Development (Q188) -- Chapter (Q6)
      - Agriculture, Forestry and Other Land Uses (AFOLU) (Q170) -- Chapter (Q6)
      - Buildings (Q174) -- Chapter (Q6)
      - Cross-sectoral Perspectives (Q179) -- Chapter (Q6)
      - Demand, Services and Social Aspects of Mitigation (Q164) -- Chapter (Q6)
      - Emissions Trends and Drivers (Q157) -- Chapter (Q6)
      - Energy Systems (Q168) -- Chapter (Q6)
      - Industry (Q178) -- Chapter (Q6)
      - Innovation, Technology Development and Transfer (Q186) -- Chapter (Q6)
      - International Cooperation (Q183) -- Chapter (Q6)
      - Introduction and Framing (Q154) -- Chapter (Q6)
      - Investment and Finance (Q184) -- Chapter (Q6)
      - Mitigation Pathways Compatible with Long-term Goals (Q158) -- Chapter (Q6)
      - Mitigation and Development Pathways in the Near to Mid-term (Q160) -- Chapter (Q6)
      - National and Sub-national Policies and Institutions (Q181) -- Chapter (Q6)
      - Transport (Q176) -- Chapter (Q6)
      - Urban Systems and Other Settlements (Q172) -- Chapter (Q6)

This view shows the full Report hierarchy, including Work and Report Series above the report entries.

Searchable nested hierarchy

This view turns the table into a readable hierarchy so a reader can quickly find a report part and trace its position in the corpus from the top-level work down to the chapter or section it belongs to.

Show code

import html
import json
import uuid
from IPython.display import HTML, display

hierarchy_lookup = full_hierarchy_df.copy()
hierarchy_lookup["class_rank"] = hierarchy_lookup["class"].map({"Work": 1, "Report Series": 2, "Report": 3, "Text Division": 4, "Chapter": 5}).fillna(99)
hierarchy_lookup["path"] = hierarchy_lookup["nested_structure"].fillna(hierarchy_lookup["name"])
hierarchy_lookup = hierarchy_lookup.sort_values(["class_rank", "name"]).drop_duplicates(subset=["name"], keep="first")

search_rows = []
for _, row in hierarchy_lookup.iterrows():
    wiki_link = row.get("wiki_link")
    search_rows.append(
        {
            "name": "" if pd.isna(row.get("name")) else str(row.get("name")),
            "path": "" if pd.isna(row.get("path")) else str(row.get("path")),
            "class": "" if pd.isna(row.get("class")) else str(row.get("class")),
            "parent": "top level" if pd.isna(row.get("parent")) else str(row.get("parent")),
            "wiki_link": "" if pd.isna(wiki_link) else str(wiki_link).strip(),
        }
    )

widget_id = f"hierarchy-search-{uuid.uuid4().hex[:8]}"
data_json = json.dumps(search_rows).replace("</", "<\\/")

html_block = f"""
<div style='max-width:900px'>
  <label for='{widget_id}-input'><strong>Find report part:</strong></label><br>
  <input id='{widget_id}-input' type='text' placeholder='Search names or path...' style='width:100%;max-width:500px;padding:6px 8px;margin:6px 0 12px 0;border:1px solid #bbb;border-radius:4px;'>
  <div id='{widget_id}-results'></div>
</div>
<script>
(function () {{
  const data = {data_json};
  const input = document.getElementById('{widget_id}-input');
  const results = document.getElementById('{widget_id}-results');

  function escapeHtml(value) {{
    return String(value)
      .replaceAll('&', '&amp;')
      .replaceAll('<', '&lt;')
      .replaceAll('>', '&gt;')
      .replaceAll('"', '&quot;')
      .replaceAll("'", '&#039;');
  }}

  function safeLink(url) {{
    if (!url) return '';
    const lower = String(url).toLowerCase();
    if (lower.startsWith('http://') || lower.startsWith('https://')) return url;
    return '';
  }}

  function render() {{
    const query = (input.value || '').trim().toLowerCase();
    const matches = !query
      ? data
      : data.filter((row) =>
          row.name.toLowerCase().includes(query) ||
          row.path.toLowerCase().includes(query) ||
          row.class.toLowerCase().includes(query)
        );

    const rows = matches.slice(0, 50).map((row) => {{
      const url = safeLink(row.wiki_link);
      const label = url
        ? `<a href="${{encodeURI(url)}}" target="_blank" rel="noopener noreferrer">${{escapeHtml(row.name)}}</a>`
        : escapeHtml(row.name);
      return `<li><strong>${{label}}</strong> (${{escapeHtml(row.class)}})<br>Parent: ${{escapeHtml(row.parent)}}<br>Path: ${{escapeHtml(row.path)}}</li>`;
    }}).join('');

    results.innerHTML = `<div><strong>Nested report hierarchy</strong><ul>${{rows || '<li>No matching report part found.</li>'}}</ul></div>`;
  }}

  input.addEventListener('input', render);
  render();
}})();
</script>
"""

display(HTML(html_block))

Find report part:

Question 2

Which chapters of the WGII report are licensed under CC-BY, and what are their DOIs?

Show code

wgii_chapters_query = f'''
PREFIX wd: <{ENTITY_NS}>
PREFIX wdt: <{PROPERTY_NS}>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>

SELECT DISTINCT ?report ?reportLabel ?chapter ?chapterLabel ?doi
WHERE {{
  ?chapter wdt:P1 wd:Q6 .
  ?chapter wdt:P3 ?textDivision .
  ?textDivision wdt:P1 wd:Q5 .
  ?textDivision wdt:P3 ?report .
  ?report wdt:P1 wd:Q4 ; rdfs:label ?reportLabel .
  FILTER(LANG(?reportLabel) = "en")
  FILTER(CONTAINS(LCASE(?reportLabel), "working group ii:"))

  OPTIONAL {{
    ?chapter wdt:P10 ?doiValue .
    BIND(STR(?doiValue) AS ?doi)
  }}

  SERVICE wikibase:label {{ bd:serviceParam wikibase:language "en". }}
}}
ORDER BY ?chapterLabel
'''

print("SPARQL query for WGII chapter list:")
print(wgii_chapters_query)

wgii_client = build_sparql_client(SPARQL_ENDPOINT)
wgii_client.setQuery(wgii_chapters_query)
wgii_client.setReturnFormat(JSON)
wgii_results = wgii_client.query().convert()
wgii_rows = wgii_results.get("results", {}).get("bindings", [])

wgii_chapters_df = pd.DataFrame([{k: v["value"] for k, v in row.items()} for row in wgii_rows])

if wgii_chapters_df.empty:
    print("No WGII chapters found.")
else:
    for col in ["report", "reportLabel", "chapter", "chapterLabel", "doi"]:
        if col not in wgii_chapters_df.columns:
            wgii_chapters_df[col] = ""

    wgii_chapters_df["report_qid"] = wgii_chapters_df["report"].astype(str).str.rsplit("/", n=1).str[-1]
    wgii_chapters_df["chapter_qid"] = wgii_chapters_df["chapter"].astype(str).str.rsplit("/", n=1).str[-1]
    wgii_chapters_df["doi"] = wgii_chapters_df["doi"].fillna("").astype(str)

    # De-duplicate by chapter item identity, not label text.
    wgii_chapters_df = wgii_chapters_df.sort_values(["chapterLabel", "doi"]).drop_duplicates(subset=["chapter_qid"], keep="first")

    print(f"WGII chapters returned (deduplicated by chapter QID): {len(wgii_chapters_df)}")
    display(
        wgii_chapters_df[["reportLabel", "report_qid", "chapterLabel", "chapter_qid", "doi"]]
        .rename(columns={
            "reportLabel": "report",
            "chapterLabel": "chapter",
            "doi": "doi (P10)",
        })
    )

SPARQL query for WGII chapter list:

PREFIX wd: <https://climatekg.tibwiki.io/entity/>
PREFIX wdt: <https://climatekg.tibwiki.io/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>

SELECT DISTINCT ?report ?reportLabel ?chapter ?chapterLabel ?doi
WHERE {
  ?chapter wdt:P1 wd:Q6 .
  ?chapter wdt:P3 ?textDivision .
  ?textDivision wdt:P1 wd:Q5 .
  ?textDivision wdt:P3 ?report .
  ?report wdt:P1 wd:Q4 ; rdfs:label ?reportLabel .
  FILTER(LANG(?reportLabel) = "en")
  FILTER(CONTAINS(LCASE(?reportLabel), "working group ii:"))

  OPTIONAL {
    ?chapter wdt:P10 ?doiValue .
    BIND(STR(?doiValue) AS ?doi)
  }

  SERVICE wikibase:label { bd:serviceParam wikibase:language "en". }
}
ORDER BY ?chapterLabel

WGII chapters returned (deduplicated by chapter QID): 24

	report	report_qid	chapter	chapter_qid	doi (P10)
0	Working Group II: Climate Change 2022 – Impact...	Q106	Africa	Q126	10.1017/9781009325844.011
1	Working Group II: Climate Change 2022 – Impact...	Q106	Asia	Q127	10.1017/9781009325844.012
2	Working Group II: Climate Change 2022 – Impact...	Q106	Biodiversity Hotspots	Q140	10.1017/9781009325844.018
3	Working Group II: Climate Change 2022 – Impact...	Q106	Central and South America	Q129	10.1017/9781009325844.014
4	Working Group II: Climate Change 2022 – Impact...	Q106	Cities and Settlements by the Sea	Q141	10.1017/9781009325844.019
5	Working Group II: Climate Change 2022 – Impact...	Q106	Cities, Settlements and Key Infrastructure	Q120	10.1017/9781009325844.008
6	Working Group II: Climate Change 2022 – Impact...	Q106	Climate Resilient Development Pathways	Q136	10.1017/9781009325844.027
7	Working Group II: Climate Change 2022 – Impact...	Q106	Decision-Making Options for Managing Risk	Q135	10.1017/9781009325844.026
8	Working Group II: Climate Change 2022 – Impact...	Q106	Deserts, Semiarid Areas and Desertification	Q142	10.1017/9781009325844.020
9	Working Group II: Climate Change 2022 – Impact...	Q106	Europe	Q130	10.1017/9781009325844.015
10	Working Group II: Climate Change 2022 – Impact...	Q106	Food, Fibre and Other Ecosystem Products	Q117	10.1017/9781009325844.007
11	Working Group II: Climate Change 2022 – Impact...	Q106	Health, Wellbeing and the Changing Structure o...	Q123	10.1017/9781009325844.009
12	Working Group II: Climate Change 2022 – Impact...	Q106	Key Risks across Sectors and Regions	Q133	10.1017/9781009325844.025
13	Working Group II: Climate Change 2022 – Impact...	Q106	Mediterranean Region	Q143	10.1017/9781009325844.021
14	Working Group II: Climate Change 2022 – Impact...	Q106	Mountains	Q145	10.1017/9781009325844.022
15	Working Group II: Climate Change 2022 – Impact...	Q106	North America	Q131	10.1017/9781009325844.016
16	Working Group II: Climate Change 2022 – Impact...	Q106	Oceans and Coastal Ecosystems and Their Services	Q114	10.1017/9781009325844.005
17	Working Group II: Climate Change 2022 – Impact...	Q106	Point of Departure and Key Concepts	Q111	10.1017/9781009325844.003
18	Working Group II: Climate Change 2022 – Impact...	Q106	Polar Regions	Q146	10.1017/9781009325844.023
19	Working Group II: Climate Change 2022 – Impact...	Q106	Poverty, Livelihoods and Sustainable Development	Q125	10.1017/9781009325844.010
20	Working Group II: Climate Change 2022 – Impact...	Q106	Small Islands	Q132	10.1017/9781009325844.017
21	Working Group II: Climate Change 2022 – Impact...	Q106	Terrestrial and Freshwater Ecosystems and Thei...	Q112	10.1017/9781009325844.004
22	Working Group II: Climate Change 2022 – Impact...	Q106	Tropical Forests	Q149	10.1017/9781009325844.024
23	Working Group II: Climate Change 2022 – Impact...	Q106	Water	Q116	10.1017/9781009325844.006

Show code

q2_query = f'''
PREFIX wd: <{ENTITY_NS}>
PREFIX wdt: <{PROPERTY_NS}>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>

SELECT DISTINCT ?report ?reportLabel ?chapter ?chapterLabel ?doi ?license ?licenseLabel ?licenseLink
WHERE {{
  ?chapter wdt:P1 wd:Q6 .
  ?chapter wdt:P3 ?textDivision .
  ?textDivision wdt:P1 wd:Q5 .
  ?textDivision wdt:P3 ?report .
  ?report wdt:P1 wd:Q4 ; rdfs:label ?reportLabel .
  FILTER(LANG(?reportLabel) = "en")
  FILTER(CONTAINS(LCASE(?reportLabel), "working group ii:"))

  OPTIONAL {{
    ?chapter wdt:P10 ?doiValue .
    BIND(STR(?doiValue) AS ?doi)
  }}

  OPTIONAL {{
    ?report wdt:P11 ?license .
    OPTIONAL {{ ?license rdfs:label ?licenseLabel . FILTER(LANG(?licenseLabel) = "en") }}
    BIND(
      IF(
        isIRI(?license),
        STR(?license),
        IF(REGEX(STR(?license), "^https?://"), STR(?license), "")
      ) AS ?licenseLink
    )
  }}

  SERVICE wikibase:label {{ bd:serviceParam wikibase:language "en". }}

  BIND(COALESCE(?licenseLabel, STR(?license), "") AS ?licenseText)
  FILTER(
    REGEX(LCASE(?licenseText), "creative commons|cc[- ]?by|cc by")
    || REGEX(LCASE(COALESCE(?licenseLink, "")), "creativecommons.org")
  )
}}
ORDER BY ?chapterLabel
'''

print("SPARQL query for Question 2:")
print(q2_query)

q2_client = build_sparql_client(SPARQL_ENDPOINT)
q2_client.setQuery(q2_query)
q2_client.setReturnFormat(JSON)
q2_results = q2_client.query().convert()
q2_rows = q2_results.get("results", {}).get("bindings", [])

q2_df = pd.DataFrame([{k: v["value"] for k, v in row.items()} for row in q2_rows])

if q2_df.empty:
    print("No WGII chapters with inherited report-level Creative Commons licensing were returned.")
else:
    expected_cols = ["report", "reportLabel", "chapter", "chapterLabel", "doi", "licenseLabel", "license", "licenseLink"]
    for col in expected_cols:
        if col not in q2_df.columns:
            q2_df[col] = ""

    q2_df["report_qid"] = q2_df["report"].astype(str).str.rsplit("/", n=1).str[-1]
    q2_df["chapter_qid"] = q2_df["chapter"].astype(str).str.rsplit("/", n=1).str[-1]
    q2_df["license_qid"] = q2_df["license"].astype(str).where(
        q2_df["license"].astype(str).str.contains("/entity/", regex=False),
        ""
    ).str.rsplit("/", n=1).str[-1]
    q2_df["doi"] = q2_df["doi"].fillna("").astype(str)

    # De-duplicate by report+chapter item identity.
    q2_df = q2_df.sort_values(["chapterLabel", "doi"]).drop_duplicates(subset=["report_qid", "chapter_qid"], keep="first")

    q2_display = pd.DataFrame({
        "report": q2_df["reportLabel"].fillna("").astype(str),
        "report_qid": q2_df["report_qid"],
        "chapter": q2_df["chapterLabel"].fillna("").astype(str),
        "chapter_qid": q2_df["chapter_qid"],
        "doi (chapter P10)": q2_df["doi"],
        "inherited_license_label (report P11)": q2_df["licenseLabel"].fillna("").astype(str),
        "inherited_license_qid": q2_df["license_qid"],
        "inherited_license_value (report P11)": q2_df["license"].fillna("").astype(str),
        "inherited_license_link": q2_df["licenseLink"].fillna("").astype(str),
    })

    print(f"WGII chapters with inherited Creative Commons report licensing (deduplicated): {len(q2_display)}")
    display(q2_display)

SPARQL query for Question 2:

PREFIX wd: <https://climatekg.tibwiki.io/entity/>
PREFIX wdt: <https://climatekg.tibwiki.io/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>

SELECT DISTINCT ?report ?reportLabel ?chapter ?chapterLabel ?doi ?license ?licenseLabel ?licenseLink
WHERE {
  ?chapter wdt:P1 wd:Q6 .
  ?chapter wdt:P3 ?textDivision .
  ?textDivision wdt:P1 wd:Q5 .
  ?textDivision wdt:P3 ?report .
  ?report wdt:P1 wd:Q4 ; rdfs:label ?reportLabel .
  FILTER(LANG(?reportLabel) = "en")
  FILTER(CONTAINS(LCASE(?reportLabel), "working group ii:"))

  OPTIONAL {
    ?chapter wdt:P10 ?doiValue .
    BIND(STR(?doiValue) AS ?doi)
  }

  OPTIONAL {
    ?report wdt:P11 ?license .
    OPTIONAL { ?license rdfs:label ?licenseLabel . FILTER(LANG(?licenseLabel) = "en") }
    BIND(
      IF(
        isIRI(?license),
        STR(?license),
        IF(REGEX(STR(?license), "^https?://"), STR(?license), "")
      ) AS ?licenseLink
    )
  }

  SERVICE wikibase:label { bd:serviceParam wikibase:language "en". }

  BIND(COALESCE(?licenseLabel, STR(?license), "") AS ?licenseText)
  FILTER(
    REGEX(LCASE(?licenseText), "creative commons|cc[- ]?by|cc by")
    || REGEX(LCASE(COALESCE(?licenseLink, "")), "creativecommons.org")
  )
}
ORDER BY ?chapterLabel

WGII chapters with inherited Creative Commons report licensing (deduplicated): 24

	report	report_qid	chapter	chapter_qid	doi (chapter P10)	inherited_license_label (report P11)	inherited_license_value (report P11)
0	Working Group II: Climate Change 2022 – Impact...	Q106	Africa	Q126	10.1017/9781009325844.011	CC-BY-NC-ND 4.0	CC-BY-NC-ND 4.0
1	Working Group II: Climate Change 2022 – Impact...	Q106	Asia	Q127	10.1017/9781009325844.012	CC-BY-NC-ND 4.0	CC-BY-NC-ND 4.0
2	Working Group II: Climate Change 2022 – Impact...	Q106	Biodiversity Hotspots	Q140	10.1017/9781009325844.018	CC-BY-NC-ND 4.0	CC-BY-NC-ND 4.0
3	Working Group II: Climate Change 2022 – Impact...	Q106	Central and South America	Q129	10.1017/9781009325844.014	CC-BY-NC-ND 4.0	CC-BY-NC-ND 4.0
4	Working Group II: Climate Change 2022 – Impact...	Q106	Cities and Settlements by the Sea	Q141	10.1017/9781009325844.019	CC-BY-NC-ND 4.0	CC-BY-NC-ND 4.0
5	Working Group II: Climate Change 2022 – Impact...	Q106	Cities, Settlements and Key Infrastructure	Q120	10.1017/9781009325844.008	CC-BY-NC-ND 4.0	CC-BY-NC-ND 4.0
6	Working Group II: Climate Change 2022 – Impact...	Q106	Climate Resilient Development Pathways	Q136	10.1017/9781009325844.027	CC-BY-NC-ND 4.0	CC-BY-NC-ND 4.0
7	Working Group II: Climate Change 2022 – Impact...	Q106	Decision-Making Options for Managing Risk	Q135	10.1017/9781009325844.026	CC-BY-NC-ND 4.0	CC-BY-NC-ND 4.0
8	Working Group II: Climate Change 2022 – Impact...	Q106	Deserts, Semiarid Areas and Desertification	Q142	10.1017/9781009325844.020	CC-BY-NC-ND 4.0	CC-BY-NC-ND 4.0
9	Working Group II: Climate Change 2022 – Impact...	Q106	Europe	Q130	10.1017/9781009325844.015	CC-BY-NC-ND 4.0	CC-BY-NC-ND 4.0
10	Working Group II: Climate Change 2022 – Impact...	Q106	Food, Fibre and Other Ecosystem Products	Q117	10.1017/9781009325844.007	CC-BY-NC-ND 4.0	CC-BY-NC-ND 4.0
11	Working Group II: Climate Change 2022 – Impact...	Q106	Health, Wellbeing and the Changing Structure o...	Q123	10.1017/9781009325844.009	CC-BY-NC-ND 4.0	CC-BY-NC-ND 4.0
12	Working Group II: Climate Change 2022 – Impact...	Q106	Key Risks across Sectors and Regions	Q133	10.1017/9781009325844.025	CC-BY-NC-ND 4.0	CC-BY-NC-ND 4.0
13	Working Group II: Climate Change 2022 – Impact...	Q106	Mediterranean Region	Q143	10.1017/9781009325844.021	CC-BY-NC-ND 4.0	CC-BY-NC-ND 4.0
14	Working Group II: Climate Change 2022 – Impact...	Q106	Mountains	Q145	10.1017/9781009325844.022	CC-BY-NC-ND 4.0	CC-BY-NC-ND 4.0
15	Working Group II: Climate Change 2022 – Impact...	Q106	North America	Q131	10.1017/9781009325844.016	CC-BY-NC-ND 4.0	CC-BY-NC-ND 4.0
16	Working Group II: Climate Change 2022 – Impact...	Q106	Oceans and Coastal Ecosystems and Their Services	Q114	10.1017/9781009325844.005	CC-BY-NC-ND 4.0	CC-BY-NC-ND 4.0
17	Working Group II: Climate Change 2022 – Impact...	Q106	Point of Departure and Key Concepts	Q111	10.1017/9781009325844.003	CC-BY-NC-ND 4.0	CC-BY-NC-ND 4.0
18	Working Group II: Climate Change 2022 – Impact...	Q106	Polar Regions	Q146	10.1017/9781009325844.023	CC-BY-NC-ND 4.0	CC-BY-NC-ND 4.0
19	Working Group II: Climate Change 2022 – Impact...	Q106	Poverty, Livelihoods and Sustainable Development	Q125	10.1017/9781009325844.010	CC-BY-NC-ND 4.0	CC-BY-NC-ND 4.0
20	Working Group II: Climate Change 2022 – Impact...	Q106	Small Islands	Q132	10.1017/9781009325844.017	CC-BY-NC-ND 4.0	CC-BY-NC-ND 4.0
21	Working Group II: Climate Change 2022 – Impact...	Q106	Terrestrial and Freshwater Ecosystems and Thei...	Q112	10.1017/9781009325844.004	CC-BY-NC-ND 4.0	CC-BY-NC-ND 4.0
22	Working Group II: Climate Change 2022 – Impact...	Q106	Tropical Forests	Q149	10.1017/9781009325844.024	CC-BY-NC-ND 4.0	CC-BY-NC-ND 4.0
23	Working Group II: Climate Change 2022 – Impact...	Q106	Water	Q116	10.1017/9781009325844.006	CC-BY-NC-ND 4.0	CC-BY-NC-ND 4.0

Question 3

For AR6 report items, retrieve licence (P11) and DOI (P10) details, including the licence link where present, and identify which reports are not Creative Commons.

Show code

q3_query = f'''
PREFIX wd: <{ENTITY_NS}>
PREFIX wdt: <{PROPERTY_NS}>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>

SELECT ?report ?reportLabel ?doi ?license ?licenseLabel ?licenseLink ?ccStatus
WHERE {{
  ?report wdt:P1 wd:Q4 ; rdfs:label ?reportLabel .
  FILTER(LANG(?reportLabel) = "en")

  OPTIONAL {{
    ?report wdt:P10 ?doiValue .
    BIND(STR(?doiValue) AS ?doi)
  }}

  OPTIONAL {{
    ?report wdt:P11 ?license .
    OPTIONAL {{ ?license rdfs:label ?licenseLabel . FILTER(LANG(?licenseLabel) = "en") }}
    BIND(
      IF(
        isIRI(?license),
        STR(?license),
        IF(REGEX(STR(?license), "^https?://"), STR(?license), "")
      ) AS ?licenseLink
    )
  }}

  BIND(COALESCE(?licenseLabel, STR(?license), "No license value") AS ?licenseText)
  BIND(
    IF(
      REGEX(LCASE(?licenseText), "creative commons|cc[- ]?by|cc[- ]?0|cc by"),
      "Creative Commons",
      "Not clearly Creative Commons"
    ) AS ?ccStatus
  )
}}
ORDER BY ?reportLabel
'''

print("SPARQL query for Question 3:")
print(q3_query)

q3_client = build_sparql_client(SPARQL_ENDPOINT)
q3_client.setQuery(q3_query)
q3_client.setReturnFormat(JSON)
q3_results = q3_client.query().convert()
q3_rows = q3_results.get("results", {}).get("bindings", [])

q3_df = pd.DataFrame([{k: v["value"] for k, v in row.items()} for row in q3_rows])

if q3_df.empty:
    print("No report-level P11/P10 rows were returned.")
else:
    expected_cols = ["reportLabel", "doi", "licenseLabel", "license", "licenseLink", "ccStatus"]
    for col in expected_cols:
        if col not in q3_df.columns:
            q3_df[col] = ""

    display_df = pd.DataFrame({
        "report": q3_df["reportLabel"].fillna("").astype(str),
        "doi (P10)": q3_df["doi"].fillna("").astype(str),
        "license_label": q3_df["licenseLabel"].fillna("").astype(str),
        "license_value (P11)": q3_df["license"].fillna("").astype(str),
        "license_link": q3_df["licenseLink"].fillna("").astype(str),
        "creative_commons_status": q3_df["ccStatus"].fillna("Not clearly Creative Commons").astype(str),
    })

    print(f"Report metadata rows returned: {len(display_df)}")
    display(display_df)

    status_summary = (
        display_df[["report", "creative_commons_status"]]
        .drop_duplicates()
        .groupby("creative_commons_status", as_index=False)["report"]
        .count()
        .rename(columns={"report": "report_count"})
    )
    print("Creative Commons status summary (distinct reports):")
    display(status_summary)

SPARQL query for Question 3:

PREFIX wd: <https://climatekg.tibwiki.io/entity/>
PREFIX wdt: <https://climatekg.tibwiki.io/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>

SELECT ?report ?reportLabel ?doi ?license ?licenseLabel ?licenseLink ?ccStatus
WHERE {
  ?report wdt:P1 wd:Q4 ; rdfs:label ?reportLabel .
  FILTER(LANG(?reportLabel) = "en")

  OPTIONAL {
    ?report wdt:P10 ?doiValue .
    BIND(STR(?doiValue) AS ?doi)
  }

  OPTIONAL {
    ?report wdt:P11 ?license .
    OPTIONAL { ?license rdfs:label ?licenseLabel . FILTER(LANG(?licenseLabel) = "en") }
    BIND(
      IF(
        isIRI(?license),
        STR(?license),
        IF(REGEX(STR(?license), "^https?://"), STR(?license), "")
      ) AS ?licenseLink
    )
  }

  BIND(COALESCE(?licenseLabel, STR(?license), "No license value") AS ?licenseText)
  BIND(
    IF(
      REGEX(LCASE(?licenseText), "creative commons|cc[- ]?by|cc[- ]?0|cc by"),
      "Creative Commons",
      "Not clearly Creative Commons"
    ) AS ?ccStatus
  )
}
ORDER BY ?reportLabel

Report metadata rows returned: 7

	report	doi (P10)	license_value (P11)	creative_commons_status
0	Climate Change 2023: Synthesis Report. Contrib...	10.59327/IPCC/AR6-9789291691647	No license specified	Not clearly Creative Commons
1	Special Report: Climate Change and Land	10.1017/9781009157988	CC-BY-NC-ND 4.0	Creative Commons
2	Special Report: Global Warming of 1.5°C	10.1017/9781009157940	CC-BY-NC-ND 4.0	Creative Commons
3	Special Report: The Ocean and Cryosphere in a ...	10.1017/9781009157964	CC-BY-NC-ND 4.0	Creative Commons
4	Working Group I: Climate Change 2021 – The Phy...	10.1017/9781009157896	CC-BY-NC-ND 4.0	Creative Commons
5	Working Group II: Climate Change 2022 – Impact...	10.1017/9781009325844	CC-BY-NC-ND 4.0	Creative Commons
6	Working Group III: Climate Change 2022 – Mitig...	10.1017/9781009157926	CC-BY-NC-ND 4.0	Creative Commons

Creative Commons status summary (distinct reports):

	creative_commons_status	report_count
0	Creative Commons	6
1	Not clearly Creative Commons	1

Interpretation

The ER model recorded in The Rock defines the intended corpus structure: Q2 Work, Q3 Report Series, Q4 Report, Q5 Text Division, and Q6 Chapter. In that schema, P3 is the parent / part-of relationship and P4 is the child / parts relationship.

The live graph is now populated across the expected report hierarchy: class counts show items at all five levels, from Q2 through Q6. This means the graph is no longer a chapter-only snapshot and now contains a working structure that can be compared directly against the ER model.

The current data therefore supports a more nuanced conclusion: the graph reflects a genuinely populated report hierarchy, while the notebook continues to use the canonical ER model as the baseline for checking which entities and relationship patterns are present and how they fit together.