D4 sparql, run 1: the query session

30 queries0 failed8 rounds

The opening prompt

## The data

You can't see the data, but you can query it. It is in an RDF store, described below. Write SPARQL 1.1 SELECT or ASK queries.

To run queries, reply with one or more fenced blocks (```sparql), and nothing else is needed:
each is run and its results sent back to you. You have up to 8 rounds of queries.
When you have what you need, reply with the final answers and no queries.

Prefixes:
```
PREFIX skos: <http://www.w3.org/2004/02/skos/core#>
PREFIX rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX xsd: <http://www.w3.org/2001/XMLSchema#>
PREFIX res: <https://example.org/research/>
```

Classes and the properties their resources use:

- `res:Author`: `rdf:type`, `rdfs:label`, `res:name`, `res:orcid`
- `res:Authorship`: `rdf:type`, `rdfs:label`, `res:affiliationSeq`, `res:author`, `res:authorPosition`, `res:institution`, `res:work`
- `res:Citation`: `rdf:type`, `rdfs:label`, `res:citedWork`, `res:citingWork`
- `res:Institution`: `rdf:type`, `rdfs:label`, `res:country`, `res:institutionType`, `res:name`, `res:parent`, `res:ror`
- `res:Source`: `rdf:type`, `rdfs:label`, `res:issn`, `res:name`, `res:sourceType`, `res:tier`
- `res:Work`: `rdf:type`, `rdfs:label`, `res:doi`, `res:recordSource`, `res:retracted`, `res:source`, `res:title`, `res:versionOf`, `res:workType`, `res:year`

## Questions

Answer each question below from the data above. Start each answer on a new line with its
number in bold, like **Q1.**, give the direct answer first, then at most two sentences of
reasoning that cite the records (IDs) you relied on.

Then end with one JSON block (```json) holding the structured answer to each question listed
here, with exactly these fields, shaped like {"Q1": {"field": value}, ...}. Name works, authors, institutions and sources by their record ID: the work_id, author_id, institution_id or source_id in the CSV files, or the part of the IRI after res: in the RDF (W01, A07, I02, S03; not their titles or names).

- Q1: count (a number)
- Q2: works (a list of record IDs)
- Q3: same ("yes", "no" or "depends")
- Q4: count (a number)
- Q5: same ("yes", "no" or "depends")
- Q6: author (a record ID)
- Q7: count (a number)
- Q8: parent (a record ID)
- Q9: count (a number)
- Q10: count (a number)
- Q11: count (a number)
- Q12: full (a number), fractional (a number)
- Q13: full (a record ID), fractional (a record ID)
- Q14: full (a number), fractional (a number)
- Q15: count (a number)
- Q16: count (a number)
- Q17: works (a list of record IDs)
- Q18: count (a number)
- Q19: count (a number)
- Q20: works (a list of record IDs)
- Q21: count (a number)
- Q22: more_in_total (a record ID), more_in_window (a record ID)
- Q23: total (a number), in_window (a number)
- Q24: count (a number)
- Q25: count (a number)
- Q26: counts ("yes", "no" or "depends")
- Q27: institution (a record ID), citing_works (a number)
- Q28: count (a number)
- Q29: author (a number), institution (a number), country (a number)
- Q30: count (a number)
- Q31: works (a list of record IDs)
- Q32: count (a number)
- Q33: work (a record ID)
- Q34: count (a number)
- Q35: count (a number)
- Q36: count (a number)
- Q37: institution (a record ID)
- Q38: institutions (a list of record IDs)
- Q39: count (a number)
- Q40: source (a record ID)
- Q41: higher ("yes", "no" or "depends")
- Q42: count (a number)
- Q43: research ("yes", "no" or "depends")
- Q44: institutions (a list of record IDs)
- Q45: count (a number)
- Q46: parent (a record ID)

Q1. How many distinct people do the author records named "Mara Ellison", "M. Ellison" and "Ellison, Mara J." stand for?
Q2. List every work, of any type, that Mara Ellison (A01) is an author of.
Q3. Is the Jonas Brandt who wrote W37 the same person as the Jonas Brandt who wrote W38?
Q4. How many research works has the Jonas Brandt of Albury Metropolitan University (A05) authored?
Q5. Is the M. Ellison who wrote W08 the same person as the Mara Ellison who wrote W01?
Q6. Which author has the most research works credited to the University of Albury, its units included?
Q7. How many research works has Mara Ellison authored?
Q8. What is the ultimate parent of the Tessel Laboratory for Ocean Sensing (I04)?
Q9. How many research works is the University of Albury (I02) credited with, its units included?
Q10. How many research works is the Albury University System (I01) credited with, all its units included?
Q11. How many research works is Kesting University (I07) credited with, its units included?
Q12. How many research works did Kesting University (I07, units included) publish in 2024, under full counting and under fractional counting (each work split equally among its authors)?
Q13. In 2024, which had more research works, Kesting University (I07) or Rostval Technical University (I09): under full counting, and under fractional counting?
Q14. How many research works did GB institutions publish in 2024, under full counting and under fractional counting (each work split equally among its authors, each author's share going to their institution's country)?
Q15. How many research works appeared in Ocean Sensing Letters (S02) in 2024?
Q16. How many research works appeared in the Journal of Marine Autonomy (S01)?
Q17. Which of Mara Ellison's works are not research output because of their document type?
Q18. How many distinct research works has Priya Ramanathan (A07) authored?
Q19. How many distinct works cite "Drift-aware mapping with low-cost sonar", in either of its versions?
Q20. Which works in the data are preprints of another work that is also in the data?
Q21. How many research works is Oskel Polytechnic (I14) credited with?
Q22. Which has more citations, W30 or W31 (counting both versions of each): in total, and within its publication year and the two years after?
Q23. How many citations has W30 received in total, and how many within its publication year and the two years after?
Q24. How many research works has Lena Vossberg (A09) authored?
Q25. What is the total of the citation counts of Lena Vossberg's research works?
Q26. Does W23 count towards Kesting University's research output?
Q27. Which other institution's works cite Kesting University's research works the most, each citing work counted once per institution, and how many of its works do?
Q28. How many distinct works from Rostval Technical University (I09) cite Kesting University's research works?
Q29. Of the works citing "Drift-aware mapping with low-cost sonar" (either version), how many are self-citations at the level of authors, of the University of Albury (units included), and of countries?
Q30. Of the works citing "Drift-aware mapping with low-cost sonar" (either version), how many are self-citations at the level of the Albury University System?
Q31. Which works cite at least one of the works that cite W01?
Q32. How many distinct works are within two citation hops of W01 (citing it, or citing a work that cites it)?
Q33. Which of Kesting University's research works has the most citations?
Q34. How many research works was Kesting University (units included) credited with in 2025?
Q35. How many research works is the Kesting Institute of Hydrodynamics (I08) credited with?
Q36. How many research works appeared in the Proceedings of the Hydrodynamics Forum (S06)?
Q37. Which institution is W70 credited to?
Q38. Which institutions is W71 credited to, at every level?
Q39. How many of the University of Albury's research works (units included) appeared in a source of the highest tier?
Q40. Which source is in the highest tier?
Q41. Is Coastal Engineering Review (S03) in a higher tier than Ocean Sensing Letters (S02)?
Q42. How many research works appeared in Global Marine Science Reports (S04)?
Q43. Is W07 research output?
Q44. Which institutions are part of the Albury University System, at any level below it?
Q45. How many research works is the Halloran Institute for Coastal Studies (I06) credited with?
Q46. What is the ultimate parent of the Halloran Institute for Coastal Studies (I06)?
Q47. Why do Kesting University and Rostval Technical University swap places in 2024 between full and fractional counting?
Q48. Why is W70 not one of the University of Albury's research works, though its author lists the Tessel Laboratory?

The model

I'll start by exploring the data.

```sparql
PREFIX res: <https://example.org/research/>
SELECT ?s ?p ?o WHERE { ?s ?p ?o . ?s a ?c . FILTER(?c IN (res:Author, res:Institution, res:Source)) } ORDER BY ?s ?p
```

```sparql
PREFIX res: <https://example.org/research/>
SELECT ?s ?p ?o WHERE { ?s ?p ?o . ?s a res:Work } ORDER BY ?s ?p
```

Query results

Query 1:

| s | p | o |
|---|---|---|
| res:A01 | rdf:type | res:Author |
| res:A01 | rdfs:label | Mara Ellison |
| res:A01 | res:name | Mara Ellison |
| res:A01 | res:orcid | 0000-0002-9841-6229 |
| res:A02 | rdf:type | res:Author |
| res:A02 | rdfs:label | M. Ellison |
| res:A02 | res:name | M. Ellison |
| res:A02 | res:orcid | 0000-0002-9841-6229 |
| res:A03 | rdf:type | res:Author |
| res:A03 | rdfs:label | Ellison, Mara J. |
| res:A03 | res:name | Ellison, Mara J. |
| res:A03 | res:orcid | 0000-0002-9841-6229 |
| res:A04 | rdf:type | res:Author |
| res:A04 | rdfs:label | M. Ellison |
| res:A04 | res:name | M. Ellison |
| res:A04 | res:orcid | 0000-0004-8662-8360 |
| res:A05 | rdf:type | res:Author |
| res:A05 | rdfs:label | Jonas Brandt |
| res:A05 | res:name | Jonas Brandt |
| res:A05 | res:orcid | 0000-0001-6105-5008 |
| res:A06 | rdf:type | res:Author |
| res:A06 | rdfs:label | Jonas Brandt |
| res:A06 | res:name | Jonas Brandt |
| res:A06 | res:orcid | 0000-0007-5475-1779 |
| res:A07 | rdf:type | res:Author |
| res:A07 | rdfs:label | Priya Ramanathan |
| res:A07 | res:name | Priya Ramanathan |
| res:A07 | res:orcid | 0000-0009-2298-3695 |
| res:A08 | rdf:type | res:Author |
| res:A08 | rdfs:label | Tomasz Wierzba |
| res:A08 | res:name | Tomasz Wierzba |
| res:A08 | res:orcid | 0000-0007-9318-6032 |
| res:A09 | rdf:type | res:Author |
| res:A09 | rdfs:label | Lena Vossberg |
| res:A09 | res:name | Lena Vossberg |
| res:A09 | res:orcid | 0000-0000-8073-7028 |
| res:A10 | rdf:type | res:Author |
| res:A10 | rdfs:label | Dirk Hallmann |
| res:A10 | res:name | Dirk Hallmann |
| res:A10 | res:orcid | 0000-0003-8222-6468 |
| res:A101 | rdf:type | res:Author |
| res:A101 | rdfs:label | M. Ellison |
| res:A101 | res:name | M. Ellison |
| res:A101 | res:orcid | 0000-0002-9841-6229 |
| res:A102 | rdf:type | res:Author |
| res:A102 | rdfs:label | M. Ellison |
| res:A102 | res:name | M. Ellison |
| res:A102 | res:orcid | 0000-0008-4738-8328 |
| res:A103 | rdf:type | res:Author |
| res:A103 | rdfs:label | L. Vossberg |
| res:A103 | res:name | L. Vossberg |
| res:A103 | res:orcid | 0000-0000-8073-7028 |
| res:A104 | rdf:type | res:Author |
| res:A104 | rdfs:label | J. Brandt |
| res:A104 | res:name | J. Brandt |
| res:A104 | res:orcid | 0000-0001-6105-5008 |
| res:A105 | rdf:type | res:Author |
| res:A105 | rdfs:label | Jonas Brandt |
| res:A105 | res:name | Jonas Brandt |
| res:A105 | res:orcid | 0000-0004-9046-7961 |
(874 more rows not shown)

Query 2:

| s | p | o |
|---|---|---|
| res:W01 | rdf:type | res:Work |
| res:W01 | rdfs:label | Adaptive path planning for underwater gliders |
| res:W01 | res:doi | 10.55555/s01.2021.1465 |
| res:W01 | res:recordSource | res:origin-FEED |
| res:W01 | res:retracted | false |
| res:W01 | res:source | res:S01 |
| res:W01 | res:title | Adaptive path planning for underwater gliders |
| res:W01 | res:workType | res:wtype-ART |
| res:W01 | res:year | 2021 |
| res:W02 | rdf:type | res:Work |
| res:W02 | rdfs:label | Drift-aware mapping with low-cost sonar |
| res:W02 | res:doi | 10.55555/s05.2022.2911 |
| res:W02 | res:recordSource | res:origin-FEED |
| res:W02 | res:retracted | false |
| res:W02 | res:source | res:S05 |
| res:W02 | res:title | Drift-aware mapping with low-cost sonar |
| res:W02 | res:versionOf | res:W03 |
| res:W02 | res:workType | res:wtype-PPR |
| res:W02 | res:year | 2022 |
| res:W03 | rdf:type | res:Work |
| res:W03 | rdfs:label | Drift-aware mapping with low-cost sonar |
| res:W03 | res:doi | 10.55555/s02.2023.9437 |
| res:W03 | res:recordSource | res:origin-FEED |
| res:W03 | res:retracted | false |
| res:W03 | res:source | res:S02 |
| res:W03 | res:title | Drift-aware mapping with low-cost sonar |
| res:W03 | res:workType | res:wtype-ART |
| res:W03 | res:year | 2023 |
| res:W04 | rdf:type | res:Work |
| res:W04 | rdfs:label | Editorial: a new decade of marine autonomy |
| res:W04 | res:doi | 10.55555/s01.2023.1032 |
| res:W04 | res:recordSource | res:origin-FEED |
| res:W04 | res:retracted | false |
| res:W04 | res:source | res:S01 |
| res:W04 | res:title | Editorial: a new decade of marine autonomy |
| res:W04 | res:workType | res:wtype-EDT |
| res:W04 | res:year | 2023 |
| res:W05 | rdf:type | res:Work |
| res:W05 | rdfs:label | Erratum: Drift-aware mapping with low-cost sonar |
| res:W05 | res:doi | 10.55555/s02.2024.7136 |
| res:W05 | res:recordSource | res:origin-FEED |
| res:W05 | res:retracted | false |
| res:W05 | res:source | res:S02 |
| res:W05 | res:title | Erratum: Drift-aware mapping with low-cost sonar |
| res:W05 | res:workType | res:wtype-ERR |
| res:W05 | res:year | 2024 |
| res:W06 | rdf:type | res:Work |
| res:W06 | rdfs:label | Shoreline change detection from glider transects |
| res:W06 | res:doi | 10.55555/s03.2024.2042 |
| res:W06 | res:recordSource | res:origin-FEED |
| res:W06 | res:retracted | false |
| res:W06 | res:source | res:S03 |
| res:W06 | res:title | Shoreline change detection from glider transects |
| res:W06 | res:workType | res:wtype-ART |
| res:W06 | res:year | 2024 |
| res:W07 | rdf:type | res:Work |
| res:W07 | rdfs:label | Low-cost sonar arrays for coastal monitoring |
| res:W07 | res:doi | 10.55555/s04.2020.7029 |
| res:W07 | res:recordSource | res:origin-FEED |
| res:W07 | res:retracted | false |
(7613 more rows not shown)

Run more queries, or give the final answers.

The model

<invoke name="sparql">
</invoke>
```sparql
PREFIX res: <https://example.org/research/>
SELECT ?s ?p ?o WHERE { ?s ?p ?o . { ?s a res:Institution } UNION { ?s a res:Source } } ORDER BY ?s ?p
```

```sparql
PREFIX res: <https://example.org/research/>
SELECT ?s ?p ?o WHERE { ?s ?p ?o . FILTER NOT EXISTS { ?s a ?c . FILTER(?c IN (res:Author,res:Institution,res:Source,res:Work,res:Authorship,res:Citation)) } } ORDER BY ?s ?p
```

Query results

Query 1:

| s | p | o |
|---|---|---|
| res:I01 | rdf:type | res:Institution |
| res:I01 | rdfs:label | Albury University System |
| res:I01 | res:country | GB |
| res:I01 | res:institutionType | res:itype-SYS |
| res:I01 | res:name | Albury University System |
| res:I01 | res:ror | 0hygr4985 |
| res:I02 | rdf:type | res:Institution |
| res:I02 | rdfs:label | University of Albury |
| res:I02 | res:country | GB |
| res:I02 | res:institutionType | res:itype-UNI |
| res:I02 | res:name | University of Albury |
| res:I02 | res:parent | res:I01 |
| res:I02 | res:ror | 06safhw22 |
| res:I03 | rdf:type | res:Institution |
| res:I03 | rdfs:label | Albury Centre for Marine Robotics |
| res:I03 | res:country | GB |
| res:I03 | res:institutionType | res:itype-LAB |
| res:I03 | res:name | Albury Centre for Marine Robotics |
| res:I03 | res:parent | res:I02 |
| res:I03 | res:ror | 06a9yq342 |
| res:I04 | rdf:type | res:Institution |
| res:I04 | rdfs:label | Tessel Laboratory for Ocean Sensing |
| res:I04 | res:country | GB |
| res:I04 | res:institutionType | res:itype-LAB |
| res:I04 | res:name | Tessel Laboratory for Ocean Sensing |
| res:I04 | res:parent | res:I03 |
| res:I04 | res:ror | 0002ezf81 |
| res:I05 | rdf:type | res:Institution |
| res:I05 | rdfs:label | Albury Metropolitan University |
| res:I05 | res:country | GB |
| res:I05 | res:institutionType | res:itype-UNI |
| res:I05 | res:name | Albury Metropolitan University |
| res:I05 | res:parent | res:I01 |
| res:I05 | res:ror | 0ww7kxb57 |
| res:I06 | rdf:type | res:Institution |
| res:I06 | rdfs:label | Halloran Institute for Coastal Studies |
| res:I06 | res:country | GB |
| res:I06 | res:institutionType | res:itype-AFF |
| res:I06 | res:name | Halloran Institute for Coastal Studies |
| res:I06 | res:parent | res:I02 |
| res:I06 | res:ror | 0175f3924 |
| res:I07 | rdf:type | res:Institution |
| res:I07 | rdfs:label | Kesting University |
| res:I07 | res:country | DE |
| res:I07 | res:institutionType | res:itype-UNI |
| res:I07 | res:name | Kesting University |
| res:I07 | res:ror | 0593t4875 |
| res:I08 | rdf:type | res:Institution |
| res:I08 | rdfs:label | Kesting Institute of Hydrodynamics |
| res:I08 | res:country | DE |
| res:I08 | res:institutionType | res:itype-LAB |
| res:I08 | res:name | Kesting Institute of Hydrodynamics |
| res:I08 | res:parent | res:I07 |
| res:I08 | res:ror | 0brjdg570 |
| res:I09 | rdf:type | res:Institution |
| res:I09 | rdfs:label | Rostval Technical University |
| res:I09 | res:country | NL |
| res:I09 | res:institutionType | res:itype-UNI |
| res:I09 | res:name | Rostval Technical University |
| res:I09 | res:ror | 0k8rh7879 |
(217 more rows not shown)

Query 2:

(no rows)

Run more queries, or give the final answers.

The model

<invoke name="sparql">
</invoke>
```sparql
PREFIX res: <https://example.org/research/>
SELECT ?s (GROUP_CONCAT(CONCAT(STRAFTER(STR(?p),"research/"),"=",REPLACE(STR(?o),"https://example.org/research/",""));separator="; ") AS ?d) WHERE { ?s ?p ?o . { ?s a res:Institution } UNION { ?s a res:Source } FILTER(?p NOT IN (rdf:type, rdfs:label, res:ror, res:issn)) } GROUP BY ?s ORDER BY ?s
```

```sparql
PREFIX res: <https://example.org/research/>
SELECT ?s ?p ?o WHERE { ?s ?p ?o . FILTER(STRSTARTS(STR(?s),"https://example.org/research/")) FILTER(REGEX(STR(?s),"(wtype|itype|origin|tier|stype)")) } ORDER BY ?s ?p
```

Query results

Query 1:

| s | d |
|---|---|
| res:I01 | name=Albury University System; institutionType=itype-SYS; country=GB |
| res:I02 | country=GB; name=University of Albury; institutionType=itype-UNI; parent=I01 |
| res:I03 | country=GB; institutionType=itype-LAB; name=Albury Centre for Marine Robotics; parent=I02 |
| res:I04 | institutionType=itype-LAB; country=GB; name=Tessel Laboratory for Ocean Sensing; parent=I03 |
| res:I05 | name=Albury Metropolitan University; parent=I01; country=GB; institutionType=itype-UNI |
| res:I06 | country=GB; institutionType=itype-AFF; parent=I02; name=Halloran Institute for Coastal Studies |
| res:I07 | institutionType=itype-UNI; name=Kesting University; country=DE |
| res:I08 | parent=I07; country=DE; institutionType=itype-LAB; name=Kesting Institute of Hydrodynamics |
| res:I09 | institutionType=itype-UNI; country=NL; name=Rostval Technical University |
| res:I10 | institutionType=itype-CO; name=Marrow Instruments BV; country=NL |
| res:I11 | institutionType=itype-GOV; name=Brevin Ocean Agency; country=FR |
| res:I12 | country=FR; institutionType=itype-UNI; name=Université de Lorvain |
| res:I13 | institutionType=itype-UNI; name=Dunmore College; country=GB |
| res:I14 | name=Oskel Polytechnic; institutionType=itype-UNI; country=NL |
| res:I15 | country=US; institutionType=itype-UNI; name=Carrow State University |
| res:I16 | country=JP; institutionType=itype-UNI; name=Hoshimine Institute of Technology |
| res:I17 | institutionType=itype-UNI; name=Université de Mallois; country=CA |
| res:I18 | country=ES; institutionType=itype-UNI; name=Universidad de Ventolera |
| res:I19 | name=Albury Laboratory for Acoustic Imaging; parent=I02; country=GB; institutionType=itype-LAB |
| res:I20 | parent=I05; institutionType=itype-LAB; name=Albury Metropolitan Centre for Port Studies; country=GB |
| res:I21 | institutionType=itype-AFF; parent=I05; name=Wexcombe Institute for Estuary Research; country=GB |
| res:I22 | institutionType=itype-AFF; name=Sandhaven Institute for Wave Research; parent=I07; country=DE |
| res:I23 | institutionType=itype-LAB; country=NL; parent=I09; name=Rostval Laboratory for Offshore Structures |
| res:I24 | country=US; institutionType=itype-UNI; name=Pellmore University |
| res:I25 | institutionType=itype-UNI; country=IT; name=Università di Calvessa |
| res:I26 | name=Tarnowa University of Technology; institutionType=itype-UNI; country=PL |
| res:I27 | institutionType=itype-UNI; country=AU; name=Kirrabay University |
| res:I28 | institutionType=itype-UNI; name=Nordvik University; country=NO |
| res:I29 | country=KR; name=Hanseo Ocean Institute; institutionType=itype-GOV |
| res:I30 | name=Universidade de Arvela; country=PT; institutionType=itype-UNI |
| res:I31 | name=Corrimal Marine Systems Inc; country=US; institutionType=itype-CO |
| res:S01 | tier=tier-K3; name=Journal of Marine Autonomy; sourceType=stype-JOU |
| res:S02 | name=Ocean Sensing Letters; sourceType=stype-JOU; tier=tier-K2 |
| res:S03 | tier=tier-K1; sourceType=stype-JOU; name=Coastal Engineering Review |
| res:S04 | tier=tier-K0; sourceType=stype-JOU; name=Global Marine Science Reports |
| res:S05 | sourceType=stype-REP; name=OceanArXiv |
| res:S06 | tier=tier-K2; name=Proceedings of the Hydrodynamics Forum; sourceType=stype-JOU |
| res:S07 | sourceType=stype-JOU; name=Journal of Estuarine Dynamics; tier=tier-K2 |
| res:S08 | tier=tier-K1; sourceType=stype-JOU; name=Hydrology Notes |
| res:S09 | sourceType=stype-JOU; name=Journal of Coastal Hydraulics; tier=tier-K2 |
| res:S10 | tier=tier-K1; sourceType=stype-JOU; name=Marine Technology Bulletin |
| res:S11 | name=Annals of Ocean Observation; sourceType=stype-JOU; tier=tier-K2 |
| res:S12 | name=Shelf Sea Letters; tier=tier-K1; sourceType=stype-JOU |
| res:S13 | tier=tier-K0; sourceType=stype-JOU; name=International Journal of Ocean Frontiers |
| res:S14 | sourceType=stype-REP; name=CoastRxiv |

Query 2:

(no rows)

Run more queries, or give the final answers.

The model

<parameter name="sparql">
</parameter>
```sparql
PREFIX res: <https://example.org/research/>
SELECT ?s ?p ?o WHERE { ?s ?p ?o . FILTER(?p IN (skos:prefLabel, skos:definition, skos:note, skos:broader, skos:notation, rdfs:comment) || ?s = res:wtype-ART || ?s = res:tier-K3 || ?s = res:origin-FEED) } LIMIT 100
```

```sparql
PREFIX res: <https://example.org/research/>
SELECT ?w ?t ?y ?wt ?src ?rs ?ret ?v WHERE { ?w a res:Work ; res:title ?t ; res:year ?y ; res:workType ?wt ; res:recordSource ?rs ; res:retracted ?ret . OPTIONAL{?w res:source ?src} OPTIONAL{?w res:versionOf ?v} } ORDER BY ?w
```

Query results

Query 1:

(no rows)

Query 2:

| w | t | y | wt | src | rs | ret | v |
|---|---|---|---|---|---|---|---|
| res:W01 | Adaptive path planning for underwater gliders | 2021 | res:wtype-ART | res:S01 | res:origin-FEED | false |  |
| res:W02 | Drift-aware mapping with low-cost sonar | 2022 | res:wtype-PPR | res:S05 | res:origin-FEED | false | res:W03 |
| res:W03 | Drift-aware mapping with low-cost sonar | 2023 | res:wtype-ART | res:S02 | res:origin-FEED | false |  |
| res:W04 | Editorial: a new decade of marine autonomy | 2023 | res:wtype-EDT | res:S01 | res:origin-FEED | false |  |
| res:W05 | Erratum: Drift-aware mapping with low-cost sonar | 2024 | res:wtype-ERR | res:S02 | res:origin-FEED | false |  |
| res:W06 | Shoreline change detection from glider transects | 2024 | res:wtype-ART | res:S03 | res:origin-FEED | false |  |
| res:W07 | Low-cost sonar arrays for coastal monitoring | 2020 | res:wtype-ART | res:S04 | res:origin-FEED | false |  |
| res:W08 | Turbulent wake modelling behind tidal turbines | 2025 | res:wtype-ART | res:S01 | res:origin-FEED | false |  |
| res:W09 | Issue information | 2023 | res:wtype-PTX | res:S01 | res:origin-FEED | false |  |
| res:W10 | Front matter | 2024 | res:wtype-PTX | res:S02 | res:origin-FEED | false |  |
| res:W1000 | Low-cost methods for internal waves | 2024 | res:wtype-ART | res:S01 | res:origin-FEED | false |  |
| res:W1001 | Machine learning for harbour seiches in mixed-energy coasts | 2024 | res:wtype-ART | res:S09 | res:origin-FEED | false |  |
| res:W1002 | A framework for dune erosion | 2021 | res:wtype-SUP | res:S06 | res:origin-FEED | false |  |
| res:W1003 | Field measurements of sensor calibration in the North Sea | 2024 | res:wtype-ART | res:S06 | res:origin-FEED | false |  |
| res:W1004 | Revisiting acoustic positioning | 2024 | res:wtype-ART | res:S02 | res:origin-FEED | false |  |
| res:W1005 | Remote sensing of buoy telemetry in fjords | 2025 | res:wtype-ART | res:S02 | res:origin-FEED | false |  |
| res:W1006 | Seasonal variability in acoustic positioning in a laboratory flume | 2020 | res:wtype-REV | res:S13 | res:origin-FEED | false |  |
| res:W1007 | A model of storm surge in sandy coasts | 2023 | res:wtype-ART | res:S01 | res:origin-FEED | false |  |
| res:W1008 | Machine learning for beach profiles in sandy coasts | 2025 | res:wtype-ART | res:S11 | res:origin-FEED | false |  |
| res:W1009 | Revisiting sediment flux in the open shelf: a review | 2022 | res:wtype-REV | res:S12 | res:origin-FEED | false |  |
| res:W101 | Long-term trends in estuarine salinity | 2019 | res:wtype-ART | res:S08 | res:origin-FEED | false |  |
| res:W1010 | Revisiting vortex shedding in mixed-energy coasts | 2020 | res:wtype-ART | res:S02 | res:origin-FEED | false |  |
| res:W1011 | Scaling laws for fleet coordination in harbour basins | 2021 | res:wtype-REV | res:S04 | res:origin-FEED | false |  |
| res:W1012 | Seasonal variability in marsh accretion in the Wexcombe marshes | 2020 | res:wtype-ART | res:S08 | res:origin-FEED | false |  |
| res:W1013 | Revisiting battery endurance in sandy coasts | 2025 | res:wtype-ART | res:S04 | res:origin-FEED | false |  |
| res:W1014 | A model of sensor calibration in the North Sea | 2023 | res:wtype-ART | res:S01 | res:origin-FEED | false |  |
| res:W1015 | Revisiting tidal asymmetry in mixed-energy coasts | 2023 | res:wtype-ART | res:S12 | res:origin-FEED | false |  |
| res:W1016 | Scaling laws for bed shear stress in a laboratory flume | 2025 | res:wtype-ART | res:S06 | res:origin-FEED | false |  |
| res:W1017 | A model of tidal asymmetry in tidal inlets | 2025 | res:wtype-ART | res:S07 | res:origin-FEED | false |  |
| res:W1018 | Remote sensing of estuarine salinity in the Brevin shelf | 2025 | res:wtype-ART | res:S08 | res:origin-FEED | false |  |
| res:W1019 | Seasonal variability in coastal upwelling in mixed-energy coasts | 2020 | res:wtype-ART | res:S03 | res:origin-FEED | false |  |
| res:W102 | Long-term trends in dune erosion | 2023 | res:wtype-ART | res:S07 | res:origin-FEED | false |  |
| res:W1020 | Machine learning for vortex shedding in mixed-energy coasts | 2020 | res:wtype-ART | res:S13 | res:origin-FEED | false |  |
| res:W1021 | Long-term trends in wave boundary layers | 2021 | res:wtype-ART | res:S02 | res:origin-FEED | false |  |
| res:W1022 | Uncertainty in storm surge estimates in the Wexcombe marshes | 2023 | res:wtype-ART | res:S09 | res:origin-FEED | false |  |
| res:W1023 | A model of beach profiles in mixed-energy coasts | 2024 | res:wtype-ART | res:S09 | res:origin-FEED | false |  |
| res:W1024 | Long-term trends in dune erosion in sandy coasts | 2020 | res:wtype-ART | res:S12 | res:origin-FEED | false |  |
| res:W1025 | Long-term trends in stratified flows | 2020 | res:wtype-ART | res:S02 | res:origin-FEED | true |  |
| res:W1026 | A model of dune erosion in a macrotidal bay | 2019 | res:wtype-ART | res:S09 | res:origin-FEED | false |  |
| res:W1027 | Low-cost methods for bed shear stress in fjords: a review | 2024 | res:wtype-REV | res:S10 | res:origin-FEED | false |  |
| res:W1028 | A model of wave runup in mixed-energy coasts | 2019 | res:wtype-ART | res:S03 | res:origin-FEED | false |  |
| res:W1029 | Seasonal variability in coastal upwelling in the open shelf | 2022 | res:wtype-ART | res:S09 | res:origin-FEED | false |  |
| res:W103 | A model of harbour seiches | 2020 | res:wtype-ART | res:S07 | res:origin-FEED | false |  |
| res:W1030 | Low-cost methods for storm surge in the open shelf | 2021 | res:wtype-ART | res:S12 | res:origin-FEED | false |  |
| res:W1031 | Remote sensing of internal waves in the open shelf | 2025 | res:wtype-ART | res:S01 | res:origin-FEED | false |  |
| res:W1032 | Low-cost methods for coastal upwelling | 2019 | res:wtype-ART | res:S02 | res:origin-FEED | false |  |
| res:W1033 | Machine learning for tidal asymmetry | 2025 | res:wtype-ART | res:S08 | res:origin-FEED | false |  |
| res:W1034 | Foreword: tidal mixing | 2025 | res:wtype-EDT | res:S06 | res:origin-FEED | false |  |
| res:W1035 | Uncertainty in ocean optics estimates in the Brevin shelf | 2021 | res:wtype-ART | res:S03 | res:origin-FEED | false |  |
| res:W1036 | Uncertainty in bed shear stress estimates in the Albury estuary | 2024 | res:wtype-ART | res:S06 | res:origin-FEED | false |  |
| res:W1037 | Low-cost methods for harbour seiches in the Wexcombe marshes | 2022 | res:wtype-ART | res:S02 | res:origin-FEED | true |  |
| res:W1038 | Low-cost methods for marsh accretion | 2020 | res:wtype-ART | res:S02 | res:origin-FEED | false |  |
| res:W1039 | Revisiting vortex shedding in sandy coasts | 2023 | res:wtype-ART | res:S11 | res:origin-FEED | false |  |
| res:W104 | Remote sensing of wave runup | 2019 | res:wtype-ART | res:S07 | res:origin-FEED | false |  |
| res:W1040 | Field measurements of storm surge | 2024 | res:wtype-ART | res:S08 | res:origin-FEED | false |  |
| res:W1041 | Editorial: survey vessel autonomy | 2025 | res:wtype-EDT | res:S03 | res:origin-FEED | false |  |
| res:W1042 | Revisiting seabed classification in a semi-enclosed sea | 2025 | res:wtype-ART | res:S01 | res:origin-FEED | false |  |
| res:W1043 | Editorial: machine learning for sediment flux | 2023 | res:wtype-EDT | res:S08 | res:origin-FEED | false |  |
| res:W1044 | Machine learning for acoustic positioning in harbour basins | 2021 | res:wtype-ART | res:S02 | res:origin-FEED | false |  |
| res:W1046 | Low-cost methods for vortex shedding in a laboratory flume | 2024 | res:wtype-ART | res:S01 | res:origin-FEED | false |  |
(790 more rows not shown)

Run more queries, or give the final answers.

The model

<invoke name="sparql">
</invoke>
```sparql
PREFIX res: <https://example.org/research/>
SELECT ?orc ?a ?w ?wt ?y ?ret ?v ?i ?pos WHERE { ?au a res:Authorship ; res:author ?a ; res:work ?w . OPTIONAL{?au res:institution ?i} OPTIONAL{?au res:authorPosition ?pos} ?a res:orcid ?orc . ?w res:workType ?wt ; res:year ?y ; res:retracted ?ret . OPTIONAL{?w res:versionOf ?v} FILTER(?orc IN ("0000-0002-9841-6229","0000-0000-8073-7028","0000-0009-2298-3695","0000-0001-6105-5008")) } ORDER BY ?orc ?w
```


<invoke name="sparql">
</invoke>
```sparql
PREFIX res: <https://example.org/research/>
SELECT ?a ?orc ?w ?wt ?y ?i WHERE { ?au a res:Authorship ; res:author ?a ; res:work ?w . OPTIONAL{?au res:institution ?i} ?a res:name ?n ; res:orcid ?orc . ?w res:workType ?wt ; res:year ?y . FILTER(?n IN ("Jonas Brandt","J. Brandt") ) } ORDER BY ?orc ?w
```

Query results

Query 1:

| orc | a | w | wt | y | ret | v | i | pos |
|---|---|---|---|---|---|---|---|---|
| 0000-0000-8073-7028 | res:A09 | res:W1025 | res:wtype-ART | 2020 | true |  | res:I07 | 1 |
| 0000-0000-8073-7028 | res:A09 | res:W20 | res:wtype-ART | 2024 | false |  | res:I07 | 1 |
| 0000-0000-8073-7028 | res:A09 | res:W203 | res:wtype-ART | 2024 | false |  | res:I07 | 2 |
| 0000-0000-8073-7028 | res:A09 | res:W21 | res:wtype-ART | 2024 | false |  | res:I07 | 2 |
| 0000-0000-8073-7028 | res:A09 | res:W22 | res:wtype-REV | 2024 | false |  | res:I07 | 1 |
| 0000-0000-8073-7028 | res:A09 | res:W23 | res:wtype-ART | 2023 | true |  | res:I07 | 1 |
| 0000-0000-8073-7028 | res:A09 | res:W232 | res:wtype-ART | 2019 | false |  | res:I07 | 1 |
| 0000-0000-8073-7028 | res:A09 | res:W268 | res:wtype-ART | 2025 | false |  | res:I07 | 1 |
| 0000-0000-8073-7028 | res:A09 | res:W366 | res:wtype-ART | 2022 | false |  | res:I07 | 1 |
| 0000-0000-8073-7028 | res:A09 | res:W417 | res:wtype-ART | 2023 | false |  | res:I07 | 1 |
| 0000-0000-8073-7028 | res:A103 | res:W478 | res:wtype-ART | 2019 | false |  | res:I08 | 1 |
| 0000-0000-8073-7028 | res:A103 | res:W478 | res:wtype-ART | 2019 | false |  | res:I07 | 1 |
| 0000-0000-8073-7028 | res:A103 | res:W531 | res:wtype-ART | 2023 | false |  | res:I08 | 1 |
| 0000-0000-8073-7028 | res:A103 | res:W531 | res:wtype-ART | 2023 | false |  | res:I07 | 1 |
| 0000-0000-8073-7028 | res:A103 | res:W686 | res:wtype-ART | 2022 | false |  | res:I08 | 1 |
| 0000-0000-8073-7028 | res:A103 | res:W686 | res:wtype-ART | 2022 | false |  | res:I07 | 1 |
| 0000-0000-8073-7028 | res:A103 | res:W693 | res:wtype-ART | 2025 | true |  | res:I07 | 1 |
| 0000-0000-8073-7028 | res:A09 | res:W714 | res:wtype-ART | 2025 | false |  | res:I07 | 1 |
| 0000-0000-8073-7028 | res:A09 | res:W738 | res:wtype-ART | 2022 | false |  | res:I07 | 1 |
| 0000-0000-8073-7028 | res:A09 | res:W802 | res:wtype-ART | 2025 | false |  | res:I07 | 1 |
| 0000-0000-8073-7028 | res:A09 | res:W967 | res:wtype-ART | 2022 | false |  | res:I07 | 1 |
| 0000-0001-6105-5008 | res:A05 | res:W1038 | res:wtype-ART | 2020 | false |  | res:I05 | 1 |
| 0000-0001-6105-5008 | res:A05 | res:W14 | res:wtype-ART | 2025 | false |  | res:I05 | 1 |
| 0000-0001-6105-5008 | res:A05 | res:W37 | res:wtype-ART | 2022 | false |  | res:I05 | 1 |
| 0000-0001-6105-5008 | res:A05 | res:W554 | res:wtype-ART | 2024 | false |  | res:I05 | 1 |
| 0000-0001-6105-5008 | res:A104 | res:W556 | res:wtype-PPR | 2019 | false | res:W1038 | res:I05 | 1 |
| 0000-0001-6105-5008 | res:A05 | res:W565 | res:wtype-ART | 2019 | false |  | res:I05 | 1 |
| 0000-0001-6105-5008 | res:A104 | res:W702 | res:wtype-ART | 2022 | false |  | res:I05 | 1 |
| 0000-0001-6105-5008 | res:A104 | res:W725 | res:wtype-ART | 2022 | false |  | res:I05 | 1 |
| 0000-0001-6105-5008 | res:A05 | res:W785 | res:wtype-REV | 2020 | false |  | res:I05 | 1 |
| 0000-0001-6105-5008 | res:A05 | res:W792 | res:wtype-ART | 2023 | false |  | res:I05 | 1 |
| 0000-0002-9841-6229 | res:A01 | res:W01 | res:wtype-ART | 2021 | false |  | res:I02 | 1 |
| 0000-0002-9841-6229 | res:A02 | res:W02 | res:wtype-PPR | 2022 | false | res:W03 | res:I02 | 1 |
| 0000-0002-9841-6229 | res:A03 | res:W03 | res:wtype-ART | 2023 | false |  | res:I02 | 1 |
| 0000-0002-9841-6229 | res:A01 | res:W04 | res:wtype-EDT | 2023 | false |  | res:I02 | 1 |
| 0000-0002-9841-6229 | res:A01 | res:W05 | res:wtype-ERR | 2024 | false |  | res:I02 | 1 |
| 0000-0002-9841-6229 | res:A01 | res:W06 | res:wtype-ART | 2024 | false |  | res:I02 | 1 |
| 0000-0002-9841-6229 | res:A02 | res:W07 | res:wtype-ART | 2020 | false |  | res:I02 | 1 |
| 0000-0002-9841-6229 | res:A01 | res:W1005 | res:wtype-ART | 2025 | false |  | res:I02 | 1 |
| 0000-0002-9841-6229 | res:A02 | res:W1048 | res:wtype-ART | 2023 | false |  | res:I02 | 1 |
| 0000-0002-9841-6229 | res:A02 | res:W1050 | res:wtype-ART | 2024 | false |  | res:I02 | 1 |
| 0000-0002-9841-6229 | res:A01 | res:W12 | res:wtype-ART | 2024 | false |  | res:I02 | 1 |
| 0000-0002-9841-6229 | res:A02 | res:W19 | res:wtype-ART | 2025 | false |  | res:I02 | 1 |
| 0000-0002-9841-6229 | res:A03 | res:W206 | res:wtype-ART | 2020 | false |  | res:I02 | 1 |
| 0000-0002-9841-6229 | res:A01 | res:W238 | res:wtype-ART | 2023 | false |  | res:I02 | 1 |
| 0000-0002-9841-6229 | res:A01 | res:W271 | res:wtype-EDT | 2019 | false |  | res:I02 | 1 |
| 0000-0002-9841-6229 | res:A01 | res:W374 | res:wtype-ART | 2023 | true |  | res:I02 | 1 |
| 0000-0002-9841-6229 | res:A02 | res:W449 | res:wtype-ART | 2022 | false |  | res:I02 | 1 |
| 0000-0002-9841-6229 | res:A01 | res:W464 | res:wtype-ART | 2021 | false |  | res:I02 | 1 |
| 0000-0002-9841-6229 | res:A101 | res:W555 | res:wtype-ART | 2020 | false |  | res:I02 | 1 |
| 0000-0002-9841-6229 | res:A101 | res:W612 | res:wtype-PPR | 2023 | false | res:W869 | res:I02 | 1 |
| 0000-0002-9841-6229 | res:A02 | res:W663 | res:wtype-PPR | 2021 | false | res:W464 | res:I02 | 1 |
| 0000-0002-9841-6229 | res:A01 | res:W676 | res:wtype-ART | 2025 | false |  | res:I02 | 1 |
| 0000-0002-9841-6229 | res:A03 | res:W763 | res:wtype-ART | 2024 | false |  | res:I02 | 1 |
| 0000-0002-9841-6229 | res:A01 | res:W813 | res:wtype-ERR | 2025 | false |  | res:I02 | 1 |
| 0000-0002-9841-6229 | res:A03 | res:W817 | res:wtype-ART | 2023 | false |  | res:I02 | 1 |
| 0000-0002-9841-6229 | res:A101 | res:W843 | res:wtype-ART | 2023 | false |  | res:I02 | 1 |
| 0000-0002-9841-6229 | res:A02 | res:W869 | res:wtype-ART | 2023 | false |  | res:I02 | 1 |
| 0000-0002-9841-6229 | res:A101 | res:W905 | res:wtype-ART | 2025 | false |  | res:I02 | 1 |
| 0000-0002-9841-6229 | res:A101 | res:W936 | res:wtype-EDT | 2019 | false |  | res:I02 | 1 |
(21 more rows not shown)

Query 2:

| a | orc | w | wt | y | i |
|---|---|---|---|---|---|
| res:A05 | 0000-0001-6105-5008 | res:W1038 | res:wtype-ART | 2020 | res:I05 |
| res:A05 | 0000-0001-6105-5008 | res:W14 | res:wtype-ART | 2025 | res:I05 |
| res:A05 | 0000-0001-6105-5008 | res:W37 | res:wtype-ART | 2022 | res:I05 |
| res:A05 | 0000-0001-6105-5008 | res:W554 | res:wtype-ART | 2024 | res:I05 |
| res:A104 | 0000-0001-6105-5008 | res:W556 | res:wtype-PPR | 2019 | res:I05 |
| res:A05 | 0000-0001-6105-5008 | res:W565 | res:wtype-ART | 2019 | res:I05 |
| res:A104 | 0000-0001-6105-5008 | res:W702 | res:wtype-ART | 2022 | res:I05 |
| res:A104 | 0000-0001-6105-5008 | res:W725 | res:wtype-ART | 2022 | res:I05 |
| res:A05 | 0000-0001-6105-5008 | res:W785 | res:wtype-REV | 2020 | res:I05 |
| res:A05 | 0000-0001-6105-5008 | res:W792 | res:wtype-ART | 2023 | res:I05 |
| res:A105 | 0000-0004-9046-7961 | res:W242 | res:wtype-ART | 2024 | res:I14 |
| res:A105 | 0000-0004-9046-7961 | res:W606 | res:wtype-ART | 2023 | res:I14 |
| res:A105 | 0000-0004-9046-7961 | res:W842 | res:wtype-ART | 2024 | res:I14 |
| res:A06 | 0000-0007-5475-1779 | res:W1031 | res:wtype-ART | 2025 | res:I12 |
| res:A06 | 0000-0007-5475-1779 | res:W28 | res:wtype-ART | 2024 | res:I12 |
| res:A06 | 0000-0007-5475-1779 | res:W34 | res:wtype-ART | 2025 | res:I12 |
| res:A06 | 0000-0007-5475-1779 | res:W38 | res:wtype-ART | 2023 | res:I12 |
| res:A06 | 0000-0007-5475-1779 | res:W384 | res:wtype-ART | 2025 | res:I12 |
| res:A06 | 0000-0007-5475-1779 | res:W525 | res:wtype-ART | 2024 | res:I12 |
| res:A06 | 0000-0007-5475-1779 | res:W835 | res:wtype-ART | 2020 | res:I12 |

Run more queries, or give the final answers.

The model

```sparql
PREFIX res: <https://example.org/research/>
SELECT ?root ?wt ?ret (COUNT(DISTINCT ?w) AS ?n) WHERE { VALUES ?root {res:I01 res:I02 res:I07 res:I09 res:I14 res:I06 res:I08 res:I05} ?au a res:Authorship; res:work ?w; res:institution ?i. ?i res:parent* ?root. ?w res:workType ?wt; res:retracted ?ret } GROUP BY ?root ?wt ?ret ORDER BY ?root ?wt ?ret
```

```sparql
PREFIX res: <https://example.org/research/>
SELECT ?s ?y ?wt ?ret (COUNT(DISTINCT ?w) AS ?n) WHERE { VALUES ?s {res:S01 res:S02 res:S04 res:S06} ?w res:source ?s; res:year ?y; res:workType ?wt; res:retracted ?ret. FILTER(?s!=res:S02 || ?y=2024) } GROUP BY ?s ?y ?wt ?ret ORDER BY ?s ?y ?wt
```

```sparql
PREFIX res: <https://example.org/research/>
SELECT ?root ?ret (COUNT(DISTINCT ?w) AS ?full) (SUM(1/?n) AS ?frac) WHERE { { SELECT DISTINCT ?w ?o ?root WHERE { VALUES ?root {res:I07 res:I09} ?au a res:Authorship; res:work ?w; res:author ?a; res:institution ?i. ?a res:orcid ?o. ?i res:parent* ?root. } } { SELECT ?w (COUNT(DISTINCT ?o2) AS ?n) WHERE { ?au2 res:work ?w; res:author ?a2. ?a2 res:orcid ?o2 } GROUP BY ?w } ?w res:year 2024; res:workType ?wt; res:retracted ?ret. FILTER(?wt IN (res:wtype-ART,res:wtype-REV)) } GROUP BY ?root ?ret
```

```sparql
PREFIX res: <https://example.org/research/>
SELECT ?c ?ret (COUNT(DISTINCT ?w) AS ?full) (SUM(1/?n) AS ?frac) WHERE { { SELECT DISTINCT ?w ?o ?c WHERE { ?au a res:Authorship; res:work ?w; res:author ?a; res:institution ?i. ?a res:orcid ?o. ?i res:country ?c. FILTER(?c="GB") } } { SELECT ?w (COUNT(DISTINCT ?o2) AS ?n) WHERE { ?au2 res:work ?w; res:author ?a2. ?a2 res:orcid ?o2 } GROUP BY ?w } ?w res:year 2024; res:workType ?wt; res:retracted ?ret. FILTER(?wt IN (res:wtype-ART,res:wtype-REV)) } GROUP BY ?c ?ret
```

Query results

Query 1:

| root | wt | ret | n |
|---|---|---|---|
| res:I01 | res:wtype-ART | false | 151 |
| res:I01 | res:wtype-ART | true | 2 |
| res:I01 | res:wtype-EDT | false | 3 |
| res:I01 | res:wtype-ERR | false | 5 |
| res:I01 | res:wtype-PPR | false | 10 |
| res:I01 | res:wtype-REV | false | 20 |
| res:I02 | res:wtype-ART | false | 103 |
| res:I02 | res:wtype-ART | true | 2 |
| res:I02 | res:wtype-EDT | false | 3 |
| res:I02 | res:wtype-ERR | false | 5 |
| res:I02 | res:wtype-PPR | false | 7 |
| res:I02 | res:wtype-REV | false | 13 |
| res:I05 | res:wtype-ART | false | 49 |
| res:I05 | res:wtype-PPR | false | 3 |
| res:I05 | res:wtype-REV | false | 7 |
| res:I06 | res:wtype-ART | false | 19 |
| res:I06 | res:wtype-REV | false | 3 |
| res:I07 | res:wtype-ART | false | 76 |
| res:I07 | res:wtype-ART | true | 5 |
| res:I07 | res:wtype-EDT | false | 1 |
| res:I07 | res:wtype-PPR | false | 4 |
| res:I07 | res:wtype-REV | false | 8 |
| res:I07 | res:wtype-SUP | false | 12 |
| res:I08 | res:wtype-ART | false | 23 |
| res:I08 | res:wtype-ART | true | 1 |
| res:I08 | res:wtype-PPR | false | 3 |
| res:I08 | res:wtype-REV | false | 1 |
| res:I08 | res:wtype-SUP | false | 4 |
| res:I09 | res:wtype-ART | false | 46 |
| res:I09 | res:wtype-ART | true | 1 |
| res:I09 | res:wtype-EDT | false | 1 |
| res:I09 | res:wtype-PPR | false | 3 |
| res:I09 | res:wtype-REV | false | 1 |
| res:I14 | res:wtype-ART | false | 43 |
| res:I14 | res:wtype-ERR | false | 2 |
| res:I14 | res:wtype-PPR | false | 7 |
| res:I14 | res:wtype-REV | false | 3 |

Query 2:

| s | y | wt | ret | n |
|---|---|---|---|---|
| res:S01 | 2019 | res:wtype-ART | false | 10 |
| res:S01 | 2019 | res:wtype-EDT | false | 2 |
| res:S01 | 2019 | res:wtype-REV | false | 2 |
| res:S01 | 2020 | res:wtype-ART | false | 6 |
| res:S01 | 2020 | res:wtype-ART | true | 1 |
| res:S01 | 2020 | res:wtype-EDT | false | 1 |
| res:S01 | 2020 | res:wtype-REV | false | 2 |
| res:S01 | 2021 | res:wtype-ART | false | 9 |
| res:S01 | 2022 | res:wtype-ART | false | 7 |
| res:S01 | 2022 | res:wtype-PTX | false | 1 |
| res:S01 | 2022 | res:wtype-REV | false | 1 |
| res:S01 | 2023 | res:wtype-ART | false | 9 |
| res:S01 | 2023 | res:wtype-EDT | false | 1 |
| res:S01 | 2023 | res:wtype-PTX | false | 1 |
| res:S01 | 2023 | res:wtype-REV | false | 2 |
| res:S01 | 2024 | res:wtype-ART | false | 22 |
| res:S01 | 2024 | res:wtype-REV | false | 2 |
| res:S01 | 2025 | res:wtype-ART | false | 22 |
| res:S01 | 2025 | res:wtype-ART | true | 1 |
| res:S01 | 2025 | res:wtype-PTX | false | 1 |
| res:S01 | 2025 | res:wtype-REV | false | 1 |
| res:S01 | 2025 | res:wtype-SUP | false | 2 |
| res:S04 | 2019 | res:wtype-ART | false | 1 |
| res:S04 | 2020 | res:wtype-ART | false | 3 |
| res:S04 | 2021 | res:wtype-ART | false | 1 |
| res:S04 | 2021 | res:wtype-REV | false | 1 |
| res:S04 | 2022 | res:wtype-ART | false | 1 |
| res:S04 | 2023 | res:wtype-ART | false | 2 |
| res:S04 | 2024 | res:wtype-REV | false | 1 |
| res:S04 | 2025 | res:wtype-ART | false | 3 |
| res:S06 | 2019 | res:wtype-ART | false | 4 |
| res:S06 | 2019 | res:wtype-PTX | false | 1 |
| res:S06 | 2020 | res:wtype-ART | false | 1 |
| res:S06 | 2020 | res:wtype-REV | false | 1 |
| res:S06 | 2021 | res:wtype-ART | false | 2 |
| res:S06 | 2021 | res:wtype-EDT | false | 1 |
| res:S06 | 2021 | res:wtype-SUP | false | 3 |
| res:S06 | 2022 | res:wtype-ART | false | 3 |
| res:S06 | 2022 | res:wtype-EDT | false | 1 |
| res:S06 | 2023 | res:wtype-ART | false | 5 |
| res:S06 | 2023 | res:wtype-PTX | false | 1 |
| res:S06 | 2023 | res:wtype-SUP | false | 3 |
| res:S06 | 2024 | res:wtype-ART | false | 7 |
| res:S06 | 2024 | res:wtype-REV | false | 1 |
| res:S06 | 2024 | res:wtype-SUP | false | 1 |
| res:S06 | 2025 | res:wtype-ART | false | 2 |
| res:S06 | 2025 | res:wtype-EDT | false | 2 |
| res:S06 | 2025 | res:wtype-ERR | false | 1 |
| res:S06 | 2025 | res:wtype-SUP | false | 3 |

Query 3:

(no rows)

Query 4:

(no rows)

Run more queries, or give the final answers.

The model

<invoke name="sparql">
</invoke>
```sparql
PREFIX res: <https://example.org/research/>
SELECT ?ret (SUM(IF(?k7>0,1,0)) AS ?f7) (SUM(?k7/?n) AS ?fr7) (SUM(IF(?k9>0,1,0)) AS ?f9) (SUM(?k9/?n) AS ?fr9) (SUM(IF(?kg>0,1,0)) AS ?fg) (SUM(?kg/?n) AS ?frg) WHERE { { SELECT ?w ?ret (COUNT(DISTINCT ?o) AS ?n) (COUNT(DISTINCT ?o7) AS ?k7) (COUNT(DISTINCT ?o9) AS ?k9) (COUNT(DISTINCT ?og) AS ?kg) WHERE { ?w res:year ?y; res:workType ?wt; res:retracted ?ret. FILTER(STR(?y)="2024" && ?wt IN (res:wtype-ART,res:wtype-REV)) ?au res:work ?w; res:author ?a. ?a res:orcid ?o. OPTIONAL{?au res:institution ?i} BIND(IF(BOUND(?i) && EXISTS{?i res:parent* res:I07},?o,?none1) AS ?o7) BIND(IF(BOUND(?i) && EXISTS{?i res:parent* res:I09},?o,?none2) AS ?o9) BIND(IF(BOUND(?i) && EXISTS{?i res:country "GB"},?o,?none3) AS ?og) } GROUP BY ?w ?ret } } GROUP BY ?ret
```
```sparql
PREFIX res: <https://example.org/research/>
SELECT ?wt ?ret (COUNT(DISTINCT ?w) AS ?n) WHERE {?w res:source res:S02; res:year ?y; res:workType ?wt; res:retracted ?ret. FILTER(STR(?y)="2024")} GROUP BY ?wt ?ret
```
```sparql
PREFIX res: <https://example.org/research/>
SELECT ?w ?wt ?y ?ret ?src ?a ?o ?i WHERE { VALUES ?w {res:W70 res:W71 res:W08} ?w res:workType ?wt; res:year ?y; res:retracted ?ret. OPTIONAL{?w res:source ?src} ?au res:work ?w; res:author ?a. OPTIONAL{?au res:institution ?i} ?a res:orcid ?o }
```
```sparql
PREFIX res: <https://example.org/research/>
SELECT (GROUP_CONCAT(DISTINCT CONCAT(STRAFTER(STR(?w),"research/"),":",STRAFTER(STR(?wt),"wtype-"),":",STR(?ret),":",COALESCE(STRAFTER(STR(?v),"research/"),""));separator=" ") AS ?l) WHERE { ?au res:work ?w; res:author ?a. ?a res:orcid "0000-0002-9841-6229". ?w res:workType ?wt; res:retracted ?ret. OPTIONAL{?w res:versionOf ?v} }
```
```sparql
PREFIX res: <https://example.org/research/>
SELECT ?o (GROUP_CONCAT(DISTINCT STRAFTER(STR(?a),"research/");separator=",") AS ?ids) (COUNT(DISTINCT ?w) AS ?n) WHERE { ?au res:work ?w; res:author ?a; res:institution ?i. ?i res:parent* res:I02. ?a res:orcid ?o. ?w res:workType ?wt. FILTER(?wt IN (res:wtype-ART,res:wtype-REV)) } GROUP BY ?o ORDER BY DESC(?n) LIMIT 5
```
```sparql
PREFIX res: <https://example.org/research/>
SELECT ?c ?d ?sa ?s2 ?s1 ?sc WHERE { ?cit res:citingWork ?c; res:citedWork ?d. FILTER(?d IN (res:W02,res:W03)) 
BIND(EXISTS{?x res:work ?c; res:author ?a1. ?a1 res:orcid ?o. ?y res:work ?d; res:author ?a2. ?a2 res:orcid ?o} AS ?sa)
BIND(EXISTS{?x2 res:work ?c; res:institution ?i1. ?i1 res:parent* res:I02. ?y2 res:work ?d; res:institution ?i2. ?i2 res:parent* res:I02} AS ?s2)
BIND(EXISTS{?x3 res:work ?c; res:institution ?i3. ?i3 res:parent* res:I01. ?y3 res:work ?d; res:institution ?i4. ?i4 res:parent* res:I01} AS ?s1)
BIND(EXISTS{?x4 res:work ?c; res:institution ?i5. ?i5 res:country ?k. ?y4 res:work ?d; res:institution ?i6. ?i6 res:country ?k} AS ?sc)
} ORDER BY ?c ?d
```
```sparql
PREFIX res: <https://example.org/research/>
SELECT ?d ?dy ?c ?cy WHERE { ?cit res:citingWork ?c; res:citedWork ?d. ?c res:year ?cy. ?d res:year ?dy. FILTER(?d IN (res:W30,res:W31) || EXISTS{?d res:versionOf ?r. FILTER(?r IN (res:W30,res:W31))} || EXISTS{?r2 res:versionOf ?d. FILTER(?r2 IN (res:W30,res:W31))}) } ORDER BY ?d ?cy
```
```sparql
PREFIX res: <https://example.org/research/>
SELECT ?a ?b WHERE {?a res:versionOf ?b. FILTER(?a IN (res:W30,res:W31) || ?b IN (res:W30,res:W31))}
```
```sparql
PREFIX res: <https://example.org/research/>
SELECT ?d (COUNT(DISTINCT ?c) AS ?n) WHERE { ?au res:work ?d; res:institution ?i. ?i res:parent* res:I07. ?d res:workType ?wt. FILTER(?wt IN (res:wtype-ART,res:wtype-REV)) ?cit res:citedWork ?d; res:citingWork ?c } GROUP BY ?d ORDER BY DESC(?n) LIMIT 6
```
```sparql
PREFIX res: <https://example.org/research/>
SELECT ?d ?wt ?ret (COUNT(DISTINCT ?cit) AS ?n) WHERE { ?au res:work ?d; res:author ?a. ?a res:orcid "0000-0000-8073-7028". ?d res:workType ?wt; res:retracted ?ret. OPTIONAL{?cit res:citedWork ?d} } GROUP BY ?d ?wt ?ret ORDER BY ?d
```
```sparql
PREFIX res: <https://example.org/research/>
SELECT ?i (COUNT(DISTINCT ?c) AS ?n) WHERE { ?au0 res:work ?d; res:institution ?i0. ?i0 res:parent* res:I07. ?d res:workType ?wt. FILTER(?wt IN (res:wtype-ART,res:wtype-REV)) ?cit res:citedWork ?d; res:citingWork ?c. ?au res:work ?c; res:institution ?i. FILTER NOT EXISTS{?i res:parent* res:I07} } GROUP BY ?i ORDER BY DESC(?n) LIMIT 6
```
```sparql
PREFIX res: <https://example.org/research/>
SELECT (COUNT(DISTINCT ?c) AS ?n) WHERE { ?au0 res:work ?d; res:institution ?i0. ?i0 res:parent* res:I07. ?d res:workType ?wt. FILTER(?wt IN (res:wtype-ART,res:wtype-REV)) ?cit res:citedWork ?d; res:citingWork ?c. ?au res:work ?c; res:institution ?i. ?i res:parent* res:I09 }
```
```sparql
PREFIX res: <https://example.org/research/>
SELECT ?lvl (GROUP_CONCAT(DISTINCT STRAFTER(STR(?c),"research/");separator=" ") AS ?l) WHERE { {?x res:citedWork res:W01; res:citingWork ?c BIND(1 AS ?lvl)} UNION {?x1 res:citedWork res:W01; res:citingWork ?c1. ?y res:citedWork ?c1; res:citingWork ?c BIND(2 AS ?lvl)} } GROUP BY ?lvl
```

Query results

Query 1:

| ret | f7 | fr7 | f9 | fr9 | fg | frg |
|---|---|---|---|---|---|---|
| false | 14 | 12.00000000000000000000000000 | 16 | 4.416666666666666666666666666 | 46 | 42.66666666666666666666666667 |
| true | 0 | 0 | 0 | 0 | 1 | 1 |

Query 2:

| wt | ret | n |
|---|---|---|
| res:wtype-PTX | false | 1 |
| res:wtype-ART | false | 24 |
| res:wtype-ERR | false | 2 |
| res:wtype-REV | false | 1 |
| res:wtype-EDT | false | 1 |
| res:wtype-ART | true | 2 |

Query 3:

| w | wt | y | ret | src | a | o | i |
|---|---|---|---|---|---|---|---|
| res:W70 | res:wtype-ART | 2023 | false | res:S02 | res:A08 | 0000-0007-9318-6032 | res:I06 |
| res:W70 | res:wtype-ART | 2023 | false | res:S02 | res:A08 | 0000-0007-9318-6032 | res:I04 |
| res:W71 | res:wtype-ART | 2024 | false | res:S01 | res:A08 | 0000-0007-9318-6032 | res:I06 |
| res:W71 | res:wtype-ART | 2024 | false | res:S01 | res:A08 | 0000-0007-9318-6032 | res:I04 |
| res:W08 | res:wtype-ART | 2025 | false | res:S01 | res:A04 | 0000-0004-8662-8360 | res:I07 |

Query 4:

| l |
|---|
| W03:ART:false: W206:ART:false: W763:ART:false: W817:ART:false: W555:ART:false: W612:PPR:false:W869 W843:ART:false: W905:ART:false: W936:EDT:false: W984:ART:false: W02:PPR:false:W03 W07:ART:false: W1048:ART:false: W1050:ART:false: W19:ART:false: W449:ART:false: W663:PPR:false:W464 W869:ART:false: W972:ART:false: W01:ART:false: W04:EDT:false: W05:ERR:false: W06:ART:false: W1005:ART:false: W12:ART:false: W238:ART:false: W271:EDT:false: W374:ART:true: W464:ART:false: W676:ART:false: W813:ERR:false: W949:ERR:false: |

Query 5:

| o | ids | n |
|---|---|---|
| 0000-0002-9841-6229 | A01,A03,A02,A101 | 23 |
| 0000-0009-2298-3695 | A07 | 15 |
| 0000-0003-7597-9990 | A110 | 14 |
| 0000-0007-9318-6032 | A106,A08 | 14 |
| 0000-0000-4633-9010 | A118 | 14 |

Query 6:

| c | d | sa | s2 | s1 | sc |
|---|---|---|---|---|---|
| res:W1048 | res:W02 | true | true | true | true |
| res:W1056 | res:W03 | false | false | false | false |
| res:W12 | res:W03 | true | true | true | true |
| res:W13 | res:W03 | true | true | true | true |
| res:W14 | res:W03 | false | false | true | true |
| res:W15 | res:W02 | false | false | false | true |
| res:W15 | res:W03 | false | false | false | true |
| res:W16 | res:W03 | false | false | false | false |
| res:W17 | res:W03 | false | false | false | false |
| res:W18 | res:W02 | false | false | false | false |
| res:W214 | res:W03 | false | false | true | true |
| res:W273 | res:W03 | false | true | true | true |
| res:W315 | res:W02 | false | true | true | true |
| res:W315 | res:W03 | false | true | true | true |
| res:W349 | res:W03 | false | false | true | true |
| res:W397 | res:W02 | false | false | false | false |
| res:W397 | res:W03 | false | false | false | false |
| res:W535 | res:W02 | false | false | false | true |
| res:W535 | res:W03 | false | false | false | true |
| res:W544 | res:W02 | false | false | true | true |
| res:W558 | res:W02 | false | false | false | false |
| res:W569 | res:W03 | false | false | false | false |
| res:W598 | res:W03 | true | true | true | true |
| res:W676 | res:W03 | true | true | true | true |
| res:W711 | res:W03 | false | false | false | false |
| res:W748 | res:W03 | false | false | true | true |
| res:W761 | res:W03 | false | true | true | true |
| res:W812 | res:W03 | false | false | true | true |
| res:W833 | res:W03 | true | true | true | true |
| res:W843 | res:W02 | true | true | true | true |
| res:W843 | res:W03 | true | true | true | true |
| res:W889 | res:W03 | false | false | false | true |
| res:W890 | res:W03 | false | false | false | false |
| res:W931 | res:W03 | false | true | true | true |
| res:W973 | res:W03 | false | true | true | true |

Query 7:

| d | dy | c | cy |
|---|---|---|---|
| res:W30 | 2019 | res:W60 | 2020 |
| res:W30 | 2019 | res:W988 | 2021 |
| res:W30 | 2019 | res:W276 | 2022 |
| res:W30 | 2019 | res:W289 | 2022 |
| res:W30 | 2019 | res:W439 | 2022 |
| res:W30 | 2019 | res:W61 | 2022 |
| res:W30 | 2019 | res:W246 | 2023 |
| res:W30 | 2019 | res:W334 | 2023 |
| res:W30 | 2019 | res:W62 | 2023 |
| res:W30 | 2019 | res:W274 | 2024 |
| res:W30 | 2019 | res:W320 | 2024 |
| res:W30 | 2019 | res:W63 | 2024 |
| res:W30 | 2019 | res:W856 | 2024 |
| res:W30 | 2019 | res:W894 | 2024 |
| res:W30 | 2019 | res:W1033 | 2025 |
| res:W30 | 2019 | res:W64 | 2025 |
| res:W30 | 2019 | res:W878 | 2025 |
| res:W30 | 2019 | res:W992 | 2025 |
| res:W31 | 2023 | res:W1039 | 2023 |
| res:W31 | 2023 | res:W62 | 2023 |
| res:W31 | 2023 | res:W851 | 2023 |
| res:W31 | 2023 | res:W320 | 2024 |
| res:W31 | 2023 | res:W65 | 2024 |
| res:W31 | 2023 | res:W650 | 2024 |
| res:W31 | 2023 | res:W318 | 2025 |
| res:W31 | 2023 | res:W66 | 2025 |
| res:W31 | 2023 | res:W794 | 2025 |
| res:W31 | 2023 | res:W878 | 2025 |
| res:W42 | 2023 | res:W1039 | 2023 |
| res:W42 | 2023 | res:W67 | 2023 |
| res:W42 | 2023 | res:W757 | 2023 |
| res:W42 | 2023 | res:W249 | 2025 |

Query 8:

| a | b |
|---|---|
| res:W42 | res:W31 |

Query 9:

| d | n |
|---|---|
| res:W22 | 19 |
| res:W20 | 14 |
| res:W401 | 5 |
| res:W21 | 3 |
| res:W227 | 3 |
| res:W599 | 3 |

Query 10:

| d | wt | ret | n |
|---|---|---|---|
| res:W1025 | res:wtype-ART | true | 0 |
| res:W20 | res:wtype-ART | false | 14 |
| res:W203 | res:wtype-ART | false | 0 |
| res:W21 | res:wtype-ART | false | 3 |
| res:W22 | res:wtype-REV | false | 19 |
| res:W23 | res:wtype-ART | true | 1 |
| res:W232 | res:wtype-ART | false | 0 |
| res:W268 | res:wtype-ART | false | 0 |
| res:W366 | res:wtype-ART | false | 1 |
| res:W417 | res:wtype-ART | false | 2 |
| res:W478 | res:wtype-ART | false | 0 |
| res:W531 | res:wtype-ART | false | 1 |
| res:W686 | res:wtype-ART | false | 0 |
| res:W693 | res:wtype-ART | true | 0 |
| res:W714 | res:wtype-ART | false | 0 |
| res:W738 | res:wtype-ART | false | 0 |
| res:W802 | res:wtype-ART | false | 0 |
| res:W967 | res:wtype-ART | false | 1 |

Query 11:

| i | n |
|---|---|
| res:I12 | 16 |
| res:I11 | 5 |
| res:I09 | 4 |
| res:I14 | 4 |
| res:I19 | 4 |
| res:I17 | 3 |

Query 12:

| n |
|---|
| 4 |

Query 13:

| lvl | l |
|---|---|
| 1 | W229 W40 W41 W602 W657 W660 W844 W895 |
| 2 | W682 W338 W396 W50 W51 W546 W895 W922 W52 W90 W1042 W337 W801 W844 |

Run more queries, or give the final answers.

The model

<invoke name="sparql">
</invoke>
```sparql
PREFIX res: <https://example.org/research/>
SELECT (COUNT(DISTINCT ?w) AS ?n34) WHERE { ?au res:work ?w; res:institution ?i. ?i res:parent* res:I07. ?w res:year ?y; res:workType ?wt; res:retracted false. FILTER(STR(?y)="2025" && ?wt IN (res:wtype-ART,res:wtype-REV)) }
```
```sparql
PREFIX res: <https://example.org/research/>
SELECT (COUNT(DISTINCT ?w) AS ?n39) WHERE { ?au res:work ?w; res:institution ?i. ?i res:parent* res:I02. ?w res:source ?s; res:workType ?wt; res:retracted false. ?s res:tier res:tier-K3. FILTER(?wt IN (res:wtype-ART,res:wtype-REV)) }
```
```sparql
PREFIX res: <https://example.org/research/>
SELECT ?i ?p WHERE { VALUES ?i {res:I04 res:I06 res:I03} OPTIONAL{?i res:parent ?p} }
```

Query results

Query 1:

| n34 |
|---|
| 25 |

Query 2:

| n39 |
|---|
| 21 |

Query 3:

| i | p |
|---|---|
| res:I04 | res:I03 |
| res:I06 | res:I02 |
| res:I03 | res:I02 |

This was the last round: give the final answers now, with no more queries.

The model

**Q1.** 1. A01, A02 and A03 share ORCID 0000-0002-9841-6229, so they are one person. A101 ("M. Ellison") also carries that ORCID, while A04 and A102 are different people.

**Q2.** 32 works. Mara Ellison's records A01, A02, A03 and A101 all share one ORCID, and I included every document type, retracted ones too. The list is in the JSON.

**Q3.** No. W37 is by A05 (ORCID …6105-5008, I05) and W38 is by A06 (ORCID …5475-1779, I12).

**Q4.** 9. A05's ORCID covers W1038, W14, W37, W554, W565, W702, W725, W785 and W792; W556 is a preprint of W1038 and is not counted separately. I counted only ART and REV works that are not retracted.

**Q5.** No. W08's M. Ellison is A04 (ORCID …8662-8360), which differs from Mara Ellison's ORCID.

**Q6.** A01, the Mara Ellison person (A01/A02/A03/A101), with 23 ART/REV works credited to I02 or its units. The next is A07 with 15.

**Q7.** 22. This is her ART and REV works, excluding the retracted W374 and counting the preprints W02, W612 and W663 with their published versions.

**Q8.** I01. The chain is I04 → I03 → I02 → I01.

**Q9.** 116, from 103 ART and 13 REV that are not retracted. Preprints are assumed to merge with their published versions.

**Q10.** 171, from 151 ART and 20 REV.

**Q11.** 84, from 76 ART and 8 REV. SUP, EDT and PPR are excluded and retracted works are not counted.

**Q12.** Full counting gives 14 and fractional counting gives 12.0.

**Q13.** Full counting: I09 (16 against 14). Fractional counting: I07 (12.0 against about 4.42).

**Q14.** Full counting gives 46 and fractional counting gives about 42.67. These are ART/REV works from 2024 that are not retracted.

**Q15.** 25, from 24 ART and 1 REV that are not retracted.

**Q16.** 95, from 85 ART and 10 REV that are not retracted.

**Q17.** W04, W05, W271, W813, W936 and W949. They are editorials (EDT) and errata (ERR).

**Q18.** 15.

**Q19.** 30 distinct works cite W02 or W03.

**Q20.** W02, W42, W556, W612 and W663. These are the ones I saw in the data; I did not run a full listing, so the list may be incomplete.

**Q21.** 46, from 43 ART and 3 REV.

**Q22.** W31, counting its preprint W42, has more citations in both cases. In total W31 has 13 against 18 for W30... that is wrong on that count: W30 has more in total (18 against 13). Within the publication year and the next two years W31 leads (13 against 2).

**Q23.** W30 has 18 citations in total and 2 within the window (2019–2021).

**Q24.** 15, excluding the retracted W1025, W23 and W693.

**Q25.** 41, from W20 (14), W21 (3), W22 (19), W366 (1), W417 (2), W531 (1) and W967 (1).

**Q26.** No. W23 is retracted.

**Q27.** I12 (Université de Lorvain), with 16 citing works.

**Q28.** 4.

**Q29.** Among the 30 citing works, 7 are self-citations at the author level, 12 at the University of Albury level (units included) and 21 at the country level.

**Q30.** 18.

**Q31.** 14 works: W682, W338, W396, W50, W51, W546, W895, W922, W52, W90, W1042, W337, W801 and W844.

**Q32.** 20. That is 8 works citing W01 directly plus 14 at two hops, with W895 and W844 in both.

**Q33.** W22, with 19 citations.

**Q34.** 25.

**Q35.** 24, from 23 ART and 1 REV.

**Q36.** 26, from 24 ART and 2 REV.

**Q37.** I04, though W70 is also credited to I06 on a second authorship line, so the data does not give a single answer.

**Q38.** I04, I03, I02, I01 and I06. W71's authorship lists I04 and I06, and I04's ancestors are I03, I02 and I01.

**Q39.** 21.

**Q40.** S01, which is tier K3.

**Q41.** No. S03 is K1 and S02 is K2.

**Q42.** 13, from 11 ART and 2 REV.

**Q43.** Yes. W07 is a non-retracted article.

**Q44.** I02, I03, I04, I05, I06, I19, I20 and I21.

**Q45.** 22, from 19 ART and 3 REV.

**Q46.** I01. I06 → I02 → I01.

**Q47.** Kesting has fewer 2024 works than Rostval (14 against 16). Its works have few co-authors, so its fractional share (12.0) is far larger than Rostval's (about 4.4), which comes from works with many authors from elsewhere.

**Q48.** The data does not show that W70 is excluded. I04 sits under I03, which sits under I02, and W70 is a non-retracted 2023 article, so it should count for the University of Albury. If it is excluded, the data I queried does not say why.

```json
{
"Q1":{"count":1},
"Q2":{"works":["W03","W206","W763","W817","W555","W612","W843","W905","W936","W984","W02","W07","W1048","W1050","W19","W449","W663","W869","W972","W01","W04","W05","W06","W1005","W12","W238","W271","W374","W464","W676","W813","W949"]},
"Q3":{"same":"no"},
"Q4":{"count":9},
"Q5":{"same":"no"},
"Q6":{"author":"A01"},
"Q7":{"count":22},
"Q8":{"parent":"I01"},
"Q9":{"count":116},
"Q10":{"count":171},
"Q11":{"count":84},
"Q12":{"full":14,"fractional":12},
"Q13":{"full":"I09","fractional":"I07"},
"Q14":{"full":46,"fractional":42.67},
"Q15":{"count":25},
"Q16":{"count":95},
"Q17":{"works":["W04","W05","W271","W813","W936","W949"]},
"Q18":{"count":15},
"Q19":{"count":30},
"Q20":{"works":["W02","W42","W556","W612","W663"]},
"Q21":{"count":46},
"Q22":{"more_in_total":"W30","more_in_window":"W31"},
"Q23":{"total":18,"in_window":2},
"Q24":{"count":15},
"Q25":{"count":41},
"Q26":{"counts":"no"},
"Q27":{"institution":"I12","citing_works":16},
"Q28":{"count":4},
"Q29":{"author":7,"institution":12,"country":21},
"Q30":{"count":18},
"Q31":{"works":["W682","W338","W396","W50","W51","W546","W895","W922","W52","W90","W1042","W337","W801","W844"]},
"Q32":{"count":20},
"Q33":{"work":"W22"},
"Q34":{"count":25},
"Q35":{"count":24},
"Q36":{"count":26},
"Q37":{"institution":"I04"},
"Q38":{"institutions":["I04","I03","I02","I01","I06"]},
"Q39":{"count":21},
"Q40":{"source":"S01"},
"Q41":{"higher":"no"},
"Q42":{"count":13},
"Q43":{"research":"yes"},
"Q44":{"institutions":["I02","I03","I04","I05","I06","I19","I20","I21"]},
"Q45":{"count":22},
"Q46":{"parent":"I01"}
}
```