Icon

DE1_​Term2_​Main

API callingWikidata API Node combination, data cleaning PainterPalette: ~10000 paintersAttributes of style/movement, quantitative data e-flux: Coexhibition data of artistsOur source ofconnections in the network Artist names Announcements Artist names Announcement-artist pairs Exactmatches(inner join) TODONeo4j connection TODONeo4j Add Graph TODOAnalytics We could do veryinteresting analyses, e.g.find communities(clusters), or I wouldn't mind Pythontoo, also for visualization But we also should doanalytics (dynamic) andbe according to the ETLpipeline, so do someanalytics that varies stepby step "Which art movements aremost interconnected?" -centrality measures"Are there key painters whoserve as 'bridges' betweendistinct art movements?""What communities arepresent in the network?"ClusteringCan cluster each newpainter e.g. in the ETLpipeline"Do certain regions orcountries dominate specificclusters or artisticmovements?" - same withgender, nationality etc. TODO ETL PIPELINE in parallel (in KNIME!)Trigger on 1) new painters added to the network (Neo4j), call API before? 2) ?new connection between two painters? could even filter the graph TODO combinestylistic columns? Removing doublespaces and only firstletter is upper case Removing douplespaces, and onlythe first letter isupper case 1012 rows 1081 rows Removing '-'and replacingwith spaceReplacingdots with dotAND space Removing '-' andreplacing with space Removing everyspecial character Removing everyspecial character 1152 rows Robust combination: Someartists have not exactly thesame name stored, we findsome of these pairs FilteredAnnouncement-artist pairs Can get many types of data,but not stylistic data Loop through artist chunks, slow! Might be done entirely in KNIME if wesolve API result processingNode 2Node 4Node 11Node 12Node 13Node 15Node 16Node 18Node 21Node 22Node 23Node 24Node 28Node 29Node 30Node 36Node 37Node 38Node 39Node 40Node 41Node 42Node 44Node 49Node 50Node 51Node 52Node 53Node 54File Reader Column Filter JSON Reader JSON Path Column Filter GroupBy Ungroup Joiner Empty Table Switch Empty Table Switch Cluster Assigner Bar Chart(JavaScript) Joiner String Manipulation String Manipulation String Manipulation String Manipulation String Manipulation String Manipulation Joiner Column Renamer ReferenceRow Filter String Manipulation Column Filter Chunk Loop Start MISSINGPython Script Loop End String Manipulation String to Number API callingWikidata API Node combination, data cleaning PainterPalette: ~10000 paintersAttributes of style/movement, quantitative data e-flux: Coexhibition data of artistsOur source ofconnections in the network Artist names Announcements Artist names Announcement-artist pairs Exactmatches(inner join) TODONeo4j connection TODONeo4j Add Graph TODOAnalytics We could do veryinteresting analyses, e.g.find communities(clusters), or I wouldn't mind Pythontoo, also for visualization But we also should doanalytics (dynamic) andbe according to the ETLpipeline, so do someanalytics that varies stepby step "Which art movements aremost interconnected?" -centrality measures"Are there key painters whoserve as 'bridges' betweendistinct art movements?""What communities arepresent in the network?"ClusteringCan cluster each newpainter e.g. in the ETLpipeline"Do certain regions orcountries dominate specificclusters or artisticmovements?" - same withgender, nationality etc. TODO ETL PIPELINE in parallel (in KNIME!)Trigger on 1) new painters added to the network (Neo4j), call API before? 2) ?new connection between two painters? could even filter the graph TODO combinestylistic columns? Removing doublespaces and only firstletter is upper case Removing douplespaces, and onlythe first letter isupper case 1012 rows 1081 rows Removing '-'and replacingwith spaceReplacingdots with dotAND space Removing '-' andreplacing with space Removing everyspecial character Removing everyspecial character 1152 rows Robust combination: Someartists have not exactly thesame name stored, we findsome of these pairs FilteredAnnouncement-artist pairs Can get many types of data,but not stylistic data Loop through artist chunks, slow! Might be done entirely in KNIME if wesolve API result processingNode 2Node 4Node 11Node 12Node 13Node 15Node 16Node 18Node 21Node 22Node 23Node 24Node 28Node 29Node 30Node 36Node 37Node 38Node 39Node 40Node 41Node 42Node 44Node 49Node 50Node 51Node 52Node 53Node 54File Reader Column Filter JSON Reader JSON Path Column Filter GroupBy Ungroup Joiner Empty Table Switch Empty Table Switch Cluster Assigner Bar Chart(JavaScript) Joiner String Manipulation String Manipulation String Manipulation String Manipulation String Manipulation String Manipulation Joiner Column Renamer ReferenceRow Filter String Manipulation Column Filter Chunk Loop Start MISSINGPython Script Loop End String Manipulation String to Number

Nodes

Extensions

Links

Download

To use this workflow in KNIME, download it from the below URL and open it in KNIME:

Download Workflow
Created by: hanic
Created at: 2024-11-08
On NodePit since: 2024-11-27
Last update: 2024-12-17
Created with KNIME version: v5.3.2

Deploy, schedule, execute, and monitor your KNIME workflows locally, in the cloud or on-premises – with our brand new NodePit Runner.

Try NodePit Runner!