workflow nodetrix-hybrid-network-exploration template: contextualise -> define-unit -> contextualise -> characterise -> visualise -> abstract -> loop(define-unit (adjust aggregation) -> contextualise (reposition aggregates) -> characterise (update attributes) -> visualise -> abstract -> assess) -> generate-knowledge description: "Assumed composite workflow (synthesised from the co-authorship case study) for exploring social networks using a hybrid node-link/matrix representation; dense subgraphs are interactively aggregated into adjacency matrices and repositioned within the network layout, while sparse inter-community structure remains a node-link diagram, supporting iterative exploration of communities, central actors, and collaboration roles" # ============================================================================ # INPUT # ============================================================================ artifact D_researchers : entities origin: given internal structure: elementary embedment: relational structure features: - id: f_name value structure: atomic value type: text description: "Researcher identifier" - id: f_citation_count value structure: atomic value type: numeric description: "Number of citations" description: "Researchers (vertices) embedded within the co-authorship collaboration network" artifact F_collaboration : feature(D_researchers) origin: given value structure: relational configuration value type: numeric representation form: "co-authorship graph with weighted edges representing collaboration strength" description: "Pairwise collaboration relationships between researchers, with associated collaboration-strength attributes" # ============================================================================ # STEP 1: INITIAL NODE-LINK LAYOUT OF THE UNDERLYING NETWORK # ============================================================================ transform T_layout : intent: contextualise manner: "energy-based cluster-prominent graph layout" input: D_researchers, F_collaboration output: D_layout_space, A_node_link actor: machine description: "Compute an initial graph layout that gives prominence to densely connected clusters and exposes the sparse global structure" artifact D_layout_space : entities internal structure: elementary features: - id: f_dimensions value structure: atomic value type: numeric description: "Number of spatial dimensions (2)" description: "Two-dimensional layout space for positioning researchers and aggregate communities" artifact A_node_link : arrangement(D_researchers) context: D_layout_space principle: "energy-based layout emphasising dense clusters" description: "Node-link positions of individual researchers reflecting global network structure and cluster prominence" # ============================================================================ # STEP 2: INITIAL AGGREGATION INTO COMMUNITIES # ============================================================================ transform T_initial_aggregate : intent: define-unit manner: "interactive selection and aggregation of densely connected subgraphs into community units" input: D_researchers, F_collaboration, A_node_link output: D_communities, F_community_membership actor: hybrid description: "Select and aggregate densely connected groups of researchers into community units guided by cluster prominence in the layout; researchers not aggregated remain as individual units" artifact D_communities : entities internal structure: group/cluster embedment: relational structure features: - id: f_community_size value structure: atomic value type: numeric description: "Number of researchers in the community" description: "Aggregated groups of researchers representing dense collaboration communities, connected to each other through remaining inter-community collaborations; a community may contain a single researcher" artifact F_community_membership : feature(D_researchers) value structure: atomic value type: categorical description: "Community membership assignment for each researcher" # ============================================================================ # STEP 3: ARRANGE AGGREGATE COMMUNITIES IN THE LAYOUT SPACE # ============================================================================ transform T_arrange_communities : intent: contextualise manner: "derive aggregate-node positions from the initial network layout" input: D_communities, F_community_membership, A_node_link, D_layout_space output: A_community_layout actor: machine description: "Place aggregate communities in the layout space using the positions of their underlying researchers in the initial node-link layout" artifact A_community_layout : arrangement(D_communities) context: D_layout_space principle: "aggregate-node placement derived from member positions in the initial node-link layout" description: "Initial positions of NodeTrix aggregate nodes and matrices in the two-dimensional network layout" # ============================================================================ # STEP 4: PROPAGATE ATTRIBUTES TO COMMUNITIES # ============================================================================ transform T_initial_characterise : intent: characterise manner: "aggregate underlying node and edge attributes into community-level attributes" input: D_communities, F_community_membership, D_researchers, F_collaboration output: F_community_attributes actor: machine description: "Compute community-level attributes (e.g., averaged values for numeric attributes, concatenated values for nominal attributes) from member researcher and collaboration attributes" artifact F_community_attributes : feature(D_communities) value structure: vector value type: {numeric, categorical, text} description: "Aggregated attributes of each community derived from its member researchers and their collaborations" # ============================================================================ # STEP 5: INITIAL HYBRID VISUALISATION AND OVERVIEW # ============================================================================ transform T_initial_visualise : intent: visualise manner: "hybrid node-link and matrix visualisation" input: A_community_layout, D_communities, D_researchers, F_community_membership, F_collaboration, F_community_attributes output: V_nodetrix actor: machine description: "Render aggregate communities as adjacency matrices, with inter-community collaborations shown as node-link connections and intra-community collaborations shown as matrix cells" artifact V_nodetrix : visualisation(A_community_layout, D_communities, D_researchers, F_community_membership, F_collaboration, F_community_attributes) layout: "node-link diagram of aggregate communities with adjacency matrices overlaid on multi-member aggregate nodes" form: "matrices for communities and links for inter-community collaborations" encoding: "aggregate-node position from A_community_layout; matrix rows and columns represent member researchers and can be manually reordered; axis labels from f_name; axis colour from f_citation_count; matrix cells and inter-community links from F_collaboration; matrix background colour from F_community_attributes" description: "Interactive hybrid visualisation showing global network structure through node-link connections and dense communities through adjacency matrices" transform T_initial_interpret : intent: abstract manner: "perception and interpretation of community density, bridging actors, and connection patterns" input: V_nodetrix output: P_patterns actor: human description: "Identify collaboration pattern types, central or bridging actors, and community cohesion from the visualisation" artifact P_patterns : pattern(D_communities, D_researchers) representation form: "categorized collaboration patterns with descriptions" description: "Identified collaboration pattern types among communities (e.g., hub-dominated, clique-like, intermediate structures) and bridging or central actors" # ============================================================================ # STEP 6: INTERACTIVE EXPLORATION LOOP # ============================================================================ loop L_exploration: purpose: "Iteratively adjust aggregation and spatial positioning of communities to explore community structure, central actors, and collaboration patterns at an appropriate level of detail" until: "The representation provides a readable, informative view sufficient to identify communities, central actors, and collaboration roles for the current analytical goal" body: transform T_adjust_aggregation : intent: define-unit manner: "merge, split, add, remove, or transfer members of aggregate communities through direct manipulation" input: D_communities, F_community_membership, V_nodetrix output: D_communities_r, F_community_membership_r actor: human description: "Refine community aggregation by merging matrices, splitting matrices, adding or removing researchers, and transferring researchers between aggregate communities" artifact D_communities_r : entities internal structure: group/cluster embedment: relational structure features: - id: f_community_size value structure: atomic value type: numeric description: "Number of researchers in the community" description: "Updated community groupings after interactive adjustment" artifact F_community_membership_r : feature(D_researchers) value structure: atomic value type: categorical description: "Updated community membership assignment for each researcher" assign: D_communities := D_communities_r F_community_membership := F_community_membership_r transform T_reposition_communities : intent: contextualise manner: "direct manipulation of aggregate-node positions" input: D_communities, A_community_layout, V_nodetrix output: A_community_layout_r actor: human description: "Move aggregate nodes or matrices to improve readability of the hybrid network representation" artifact A_community_layout_r : arrangement(D_communities) context: D_layout_space principle: "user-defined aggregate-node placement" description: "Updated positions of aggregate nodes and matrices after direct manipulation" assign: A_community_layout := A_community_layout_r transform T_update_attributes : intent: characterise manner: "recompute aggregated community-level attributes" input: D_communities, F_community_membership, D_researchers, F_collaboration output: F_community_attributes_r actor: machine description: "Recompute community-level attributes reflecting the updated aggregation" artifact F_community_attributes_r : feature(D_communities) value structure: vector value type: {numeric, categorical, text} description: "Updated aggregated attributes of each community after re-aggregation" assign: F_community_attributes := F_community_attributes_r transform T_visualise_r : intent: visualise manner: "update hybrid node-link and matrix visualisation through direct manipulation and display controls" input: V_nodetrix, A_community_layout, D_communities, D_researchers, F_community_membership, F_collaboration, F_community_attributes output: V_nodetrix_r actor: hybrid description: "Update the NodeTrix view after aggregation, positioning, or visual-variable adjustments such as link thickness, matrix size, and axis-label visibility" artifact V_nodetrix_r : visualisation(A_community_layout, D_communities, D_researchers, F_community_membership, F_collaboration, F_community_attributes) layout: "node-link diagram of aggregate communities with adjacency matrices overlaid on multi-member aggregate nodes" form: "matrices for communities and links for inter-community collaborations" encoding: "same encoding as V_nodetrix, reflecting updated aggregation, positioning, and display settings" description: "Updated hybrid visualisation reflecting current aggregation, positioning, and display settings" assign: V_nodetrix := V_nodetrix_r transform T_interpret_r : intent: abstract manner: "perception and interpretation of community density, bridging actors, and connection patterns" input: V_nodetrix output: P_patterns_r actor: human description: "Identify or refine collaboration pattern types, central or bridging actors, and community cohesion from the updated visualisation" artifact P_patterns_r : pattern(D_communities, D_researchers) representation form: "categorized collaboration patterns with descriptions" description: "Updated or refined collaboration pattern types and identification of central or bridging actors" assign: P_patterns := P_patterns_r transform T_assess : intent: assess manner: "judge readability and adequacy of the current aggregation and positioning for the current analytical goal" input: V_nodetrix, P_patterns output: K_exploration_quality actor: human description: "Evaluate whether the current aggregation level, layout, and visual encoding adequately support community, central-actor, and role analysis, or whether further adjustment is needed" artifact K_exploration_quality : knowledge(D_communities) representation form: "quality judgment" description: "Assessment of whether the current representation sufficiently supports community identification, central actor identification, and role analysis" end loop L_exploration # ============================================================================ # STEP 7: SYNTHESISE FINDINGS # ============================================================================ transform T_synthesise : intent: generate-knowledge manner: "formulate statements about community structure and collaboration roles" input: P_patterns, K_exploration_quality output: K_findings actor: human description: "Synthesise findings about collaboration communities, central and bridging actors, and characteristic collaboration pattern types" artifact K_findings : knowledge(P_patterns, K_exploration_quality) representation form: "statements and explanations" description: "Documented findings about collaboration communities, central and bridging actors, and collaboration pattern types revealed through hybrid network exploration"