---
title: 'DiscopFlow: Organizational Workflow Mining'
url: https://www.emergentmind.com/topics/discopflow
type: topic
---

# DiscopFlow: Organizational Workflow Mining

DiscopFlow is a workflow mining (WM) tool designed specifically to uncover and analyze organizational structures and interaction protocols embedded within business processes. Distinct from prior WM systems, DiscopFlow leverages enriched workflow logs incorporating FIPA-ACL performatives, enabling extraction of social and communicative dynamics such as hierarchies, coalitions, federations, markets, and negotiation patterns including contract-net, auction, and voting protocols. Its architecture employs modular analyzers to separately address organizational structure, protocol detection, informational perspective, graphical representation, and basic performance metrics, grounded in a formal meta-model extending classical workflow logs by actor-to-actor interaction events [1203.4257].

## 1. System Architecture and Modules

DiscopFlow comprises seven integrated software modules and a central workflow-log database (Oracle 10g), organized as follows:

| Module                  | Core Function                                          | Status           |
|-------------------------|-------------------------------------------------------|------------------|
| LogGenerator            | Create/populate enriched log per workflow meta-model   | Implemented      |
| LogConverter            | Export relational logs to XML                         | Under development|
| OrgStruct_Analyser      | Detect and classify organizational structures          | Implemented      |
| InterPro_Analyser       | Detect organization-level protocols                   | Implemented      |
| Info_Analyser           | Discover document flows per activity                  | Implemented      |
| AGR_Analyser            | Visualize agent-group-role (AGR) relationships        | Implemented      |
| Performance_Analyser    | Analyze activity and actor performance                | Under development|

All analytic modules connect to the relational database via JDBC. Log generation precedes analysis; subsequent modules read the enriched event log and produce structural, informational, or graphical outputs. The future LogConverter will provide tool-independent XML export for interoperability and further processing [1203.4257].

## 2. Workflow Log Meta-Model

The DiscopFlow meta-model extends conventional process-event logs by capturing explicit communicative actions between actors. The model is characterized by:

- $P = \{p_1, \dotsc, p_n\}$: Business processes
- $I_p = \{i_1, \dotsc, i_k\}$: Instances for process $p$
- $E = \{e_1, \dotsc, e_m\}$: Log events
- $A, R, U, D, M$: Sets of actors, roles, organizational units, documents, FIPA-ACL performatives

Each event $e \in E$ is a 7-tuple:

$$
e = (\operatorname{inst}(e), \operatorname{ts}(e), \operatorname{act}(e), \operatorname{doc_{in}}(e), \operatorname{doc_{out}}(e), \operatorname{sender}(e), \operatorname{receiver}(e), \operatorname{perf}(e))
$$

where:
- $\operatorname{inst}(e)$ identifies the process instance,
- $\operatorname{ts}(e)$ is a timestamp,
- $\operatorname{act}(e)$ is the activity,
- $\operatorname{doc_{in}}(e), \operatorname{doc_{out}}(e)$ are input/output documents,
- $\operatorname{sender}(e), \operatorname{receiver}(e)$ are actors or ‘System’,
- $\operatorname{perf}(e)$ is the FIPA-ACL performative.

Actor-role and actor-unit mappings are represented as functions:
- $\operatorname{role}: A \rightarrow 2^R$
- $\operatorname{unit}: A \rightarrow U$

The meta-model captures organizational and informational context, enabling analysis of “who does what” (via activity, role, unit), “with which documents,” and critically, “by which communicative acts” [1203.4257].

## 3. Organizational Structure and Interaction Protocol Discovery

### 3.1 Structure Detection

The OrgStruct_Analyser builds a directed multigraph $G$ on actors, labeling edges $(a \to b)$ with multisets of exchanged performatives. It implements pattern-based identification of:

- **Strict Hierarchy:** $\forall e$ with $\operatorname{perf}(e) = $ 'delegate', $\operatorname{sender}(e) = a$, $\operatorname{receiver}(e) = b$, with no reverse delegation, then $(a,b)$ is a strict superior–subordinate relation.
- **Relaxed Hierarchy:** If delegation occurs bidirectionally, $(a,b)$ have a relaxed hierarchy.
- **Federation:** Symmetric exchange of 'cfp' and ‘propose’ on the same activity, no persistent dominance.
- **Coalition:** Groups mutually propose for an activity, without clear leader.
- **Market:** Calls for proposal issued to a pool with winner selection denotes market dynamics.

The pseudocode iterates over $(a, b) \in A \times A$, counting delegation events to detect strict versus relaxed hierarchies with time complexity $O(n^2 + m)$, where $n = |A|$ and $m = |E|$ [1203.4257].

### 3.2 Protocol Identification

The InterPro_Analyser detects negotiation protocols via pattern-matching on performative sequences per activity instance $\sigma_i = \langle \operatorname{perf}(e_1), \operatorname{perf}(e_2), \dotsc \rangle$:

- **Contract Net:** Subsequence matches $cfp$ $(propose)^+$ $(accept$-$proposal \mid reject$-$proposal)^+$ $execute$.
- **Auction:** Pattern $cfp$ $(bid \mid propose)^*$ $inform$-$result$.
- **Vote:** $cfp$, multiple $propose$, then $inform$-$decision$.

Pattern detection operates in linear time with respect to the length of $\sigma_i$ [1203.4257].

## 4. Use of FIPA-ACL Performatives

DiscopFlow operationalizes each FIPA-ACL performative as an indicator of social intent:

- **delegate:** Authorization/subordination
- **cfp:** Initiation of negotiation
- **propose**/**bid:** Offer submissions
- **accept-proposal / reject-proposal:** Outcome resolutions
- **inform:** Notification

Sequences and distributions of these communicative acts, when aggregated per actor pair or case, allow reconstruction of both macroscopic organizational forms and microscopic negotiation protocols in process enactment [1203.4257].

## 5. Empirical Example

A segment from the water distribution crisis process log illustrates DiscopFlow’s event representation:

1. (Mahdi → System: Execute(Investigation report establishment))
2. (Mahdi → Salim: Delegate(Alarm triggering))
3. (Salim → Mahdi: Inform(Alarm triggering))
4. (Malik → Sami: Cfp(Analysis samples))
5. (Malik → Amal: Cfp(Analysis samples))
6. (Amal → Malik: Propose(Analysis samples))
7. (Sami → Malik: Propose(Analysis samples))
8. (Malik → Amal: Accept-proposal(Analysis samples))
9. (Malik → Sami: Reject-proposal(Analysis samples))
10. (Amal → System: Execute(Analysis samples))

From lines 2–3, DiscopFlow infers a strict hierarchy between Mahdi and Salim. Lines 4–9 instantiate a contract-net protocol among Malik, Amal, and Sami, with Malik as initiator and Amal/Sami as responders, matching the contract-net pattern in negotiation [1203.4257].

## 6. Comparison with Existing Workflow Mining Tools

DiscopFlow is evaluated against ProM, InWolvE, and WorkflowMiner according to criteria:

| Feature                    | ProM        | InWolvE      | WorkflowMiner | DiscopFlow      |
|----------------------------|-------------|--------------|---------------|-----------------|
| Log Conversion             | Yes         | Yes          | No            | Yes             |
| Informational Perspective  | Partial     | No           | No            | Yes             |
| Organizational Discovery   | Partial     | No           | No            | Yes             |
| Delta/Performance Analysis | Yes         | No           | No            | Planned         |

DiscopFlow is the only system to provide comprehensive organizational structure and interaction protocol discovery by leveraging FIPA-ACL performatives. No precision/recall metrics are reported, and performance and process-integration modules remain under development [1203.4257].

## 7. Contributions, Open Issues, and Future Directions

DiscopFlow advances workflow mining through:

1. Demonstration that Multi-Agent System (MAS) abstractions can be discovered via enriched workflow logs.
2. Formalization of an extended event-log meta-model integrating performatives, actors, roles, units, and document flows.
3. Implementation of a modular prototype supporting detection of organizational forms and interaction protocols, with AGR (Agent–Group–Role) visualization.

Limitations include the need for full implementation of performance analytics and log conversion to XML, validation on larger real-world data sets, and formal evaluation against engineered baselines [1203.4257]. A plausible implication is that future work may incorporate integrated mining of process, informational, and organizational perspectives, further advancing the field of workflow mining through multi-perspective analysis.

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**Reference:** "DiscopFlow: A new Tool for Discovering Organizational Structures and Interaction Protocols in WorkFlow" [1203.4257]

Source: https://www.emergentmind.com/topics/discopflow