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This thesis is motivated by the steep increase in grass-root content production and the transformation of Web2.0 consumers into “prosumers”, a concept that pre-dated the web itself (Toffler 1980). The notion of “prosumers” in the Web 2.0 and beyond presumes an increasingly wider-scale ability for content creation with a much deeper understanding of the implications and associated risks (at all levels from quality to IPR and copyright aspects). Technology today offers the possibility to easily master complex processes such as video/image editing with a home computer or a laptop yet this is not sufficient for managing all the decision points involved in an informed fashion. The widespread availability of office-automation solutions powerful enough to handle fairly complex processes of monitoring and management, raises the research question as to the feasibility of providing a didactic model and support tools that could better serve the increased desire of web users to become content producers.
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Contingent Workflow Modelling for a Didactic Approach to
Project Management in Media Content Production
David Luigi FUSCHI
Context
Topic: Media content production
Issue: monitoring and managing the decision making process while understanding the embedded risks
Approach: a formula-based media content production planning, monitoring and risk management system
Contribution (I)
A project management approach to the description of creative media content production processes and related risks
A comparative analysis of creative media content production processes
A clear indication of intra-process dependencies, relations and risks
Contribution (II)
A complete reference model for the Filmmaking process from Concept to Fruition
A didactic support for teaching Content Production Planning and Risk Management
A customisable system for Content Production Planning and Risk Management
Addressed Domains
Stakeholders taken into account
Film TV/Radio Book
Decision
makers
Financers Producer
Director Author
Composer
Board of
Directors
Producer
Publisher
Editor
Author
OperativeCrew
Staff
Crew
StaffAuthor
Motivation (I)
Creativity in media production is paramount Related processes complexity is remarkable The process is characterised by blurred
boundaries between roles and responsibili-ties with significant embedded risks
There is a need for process monitoring and control support at each decision level
Little work has been done in this respect with the exception of YAWL4Film
Motivation (II)
Workflow is often limited to automation, but Workflow is not necessarily automation Artificial Intelligence and Workflow have
been used for:understand and recreate narrativestorytelling poetry conversational agentscontent creation & processing
Motivation (III)
Media industry people are reluctant to use/adopt technology perceived as possibly hampering creativity
The growing complexity and cost of development advocates for monitoring and risk management tools
This dialectic situation resolves with the adoption of minimal technology for the management side and the usage of as much technology as needed for the production side
Hypothesis
The complex “creative media content production process” can be described and formalised in terms of models of interacting processes and constraints that can be integrated within a model-based and data-driven DSS to serve media content creation and production management for non-professional users working within an office automation computing environment.
Research questions (I) Is it possible to provide didactically
sound and informative support throughout the process to non-professionals by exploiting the functionalities and possibilities offered by simple solutions like those available in office automation?
Research questions (II) Describe and model the “creative content
production process” in its entirety? Describe the “creative content production
process” in terms of “workflow”? Describe the “workflow” relations among
“actions”, “actors” and “objects” using a “state-machine-based” approach?
Implement and support a “workflow” by using only simple solutions like those provided by office automation?
Literature survey
Workflow modelling
Modelling and simulation
Decision support systems
Project Management
Adopted framing and supportive theories
System Theory (Von Bertalanffy)
Abstraction Principle (MacLennan)
Activity Theory (Alexei Leont'ev and Sergei Rubinstein)
Threshold Concept (Meyer and Land)
Methodology
Primary data used
Interviews with:Producers (3)Directors (4)Director of Photography (2)Production Manager (1)Author (1)Multimedia / Game Producers (2)Multimedia / Game Developers (1)Graphic creator / CGI Expert (1)
Secondary data used
Interviews, commentaries and make-of footage of selected movies
Information extractedDifficulties encounteredLogic and Method adoptedDirectors’ intention and work-methodCrew / Cast opinions and experience
Data available via the Internet Movie Database (IMDb)
Research Implementation
Observation
Analysis
Modelling
Experimentation
System Development
Evaluation
Act
ivit
y
Conclusions
Time
Modelling activitiesTheoretical part
Basic relations among concepts
Modelling of objects…
Intra actors dependencies
And dynamics induced among actors by the nature of the filmmaking industry
There are interdependencies occurring in the line of management
Adding value in the process
IPR protection and respect
Processes and interrelations
A process as state machine
Processes and interrelations
The process
Development Pre-Production Production Post-Production Marketing Distribution
ISO 5807:1985 - Information processing -- Documentation symbols and conventions for data, program and system flowcharts, program network charts and system resources chartsISO 1028:1973 Information processing -- Flowchart symbolsISO 2636:1973 Information processing -- Conventions for incorporating flowchart symbols in flowchartsISO 10628:1997 Flow diagrams for process plants -- General rules
A change in the timeframe The content production life-cycle is being
compressed adding constraints to its management
Grass-root content production further shortens this timeframe making content available soon after production
Other cycles
The multimedia cycle The game cycle The publishing cycle
They are all relevant for grass-root content production as there are already examples available
An example of the formulas
Formula Purpose
=IF(AND(_expenseDate<>0,
NOT(AND(_expenseAmount<>0,
_accountNumber<>0,
_authorisedBy<>0,
_authotisedOn<>0))),
TRUE, FALSE)
If the _expenseDate has been introduced, but is missing either the
_expenseAmount or the _accountNumber or the
_authorisedBy or the _authotisedOn then the record is
incomplete and therefore highlighted in Orange
For an efficient management it is necessary to keep track of expenses, therefore the records that have missing fields are highlighted in this very basic archive.. Data related to an expense may be easily recovered close to the occurrence of the expense itself and become harder once times goes by.
Monitoring and Management System (Demo)
Practical part
Experimental Production Engagement
Practical part
The centre of the table is rotated left-wise and so does the view
Pre-production
Production
Technical issues encountered Combination of different shooting
techniques implies heavy constraints on set and lighting management
Experimental productions aimed at proving technical advances/innovation are not fully-suitable for narrative purposes
Management of experimental productions strongly deviates from standard practices
Evaluation resultsExperimental part
Heuristic evaluation by Producer Producer & DoP Director & Producer Director & DoP Director Multimedia Producer & Workflow Expert Developer of Multimedia productions Specialist in PR & Marketing
Evaluation Snapshot
System Usability
Av. 72.5
Stdv. 1.86006
Major positive outcomes Thorough modelling effort High-quality model implementation Almost complete coverage Adds value to the understanding of the
intra-process implications and dependencies
Well suited for teaching and explaining process complexity
Major negative outcomes Adopted abstraction and overall
coverage of the process implies loss on specificity in specific areas
The balance between generality and specificity penalises the latter
Producers do not monitor the whole process as describe (they usually ignore distribution)
More suitable for teaching than practice
Conclusions (I)
Through Observation data was gathered
The performed Analysis led to Modelling
Models defined were used to guide the system development
Experimentation and evaluation was then performed
Conclusions (II)
It is possible to describe and model the “creative content production process” in its entirety although not in a very fine granularity
It is possible to describe the “creative content production process” in terms of “workflow” although usability depends on the adopted granularity level
Conclusions (II)
Describing a “workflow” in terms of relations among “actions”, “actors” and “objects” using a “state-machine-based” approach helps identifying risks
It is possible to implement and support a “workflow” by using only simple office automation although this is not a practical solution for end-users, but rather a good complement for teaching and learning
Future work (I)
Some of the received comments need to be implemented
Revision of some of the labels in the diagrams
More thorough explanation of some passages in the flow
Transformation into an application that could allow for better flexibility in the HCI
Future work (II)
Future work (IIl)
Extension of the implementation to the other modelled cycles
Transformation of the overall into a specific training with tutorials and devoted slides/video
Possible split-up of the present single file approach into a multi-file one
Questions?Thank you!
