Formal framework for semantic interoperability in Supply Chain networks

Editor's Notes

• #3: Outline of the presentation Research questions 1,2 – “Problemation (problem + motivation) puzzles” 3,4 – Methodology puzzles 5,6 – Implementation puzzles
• #6: Metaphor of multitasking
• #7: Complexity and volume of supply relationships , high frequency of transactions between parties. In Supplier Relationship Management, 80% is human effort and 20% information technology. There is a tendency to reduce number of suppliers because of possible relation cost reductions . Costs of SCM up to 8-10% of sales.
• #8: New organizational forms. Although significant innovation is made in this topic, the essence of the supplier-customer relationships remains the same as in what is considered as traditional supply chains. The economic phenomena, such as globalization, outsourcing, increased demand for customization and specialization do not change this essence. This is the reason why the title of this thesis still refers to the supply chains, and not to the new terms of Virtual Enterprise or Collaborative Networked Organization.
• #10: First, enterprises in a supply chain need to speak the same language.
• #12: Source connects to supplier Deliver connects to customer Not all companies have make We can model as far up or down the supply chain as we view important (not limited to two tiers) Customers and / or suppliers can be internal or external Plan (Processes that balance aggregate demand and supply to develop a course of action which best meets sourcing, production and delivery requirements). Balance resources with requirements, Establish/communicate plans for the whole supply chain Source (Processes that procure goods and services to meet planned or actual demand). Schedule deliveries (receive, verify, transfer) Make (Processes that transform product to a finished state to meet planned or actual demand). Schedule production Deliver (Processes that provide finished goods and services to meet planned or actual demand, typically including order management, transportation management, and distribution management). Warehouse management from receiving and picking product to load and ship product. Return (Processes associated with returning or receiving returned products). Manage Return business rules SCOR describes processes not functions. In other words, the Model focuses on the activity involved, not the person or organizational element that performs the activity.
• #14: Because SCOR spans boundaries of the enterprises.
• #16: Each of the systems speaks its own language. So, we need a common dictionary, which can be used to reconcile the languages of systems and SCOR. In other words, we need to make implicit SCOR – explicit.
• #19: English translation of Welsh: “I am not in the office at the moment. Please send any work to be translated”
• #23: Networking is defined as a simple information exchange for some benefit. Coordinated networking implies aligning activities of two parties . Cooperation also involves resource sharing for achievement of the compatible goals. Collaboration means that common goal is setup .
• #25: Outline of the presentation Research questions 1,2 – “Problemation (problem + motivation) puzzles” 3,4 – Methodology puzzles 5,6 – Implementation puzzles
• #27: Supply Chain Management becomes more transparent and decisions are made upon the real conditions. ZAMENI OVU SLIKU
• #28: Systems are insensitive to the not-so-obvious and non-functional contexts, such as communication culture, etc. You have to be explicit when communicating with a system. Teaser: What do we know about SCOR ?
• #29: Common misconception: differences between semantic interoperability an semantically facilitated interoperability.
• #30: A sender's system S is _semantically operable_ with a receiver's system R if and only if the follow condition holds for any data p that is transmitted from S to R: For every statement q that is implied by p on the system S, there is a statement q' on the system R that (1) is implied by p on the system R, and (2) is logically equivalent to q. the receiver must at least be able to derive a logically equivalent implication for every implication of the sender's system.
• #31: Adding contexts improves expressiveness of a framework if there exist systems S 1 and S 2 , driven by the ontologies O 1 and O 2 , and if there exist alignment between these ontologies O 1 ≡O 2 , the competence of O 1 will be improved and S 1 will be enabled to make more qualified conclusions about its domain of interest
• #35: Can you consider all this knowledge about SCOR explicit ? Even if it is explicit, is it represented in such a way so it can be computed by the systems.
• #37: This is why we developed SCOR-OWL and SCOR-Full models. First we represent the implicit knowledge. Now, it can be computed.
• #41: D escribes an executive role and entails all entities which perform individual or set of tasks within the supply network, classified with the concepts of equipment, organization, supply chain, supply chain network, facility and information system. A gents do not have explicit definition of functions. Functionality is defined as a property of a course, performed by an agent. Hence, agents are functional in a context of a course they execute. The basic formal consequence of the assumptions above is that agents do not exist if they do not perform some course of doable things.
• #42: C lassifies prescriptions or descriptions (independent of the time dimension) of ordered sets of tasks . C ourse generalizes “doable” or “done” things with common properties of environment (corresponding to the enabling and resulting states, constraints, requirements, etc.), quality (cost, duration, capacity, performance, etc.) and organization (agent and business function). The second necessary condition for a Course is that it has some impact to the environment (a goal, objective or state) and/or it receives some feedback from the environment or it considers some of its features (such as constraint, requirement, rule or assumption). In other words, the course must have its own setting. Subproperties of has-setting are has-postcondition and has-precondition.
• #43: Setting concept provides the description of environment of a course. It aggregates semantically defined features of the context in which course take place – its motivation, drivers and constraints. T hey must correspond to some quantifiable notions which describe the specific values or states. Otherwise, they would be only of abstract nature. So, the necessary condition for a setting is to be realized by some configured item (to be described later) .
• #44: Quality is the general attribute of a course, agent or function which can be perceived or measured . Like in the case of Setting concepts, those attributes are only semantically described abstract categories. Hence, they need to be mapped to the actual specific values or states. The necessary condition for the instances of the Quality concept is that they need to be associated to at least one instance of the “configured-item” concept .
• #45: Function concept entails elements of the horizontal business organization, such as stocking, shipping, control, sales, replenishment, return, delivery, disposition, maintenance, production, etc. Although it may have some qualities associated, the concept of function is an abstract concept, which basic purpose is to semantically define the context of the course.
• #46: Configured items model state semantics of the resource – physical or information item . Information items are the atomic concepts which can be semantically defined when mapped to other enterprise ontologies . For the expressive process model, it is crucial to define how resources are communicated among activities and their corresponding actors . This is why communicated item concept is introduced. It aggregates specific concepts of Notice (or its child concept - Signal), Request, Response and Receipt .
• #47: Configured items are characterized by one or multiple states of information or a physical item, assigned numerical (textual or date) value or realized by another configured item . Available states are identified in the analysis of SCOR model and include 25 possible attributes of the configured item, which can be associated to different information and physical items. Some of the examples of the states are: Adjusted, Approved, Authorized, Completed, Delivered, Installed, Loaded, Planned, Released, Returned, Updated, Validated . I nformation items become configured when at least one of their properties is defined or configured, whether this property can be described by numerical, textual or date information; or the state. Sometimes, it is not possible to “configure” the information item with a simple object, such as data type or state. Hence, information item can also be “realized” with a configured item, as a complex property.
• #51: SCOR-MAP is a central ontology. It imports (blue arrows) domain ontologies, implicit SCOR model represented in OWL (SCOR-KOS OWL), SCOR’s semantic enrichment (SCOR-FULL OWL) and all local ontologies. SCOR-MAP stores the SWRL rules which are used to represent correspondences between all these models. Focus of this paper is on what is inside purple boxes.
• #52: SCOR-MAP is a central ontology. It imports (blue arrows) domain ontologies, implicit SCOR model represented in OWL (SCOR-KOS OWL), SCOR’s semantic enrichment (SCOR-FULL OWL) and all local ontologies. SCOR-MAP stores the SWRL rules which are used to represent correspondences between all these models. Focus of this paper is on what is inside purple boxes.
• #53: Outline of the presentation Research questions 1,2 – “Problemation (problem + motivation) puzzles” 3,4 – Methodology puzzles 5,6 – Implementation puzzles
• #58: SCOR-MAP is a central ontology. It imports (blue arrows) domain ontologies, implicit SCOR model represented in OWL (SCOR-KOS OWL), SCOR’s semantic enrichment (SCOR-FULL OWL) and all local ontologies. SCOR-MAP stores the SWRL rules which are used to represent correspondences between all these models. Focus of this paper is on what is inside purple boxes.
• #59: Outline of the presentation Research questions 1,2 – “Problemation (problem + motivation) puzzles” 3,4 – Methodology puzzles 5,6 – Implementation puzzles
• #65: Typically, a photo like that can be associated to infinite pleasure and joy of flying, time is frozen to enjoy the perfect view that only you could enjoy, blood is quickly going through your vens. However, there is also a pessimist perspective: once he lands, no way that this guy will not suffer a serious and complicated bone fracture!
• #82: When all local languages are translated to universal domain knowledge, this domain knowledge is then used as a facilitator for the communication. The pre-condition for implementing the above scenario is to have all local languages and domain knowledge - formally described, by using the same formalism. When same formalism is used for all those formal descriptions, it is also possible to define correspondences between the notions of the local languages and domain knowledge. Now, domain knowledge can be considered as advanced dictionary, which is used to formally define meanings of all terms of the exchanged messages. The meaning is formally defined because it is intended to be computable or inferred by the different agents for the different purposes. This formal definition aims at bringing closer the symbols, used to formally describe a particular object, to its typical mental representation. With regard to this, the logical positivists strongly argued that the meaning is nothing more or less than the truth conditions it involves. Here, the meaning is explained by using the references to the actual existing (possibly also logically explained) things in the world. The process of the representation of such meanings is called intensional conceptualization. In linguistics, meaning is what the sender expresses, communicates or conveys in its message to the receiver (or observer) and what the receiver infers from the current context (Akmajian et al, 1995). The diversity of the contexts in which the same message is inferred may easily lead to different interpretations of the meaning of this message. The pragmatic meaning considers the contexts that affect the meaning and it distinguishes two of their primary forms: linguistic and situational. The linguistic context refers to how meaning is understood, without relying on intent and assumptions. The situational context refers to non-linguistic factors which affect the meaning of the message. The linguistic context of the meanings depends on the expressivity of the vocabulary used to describe those meanings and a level of abstraction applied in its development. Both factors significantly influence the capability of the receiver to understand the transmitted messages. The expressivity of vocabulary basically refers to the number and diversity of the concepts (and their properties) used to describe one domain of knowledge. The higher levels of expressivity are important for the cases of very specific communication about highly focused issues of the domain. In most cases, it is very likely that the outside listener will not understand the communication between two domain experts. The level of abstraction has more profound impact. The human reasoning of an unknown term is done by attempting to refer to the known related concepts (or truth conditions). When this is not enough to classify a term, humans reduce or eliminate some truth conditions in attempt to infer a more general, more abstract, known term, which may help in understanding the initial one. Sometimes, even more truth conditions are added so the unknown term is specialized to a known one. Hence, existence of the different levels of abstraction of similar terms or groups of terms may certainly help in understanding the domain knowledge. Typically, higher level of abstraction used in development of one vocabulary, implies lesser expressivity and vice-versa. However, the advantages of both factors can be combined by developing different vocabularies whose concepts are referenced to each other. Hence, highly abstract, less expressive knowledge may be related to a very specific one. If we consider the above-mentioned communication between two experts on the focused domain issues, it is clear that the references to the known generalizations of the specific terms would certainly help the outside listener to understand this communication.
• #83: When all local languages are translated to universal domain knowledge, this domain knowledge is then used as a facilitator for the communication. The pre-condition for implementing the above scenario is to have all local languages and domain knowledge - formally described, by using the same formalism. When same formalism is used for all those formal descriptions, it is also possible to define correspondences between the notions of the local languages and domain knowledge. Now, domain knowledge can be considered as advanced dictionary, which is used to formally define meanings of all terms of the exchanged messages. The meaning is formally defined because it is intended to be computable or inferred by the different agents for the different purposes. This formal definition aims at bringing closer the symbols, used to formally describe a particular object, to its typical mental representation. With regard to this, the logical positivists strongly argued that the meaning is nothing more or less than the truth conditions it involves. Here, the meaning is explained by using the references to the actual existing (possibly also logically explained) things in the world. The process of the representation of such meanings is called intensional conceptualization. In linguistics, meaning is what the sender expresses, communicates or conveys in its message to the receiver (or observer) and what the receiver infers from the current context (Akmajian et al, 1995). The diversity of the contexts in which the same message is inferred may easily lead to different interpretations of the meaning of this message. The pragmatic meaning considers the contexts that affect the meaning and it distinguishes two of their primary forms: linguistic and situational. The linguistic context refers to how meaning is understood, without relying on intent and assumptions. The situational context refers to non-linguistic factors which affect the meaning of the message. The linguistic context of the meanings depends on the expressivity of the vocabulary used to describe those meanings and a level of abstraction applied in its development. Both factors significantly influence the capability of the receiver to understand the transmitted messages. The expressivity of vocabulary basically refers to the number and diversity of the concepts (and their properties) used to describe one domain of knowledge. The higher levels of expressivity are important for the cases of very specific communication about highly focused issues of the domain. In most cases, it is very likely that the outside listener will not understand the communication between two domain experts. The level of abstraction has more profound impact. The human reasoning of an unknown term is done by attempting to refer to the known related concepts (or truth conditions). When this is not enough to classify a term, humans reduce or eliminate some truth conditions in attempt to infer a more general, more abstract, known term, which may help in understanding the initial one. Sometimes, even more truth conditions are added so the unknown term is specialized to a known one. Hence, existence of the different levels of abstraction of similar terms or groups of terms may certainly help in understanding the domain knowledge. Typically, higher level of abstraction used in development of one vocabulary, implies lesser expressivity and vice-versa. However, the advantages of both factors can be combined by developing different vocabularies whose concepts are referenced to each other. Hence, highly abstract, less expressive knowledge may be related to a very specific one. If we consider the above-mentioned communication between two experts on the focused domain issues, it is clear that the references to the known generalizations of the specific terms would certainly help the outside listener to understand this communication.