Titulo Estágio
BRISBANE: Bootstrapping Semantic Service Network Analysis Using Social Networks
Área Tecnológica
Sistemas de Informação
Local do Estágio
DEI-FCTUC
Enquadramento
The power of service-based economies is no longer restricted to individual countries but spans networks that structure and underline society. Networks have been playing an increasingly important role in many fields. The Internet, the World Wide Web, social networks, and Linked Data are examples of some of the myriad types of networks that are a part of everyday life of many people. Service networks are another class of networks of emerging interest since worldwide economies are becoming increasingly connected. Nonetheless, while the economies of many countries are becoming service-oriented and accounting for more than 70% of GDP (i.e. Germany, US, and Japan), very few studies on service networks exist.
To date, however, we are still far from being able to analyse their societal and organizational power in ways that can harness their full potential. Understanding when, why, where, and how service networks function best is fundamental for the future generations to avoid many economical problems we are facing. Here, network analysis can help by providing an "x-ray" of service-based economies.
Two challenges for service networks can be identified. On the one hand, the is the need to bootstrap and re-construct service networks using computer understandable and computer processable formats. The information revolution has given birth to new economies structured around massive flows of on-line data, information, and knowledge which make this challenge finally achievable using automated means (e.g. web scrapping and web API). Previous approaches typically collected business data manually from survey firms, teardown reports or on-site analysis (e.g. Dell supply chain analysis [6] and Apple’s iPod networks [7]). These methodologies are clearly not suitable to be applied to study global service networks. On the other hand, methods to analyse networks need to be develop in the same vein as algorithms have been developed to study social networks. This project focuses on the particularly challenging objectives of building and analysing global service networks. It relies on Service Network Analysis (SNA) [2] to study and optimize the provisioning of complex services modeled as Open Semantic Service Networks, a computer-understandable digital structure which represents connected and dependent services.
References
[1] Jorge Cardoso. Modeling service relationships for service networks. In Joao Falcao e Cunha, Mehdi Snene, and Henriqueta Novoa, editors, 4th International Conference on Exploring Service Science (IESS 1.3), pages 114–128, Porto, Portugal, February 2013. Springer, LNBIP.
[2] Jorge Cardoso, John A. Miller, Casey Bowman, Christian Haas, Amit P. Sheth, and Tom W. Miller. Open service network analysis. In 1st International IFIP Working Conference on Value-Driven Social Semantics & Collective Intelligence (VaSCo), 2013.
[3] Jorge Cardoso, Alistair Barros, Norman May, and Uwe Kylau. Towards a unified service description language for the Internet of Services: Requirements and first developments. In IEEE International Conference on Services Computing, Florida, USA, 2010. IEEE Computer Society Press.
[4] Jorge Cardoso, Carlos Pedrinaci, and Pieter De Leenheer. Open semantic service networks: Modeling and analysis. In Joao Falcao e Cunha, Mehdi Snene, and Henriqueta Novoa, editors, 4th International Conference on Exploring Service Science (IESS 1.3), pages 141–154, Porto, Portugal, February 2013. Springer, LNBIP.
[5] Jorge Cardoso, Carlos Pedrinaci, Torsten Leidig, Paulo Rupino, and Pieter De Leenheer. Open semantic service networks. In The International Symposium on Services Science (ISSS 2012), pages 1–15, Leipzig, Germany, 2012.
[6] Roman Kapuscinski, Rachel Q. Zhang, Paul Carbonneau, Robert Moore, and Bill Reeves. Inventory decisions in dell’s supply chain. Interfaces, 34:191–205, June 2004.
[7] Greg Linden, Kenneth Kraemer, and Jason Dedrick. Who captures value in a global innovation network? : the case of apple’s ipod. Commun. ACM, 52:140–144, March 2009.
Objetivo
This project targets to address the two challenges described in the previous section by relying on web information (e.g. LinkedIn, Service Marketplaces, ServiceMagic.com, companies web sites, etc.) to reconstruct service networks and by adapting algorithms mainly from the field of social networks to better understand service networks.
Objective 1. A service network can be constructed and represented using OSSN by accessing, retrieving and combining information from service and relationship models. Service and relationship models can be acquired using manual and automated methods. Automated methods, e.g. by using Web scraping and wrappers, can crawl unstructured service sources from the Web, such as corporate Web sites and marketplaces (e.g. LinkedIn, Wikipedia, ServiceMagic.com, Sears’ ServiceLive.com, ServiceAlley.com, and Redbeacon.com), and create models on-the-fly. Relationships can also be identified by inferring or deriving similarities between service providers, service models and service marketplaces. For example, let us consider the following rule. Infer implicit service relationships if: 1) a set of services is provided by the same organizational department, 2) if two services have the same goal or 3) if they target the same customer profile. The use of industry segments and supply chains to relate services is also an approach to explore. Once service networks are reconstructed they are ready to be analysed.
Objective 2. This project resorts to Service Network Analysis to offers a systematic and scientific analysis of service networks. SNA views service systems and service relationships in terms of network theory, consisting of nodes (representing individual services within the network) and ties (which represent relationships between services such as roles, level of integration, involvement strength, and cause-effect bindings [1]). Here, we will adapt algorithms from social network analysis. For example, we will use closeness to determines how close services are to one another in a network; centrality to provide an indication of the ‘power’ of services based on their overall connection with other services; and structural equivalence to examine which services have a common set of relationships to other services.
Both objectives will be materialized with a software tool which will crawl the web, re-construct service networks, and calculate metrics with will provide valuable information to better understand how service-oriented economies are organizing themselves.
Plano de Trabalhos - Semestre 1
(a) Literature review (Sept-Nov 2013). Conduct a literature review of open service networks, service relationships, and social network analysis. Read the papers published by the ISG group, namely [2, 3, 5, 1, 4]. Look into the Linked USDL (linked-usdl.org) and OSSR specifications (available at genessiz.org) for modelling services and relationships, respectively.
(b) Web data sources (Oct 2013). Analyse web sites, such as Focus.com, LinkedIn, Wikipedia, ServiceMagic.com, Sears’ ServiceLive.com, ServiceAlley.com, and Redbeacon.com, to find valuable sources which contain the required information to re-construct open service networks. Create a simplified model of a service network using pen-and-paper.
(c) Use Case (Nov-Dec 2013). Identify a solid business use case definition which will show the value of service network analysis and that will drive the research project until completion. Create a wiki page and logo for the project.
(d) Architecture and tools (Nov-Dec 2013). Design the first draft of the application to developed to re-construct and analyse service networks. Identify the tools and the software needed for the project. For example, scrappers, parsers, and network and visualization packages.
(e) Mid-term report (Dec-Jan 2013/4). Write and defend the mid-term report.
Plano de Trabalhos - Semestre 2
(a) First prototype (Feb-Mar 2014). Generate the first demo version of the application which re-constructs service networks, applies simple algorithms from the field of social networking analysis, and visualizes the results. Show it can be effectively used with the business use case definition (created in step 1.c)). The prototype will help defining additional functional requirements and will also allow receiving feedback from other members of the group.
(b) Programming (Mar-May 2014). Program the components, visualization modules and SNA application. Define a second version of the business use case to better illustrate the benefits of service network analysis. Definition and execution of the acceptance tests. Receive and address feedback.
(c) Algorithms (April 2013). Adapt existing algorithms from the field of social networking to service networks. Examples of algorithms include closeness, centrality, structural equivalence, cohesion, and radiality.
(d) Documentation (Feb-Jun 2014). Integration and revision of the documentation produced in each phase of the project into the final documentation which describes the work carried out technically and from a business perspective. Update weekly a wiki with the project information. Write the final version of the business use case.
(e) Thesis (Jun 2014). Write the final version of the master thesis. Based on the thesis, write a shorter document (a paper) to submit to a conference.
Condições
This work will be carried out at DEI/Universidade de Coimbra within the Information System Group (ISG). A suitable space will be made available to students. Meetings will be held regularly (every week) with several students working on services networks, service systems, and service relationships.
Orientador
Jorge Cardoso/Paulo Rupino
jcardoso@dei.uc.pt 📩