aDApTA: Adaptive approach to information integration in dynamic environments
Introduction
In supply chain management, there are different organizations and systems generating and consuming information that has semantic and structural heterogeneity. Empirical studies suggest that integrated supply chain information can deliver a better operational and business performance. However, achieving this integration is a hard task due to the differences in semantics and business rules between applications that were not originally expected to collaborate [28], [16]. Logistics management is a discipline within the supply chain that specializes in commercial and humanitarian logistics [13].
The recent disaster caused by Typhoon Haiyan (Yolanda) in the Philippines highlights the complexity of humanitarian logistics. Managers and citizens make decisions under high pressure due to the dynamic of the unpredicted events. The amount, type, and location of needs and donations (e.g., medical supplies, food and clothes) are unpredictable.
The humanitarian logistics process can be divided into four phases: assessment, procurement, warehousing, and transport [29]. In the assessment phase, it is crucial to evaluate the needs of victims and staff so that better support can be provided in the following phases. Such a task has to be accomplished during highly dynamic events, and carrying it out is based on situational awareness and knowledge of the availability of warehouse stock. The assessment can also be supported by applications and technologies that identify and match requests with offers of help on the social media to meet the needs of victims [26], [24]. Furthermore, to manage this complex environment, some research has focused on the operational models [14], [20] and other research has focused on the design of the operational process [29]. However, from an information management perspective, some particular characteristics have emerged that require appropriate approaches.
As Fig. 1 depicts, victims, staff, donors, and warehouse managers generate and present information in different information systems using distinct structures and meanings. For example, the priority regions may be listed on a spreadsheet and the information about shipments and warehouse stock may be stored on a relational database file. In return, citizens, the community, and managers need to consume integrated logistical information to better make decisions. Thus, the heterogeneity of incoming data has to be addressed in order to deliver an integrated view of the situation. Therefore, to handle the dynamic behavior of this scenario, adaptive procedures, where information plays a central role, can be adopted.
The integrated view has to cover the current information about requests and donations as well as previous information about warehouse inventories. Moreover, mechanisms to support complementary information demands, such as geographic coordinates, are necessary. Some information systems, such as Sahana Eden, help put this information together. However, information systems based on relational database models are not suitable for dealing with information with an unpredicted structure as its schema rigidity increases the difficulties of the task of data integration. Although it is possible to configure the schema, this usually results in the loss of explicit semantic due to the differences between the previous and current schema information.
This paper presents aDApTA, an adaptive approach to information integration based on the level of semantic expressivity of data sources. The approach uses graph representation and its implementation on the Web as a strategy for data structure and description adaptation. The architecture uses information available worldwide on the Web to address unexpected demands for complementary information and to support context changes and database content adaptation. To illustrate its usage, the aDApTA was applied to data from a real-life scenario involving humanitarian logistics during the emergency response phase of the Typhoon Haiyan disaster in the Philippines. The experiment illustrates how information integration can be adapted to the semantic level expressivity of data sources.
This paper is organized as follows: the second section discusses issues concerning information management in a complex environment using a real case study scenario; the third section is dedicated to proposing an approach to the adaptive integration of information and the supporting architecture; and the final sections present the approach application and its results, followed by conclusions and a discussion of the future direction of work.
Section snippets
Issues concerning information management in complex environments
In November 2013, the Typhoon Haiyan disaster mobilized many organizations worldwide to aid the victims. Immediately after the disaster, the Sahana Software Foundation1 deployed one of its products, the EDEN (Emergency Development ENvironment for Rapid Deployment Humanitarian Response Management) platform. Additionally, to prioritize the shipment of relief goods, the United Nations Office for the Coordination of Humanitarian Affairs (OCHA) and the Department of Social
Web of Data
Based on graph structure and supported by the W3C, the Web of Data involves using simple principles of the semantic web to interlink and annotate data under an open source licence, reusing vocabularies or schemas [7]. Also known as Linked Open Data (LOD), it is a powerful environment, which can be used, for example, as a worldwide source of information. At the core of the LOD initiatives resides the idea of interconnecting fine-grained information resources, which were not originally
Adaptive approach for integration of information
As explained in Section 2, the adaptation occurs when something is fitted, changed, or modified to suit a different environment. In our scenario, the information representing the current situation awareness, with its unpredicted structure and semantics, should be modified to suit the reference information base, which represents previous knowledge. The same premise is applied to the complementary information needed to fulfill an unpredicted demand for information. In order to obtain an
Application case
The humanitarian logistic of the Philippines disaster has the elements necessary to demonstrate the application of the aDApTA. To conduct an experiment using this approach, a prototype was developed. In this application case study several heterogeneous data sources were used to support decision making in the complex environment, representing previous and current knowledge. Table 1 presents details of the data sources, the approximate number of data items, the data format, and the content used
Conclusions
This research showed that by using widely recognized web standards, exploring the data available on the web, and adapting and extending existing tools it is possible to support adaptive information bases suited to the dynamic behavior of unpredicted events, such as those present in the humanitarian logistics of organizing emergency responses. The aDApTA approach supports the modification of the structure and semantics of the data sources to a reference information base, which enables the
Acknowledgements
This work was partially supported by grants Nos. 308934/2012-1, 407447/2013-0, 484030/2013-2 and 201974/2014-2 (CNPq), and grants E-26/110.492/2012 and E-26/103.076/2011 (FAPERJ), and by the Brazilian Navy.
Kelli de Faria Cordeiro is a Ph.D. candidate on complex information system management, with thesis topic on adaptive information integration to support decision making in complex environment, at the Knowledge Engineering Group (GRECO), at Graduate Program in Informatics (PPGI) – Institute of Mathematics (IM) – Federal University of Rio de Janeiro (UFRJ), Brazil. Thesis defense scheduled for 2015. She is a military Officer at Brazilian Navy (MB), currently working at Systems Analysis Center
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Kelli de Faria Cordeiro is a Ph.D. candidate on complex information system management, with thesis topic on adaptive information integration to support decision making in complex environment, at the Knowledge Engineering Group (GRECO), at Graduate Program in Informatics (PPGI) – Institute of Mathematics (IM) – Federal University of Rio de Janeiro (UFRJ), Brazil. Thesis defense scheduled for 2015. She is a military Officer at Brazilian Navy (MB), currently working at Systems Analysis Center (CASNAV). Ms. Cordeiro received her M.Sc. degree in 2005 at Federal University of Rio de Janeiro. Additionally, she has specialist degree on Analysis, Management and Project of Information Systems and on Data Base System, besides the Data Processing Technologist degree. She has experience in information system development and database system management. Her main research topics are decision support systems, data warehousing, business intelligence, conceptual modeling, linked open data and big data.
Maria Luiza M. Campos is a researcher and professor at the Computer Science Department of the Federal University of Rio de Janeiro. Previously, she was a Data Administrator at the Brazilian Statistical Agency. She received her Ph.D. in Information Systems from the University of East Anglia, Norwich, England, in 1993 and for the period of 2014–2015 she is engaged as a one-year visiting research scholar at the Laboratory for Applied Ontology (ISTC/CNR), in Italy. Her main research interests include data and metadata management, ontology engineering and conceptual modeling, applied to decision support systems and information integration in general. She has led many projects in the domains of bioinformatics, energy, emergencies and government data, funded by Brazilian agencies RNP, FINEP, CNPq and FAPERJ.
Marcos R.S. Borges is Full Professor of Computer Science at the Federal University of Rio de Janeiro, Brazil. He earned his doctorate in Computer Science from the University of East Anglia, UK in 1986. From 1994 to 1996, he was a visiting research scholar and a member of the Object Technology Laboratory at Santa Clara University, California, USA. Dr. Borges has also served as Visiting Professor at University of Paris VI (2001) and at Polytechnic University of Valencia, Spain (2004–2005). He has published over a hundred research papers in international conferences and journals, including Decision Support Systems, Computers in Industry, Information Sciences and Expert Systems with Applications. His research interests include CSCW, Group Decision Support Systems, Resilience Engineering and Collective Knowledge. Since 2004 he has been working in the emergency management domain and has published the latest results on this topic in journals such as Journal of Decision Systems, Reliability Engineering and System Safety, Group Decision and Negotiation, and Journal of Loss Prevention in the Process Industries.