Semantically-aware data discovery and placement in collaborative computing environments

As the size of scientific datasets and the demand for interdisciplinary collaboration grow in modern science, it becomes imperative that better ways of discovering and placing datasets generated across multiple disciplines be developed to facilitate interdisciplinary scientific research. For discovering relevant data out of large-scale interdisciplinary datasets. The development and integration of cross-domain metadata is critical as metadata serves as the key guideline for organizing data. To develop and integrate cross-domain metadata management systems in interdisciplinary collaborative computing environment, three key issues need to be addressed: the development of a cross-domain metadata schema; the implementation of a metadata management system based on this schema; the integration of the metadata system into existing distributed computing infrastructure. Current research in metadata management in distributed computing environment largely focuses on relatively simple schema that lacks the underlying descriptive power to adequately address semantic heterogeneity often found in interdisciplinary science. And current work does not take adequate consideration the issue of scalability in large-scale data management. Another key issue in data management is data placement, due to the increasing size of scientific datasets, the overhead incurred as a result of transferring data among different nodes also grow into a significant inhibiting factor affecting overall performance. Currently, few data placement strategies take into consideration semantic information concerning data content. In this dissertation, we propose a cross-domain metadata system in a collaborative distributed computing environment and identify and evaluate key factors and processes involved in a successful cross-domain metadata system with the goal of facilitating data discovery in collaborative environments. This will allow researchers/users to conduct interdisciplinary science in the context of large-scale datasets that will make it easier to access interdisciplinary datasets, reduce barrier to collaboration, reduce cost of future development of similar systems. We also investigate data placement strategies that involve semantic information about the hardware and network environment as well as domain information in the form of semantic metadata so that semantic locality could be utilized in data placement, that could potentially reduce overhead for accessing large-scale interdisciplinary datasets

An Information Management Conceptual Approach for the Strategies Alignment Collaborative Process

[EN] This paper proposes an information management approach to deal with the strategies alignment collaborative process. Much attention has been given to the information management in collaborative networks (CNs), resulting in a wide variety of information management approaches and frameworks. The treatment, estimation, and collection of data are key issues that still need to be addressed, due to the complexity associated with the information exchange and the need to build trust relationships within the CN. In order to address this literature gap, this paper presents an approach to manage information in the specific collaborative process of strategies alignment. The approach is composed of a methodology, that enables to identify the roles participating in the application of the collaborative process, select the collaborative application context, determine the level of collaboration to be applied, and estimate and gather the data required to feed the strategies alignment process. The proposed information management approach bridges the conceptual model of strategies alignment process, with its application in real-world CNs.This work has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 872548 "Fostering DIHs for Embedding Interoperability in Cyber-Physical Systems of European SMEs" (DIH4CPS) (http://dih4cps.eu/).Andres, B.; Poler, R. (2020). An Information Management Conceptual Approach for the Strategies Alignment Collaborative Process. Sustainability. 12(10):1-22. https://doi.org/10.3390/su12103959S1221210Camarinha-Matos, L. M., & Afsarmanesh, H. (2005). Collaborative networks: a new scientific discipline. Journal of Intelligent Manufacturing, 16(4-5), 439-452. doi:10.1007/s10845-005-1656-3Cheikhrouhou, N., Pouly, M., & Madinabeitia, G. (2013). Trust categories and their impacts on information exchange processes in vertical collaborative networked organisations. International Journal of Computer Integrated Manufacturing, 26(1-2), 87-100. doi:10.1080/0951192x.2012.681913Andres, B., & Poler, R. (2016). A decision support system for the collaborative selection of strategies in enterprise networks. Decision Support Systems, 91, 113-123. doi:10.1016/j.dss.2016.08.005Blome, C., Paulraj, A., & Schuetz, K. (2014). Supply chain collaboration and sustainability: a profile deviation analysis. International Journal of Operations & Production Management, 34(5), 639-663. doi:10.1108/ijopm-11-2012-0515Soosay, C. A., & Hyland, P. (2015). A decade of supply chain collaboration and directions for future research. Supply Chain Management: An International Journal, 20(6), 613-630. doi:10.1108/scm-06-2015-0217Chen, L., Zhao, X., Tang, O., Price, L., Zhang, S., & Zhu, W. (2017). Supply chain collaboration for sustainability: A literature review and future research agenda. International Journal of Production Economics, 194, 73-87. doi:10.1016/j.ijpe.2017.04.005Transforming Our World: The 2030 Agenda for Sustainable Development https://sustainabledevelopment.un.org/post2015/transformingourworldFonseca, L. M., Domingues, J. P., & Dima, A. M. (2020). Mapping the Sustainable Development Goals Relationships. Sustainability, 12(8), 3359. doi:10.3390/su12083359Horan, D. (2019). A New Approach to Partnerships for SDG Transformations. Sustainability, 11(18), 4947. doi:10.3390/su11184947Andres, B., & Marcucci, G. (2020). A Strategies Alignment Approach to Manage Disruptive Events in Collaborative Networks. Sustainability, 12(7), 2641. doi:10.3390/su12072641Andres, B., & Blanes, V. J. (2020). A Negotiation Approach to Support the Strategies Alignment Process in Collaborative Networks. Sustainability, 12(7), 2766. doi:10.3390/su12072766Provan, K. G., & Kenis, P. (2007). Modes of Network Governance: Structure, Management, and Effectiveness. Journal of Public Administration Research and Theory, 18(2), 229-252. doi:10.1093/jopart/mum015Pilbeam, C., Alvarez, G., & Wilson, H. (2012). The governance of supply networks: a systematic literature review. Supply Chain Management: An International Journal, 17(4), 358-376. doi:10.1108/13598541211246512Alemany, M. M. E., Alarcón, F., Lario, F.-C., & Boj, J. J. (2011). An application to support the temporal and spatial distributed decision-making process in supply chain collaborative planning. Computers in Industry, 62(5), 519-540. doi:10.1016/j.compind.2011.02.002Schneeweiss, C. (2003). Distributed decision making in supply chain management. International Journal of Production Economics, 84(1), 71-83. doi:10.1016/s0925-5273(02)00381-xAlemany, M. M. E., Boj, J. J., Mula, J., & Lario, F.-C. (2009). Mathematical programming model for centralised master planning in ceramic tile supply chains. International Journal of Production Research, 48(17), 5053-5074. doi:10.1080/00207540903055701Saiz, J. J. A., Rodriguez, R. R., Bas, A. O., & Verdecho, M. J. (2010). An information architecture for a performance management framework by collaborating SMEs. Computers in Industry, 61(7), 676-685. doi:10.1016/j.compind.2010.03.012Andrés, B., & Poler, R. (2013). Relevant problems in collaborative processes of non-hierarchical manufacturing networks. Journal of Industrial Engineering and Management, 6(3). doi:10.3926/jiem.552Mula, J., Poler, R., & Garcia, J. P. (2006). MRP with flexible constraints: A fuzzy mathematical programming approach. Fuzzy Sets and Systems, 157(1), 74-97. doi:10.1016/j.fss.2005.05.045Campuzano, F., Mula, J., & Peidro, D. (2010). Fuzzy estimations and system dynamics for improving supply chains. Fuzzy Sets and Systems, 161(11), 1530-1542. doi:10.1016/j.fss.2009.12.002Mula, J., Peidro, D., & Poler, R. (2014). Optimization Models for Supply Chain Production Planning Under Fuzziness. Studies in Fuzziness and Soft Computing, 397-422. doi:10.1007/978-3-642-53939-8_17Da Piedade Francisco, R., Azevedo, A., & Almeida, A. (2012). Alignment prediction in collaborative networks. Journal of Manufacturing Technology Management, 23(8), 1038-1056. doi:10.1108/17410381211276862Savastano, M., Amendola, C., Bellini, F., & D’Ascenzo, F. (2019). Contextual Impacts on Industrial Processes Brought by the Digital Transformation of Manufacturing: A Systematic Review. Sustainability, 11(3), 891. doi:10.3390/su1103089

Managing collaborative processes for natural resources

A new style of natural resource decision-making is under development in the United States that has evolved from the approach that dominated the last hundred years. The historical implementation of natural resource policy has been characterized as top down where a highly compartmentalized bureaucratic structure dominated the management of natural resources through policies focused on outputs and guided by scientific management. The historical implementation of natural resource policy frames the resolution of conflicting goals as mutually exclusive, which has led to fierce competition for the power necessary for one goal to dominate over another. Collaboration and ecosystem management policy approaches were largely born out of the recognition that the historical implementation of natural resource policy has been ineffective at resolving conflict due to the narrow approaches available in the courts and administrative appeals. Collaborative policy processes have been characterized as bottom up, rather than top down, recognizing that no one group is the dominant decision maker in the current reality of a shared power world. Collaborative policy processes are comprehensive in addressing multiple natural resource values and interests, have socially defined goals and objectives, include more voluntary than regulatory policies, and rely on integrated holistic knowledge. Given the monumental differences between the historical implementation of natural resource policy and the current shift to collaborative policy processes, this change is often referred to as a paradigm shift. The goal of this research was to more fully understand this new style of decision making, collaboration, through examining the growing literature base and case analysis of participants\u27 experiences in collaboration. Collaborative process principles identified in the literature coupled with participant experiences of those principles in collaborative processes provided lessons learned to help inform our society on how to make the transition from our past adversarial, split the stakes processes and our future with collaborative processes. The collaborative process principles identified in the literature focused on who was involved and how (process) people were involved in two specific areas of collaboration: how decisions are negotiated, and data and information management. Eleven principles to guide negotiations in collaborative policy processes were identified. Six principles to guide data and information management in collaborative policy processes were identified. Together these principles comprise a template to guide how an effective collaborative process needed to be managed, and provided a lens through which to analyze the cases. This template was compared to real life participant experiences in collaboration and several lessons learned were gleaned from the combination of theory and empirical evidence. Perhaps the most important lesson learned in this research was the importance of process management. A rigorous application of the principles of the collaborative process was important to provide procedural due process and a legitimate process that was perceived as fair and just to all interests involved. Collaboration required the balancing of tensions of several inherent paradoxes, and to do this effectively required process management of the collaborative principles. Involvement shaped real life collaboration, and while participants\u27 perceived inclusive involvement as beneficial, it was no panacea for the complexities of involving the variety of interests engaged in natural resource issues. In real life, a productive role was the true measure of involvement and while this was difficult there were ways, such as the structured use of subgroups, to balance the tensions between inclusive involvement and role efficacy. The involvement of scientists in collaboration must be done carefully because the credibility of scientists in the cases analyzed in this research was compromised. Collaboration required considerable time and skills, but as we continue to practice collaboration the time it takes may be reduced through the improved skills and relationships of participants. Relationships were improved and trust was built between very divided interests in the majority of the cases analyzed in this research and continued experimentation with collaboration may help to build a foundation that will make future collaborative efforts even more positive and successful. Facilitation can also help participants get through the unfamiliar process of collaboration and help develop the people skills necessary for effective collaborations. The incentive to participate in collaboration appeared to be largely born from the conflicts created by the historical implementation of natural resource policy. Collaboration may not be so much of a paradigm shift as it is an evolution since it often depends upon a government role of fostering sustainable natural resource use by establishing standards and targets that result in being the incentive to collaborate. Even though this government role provided the biggest incentive to participate in collaboration, participants in all the cases analyzed in this research recognized the reality of a shared power world. Participants recognized that there were many legitimate and powerful interests that needed to be involved in order to achieve a successful collaboration

An Integrative Information Aqueduct to Close the Gaps between Satellite Observation of Water Cycle and Local Sustainable Management of Water Resources

[EN] The past decades have seen rapid advancements in space-based monitoring of essential water cycle variables, providing products related to precipitation, evapotranspiration, and soil moisture, often at tens of kilometer scales. Whilst these data effectively characterize water cycle variability at regional to global scales, they are less suitable for sustainable management of local water resources, which needs detailed information to represent the spatial heterogeneity of soil and vegetation. The following questions are critical to effectively exploit information from remotely sensed and in situ Earth observations (EOs): How to downscale the global water cycle products to the local scale using multiple sources and scales of EO data? How to explore and apply the downscaled information at the management level for a better understanding of soil-water-vegetation-energy processes? How can such fine-scale information be used to improve the management of soil and water resources? An integrative information flow (i.e., iAqueduct theoretical framework) is developed to close the gaps between satellite water cycle products and local information necessary for sustainable management of water resources. The integrated iAqueduct framework aims to address the abovementioned scientific questions by combining medium-resolution (10 m-1 km) Copernicus satellite data with high-resolution (cm) unmanned aerial system (UAS) data, in situ observations, analytical- and physical-based models, as well as big-data analytics with machine learning algorithms. This paper provides a general overview of the iAqueduct theoretical framework and introduces some preliminary results.The authors would like to thank the European Commission and Netherlands Organisation for Scientific Research (NWO) for funding, in the frame of the collaborative international consortium (iAqueduct) financed under the 2018 Joint call of the Water Works 2017 ERA-NET Cofund. This ERA-NET is an integral part of the activities developed by the Water JPI (Project number: ENWWW.2018.5); the EC and the Swedish Research Council for Sustainable Development (FORMAS, under grant 2018-02787); Contributions of B. Szabo was supported by the Janos Bolyai Research Scholarship of the Hungarian Academy of Sciences (grant no. BO/00088/18/4).Su, Z.; Zeng, Y.; Romano, N.; Manfreda, S.; Francés, F.; Ben Dor, E.; Szabó, B.... (2020). An Integrative Information Aqueduct to Close the Gaps between Satellite Observation of Water Cycle and Local Sustainable Management of Water Resources. Water. 12(5):1-36. https://doi.org/10.3390/w12051495S13612

A Holistic Algorithm for Materials Requirement Planning in Collaborative Networks

[EN] Collaboration has increasingly been considered a key topic within the small and medium-sized enterprises, allowing dealing with the intense competitiveness of today¿s globalised markets. The European H2020 Cloud Collaborative Manufacturing Networks Project proposes mechanisms to encourage collaboration among enterprises, through the computation of collaborative plans. Particularly, this paper focuses on the proposal of a holistic algorithm to deal with the automated and collaborative calculation of the Materials Requirement Plan. The proposed algorithm is validated in a collaborative network belonging to the automotive industry.The research leading to these results is in the frame of the “Cloud Collaborative Manufacturing Networks” (C2NET) project, which has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 636909.Andres, B.; Poler, R.; Sanchis, R. (2017). A Holistic Algorithm for Materials Requirement Planning in Collaborative Networks. IFIP Advances in Information and Communication Technology. 560:41-50. https://doi.org/10.1007/978-3-319-65151-4_4S4150560CORDIS Europa: Factories of the Future. H2020-EU.2.1.5.1. - Technologies for Factories of the Future (2014)H2020 Project C2NET (2015). http://cordis.europa.eu/project/rcn/193440_en.htmlAndres, B., Sanchis, R., Poler, R.: A cloud platform to support collaboration in supply networks. Int. J. Prod. Manag. Eng. 4(1), 5–13 (2016)Andres, B., Sanchis, R., Lamothe, J., Saari, L., Hauser, F.: Integrated production-distribution planning optimization models: a review in collaborative networks context. Int. J. Prod. Manag. Eng. 5(1), 31–38 (2017)Camarinha-Matos, L.M., Afsarmanesh, H.: Collaborative networks: a new scientific discipline. J. Intell. Manuf. 16(4–5), 439–452 (2005)Andres, B., Poler, R.: Models, guidelines and tools for the integration of collaborative processes in non-hierarchical manufacturing networks: a review. Int. J. Comput. Integr. Manuf. 2(29), 166–201 (2016)Sanchis, R., Poler, R., Lario, F.C.: Identification and analysis of Disruptions: the first step to understand and measure Enterprise Resilience. In: International Conference on Industrial Engineering and Engineering Management, pp. 424–431 (2012)Andres, B., Saari, L., Lauras, M., Eizaguirre, F.: Optimization algorithms for collaborative manufacturing and logistics processes. In: Zelm, M., Doumeingts, G., Mendonça, J.P. (eds.) Enterprise Interoperability in the Digitized and Netwroked Factory of the Future, iSTE 2016, pp. 167–173 (2016)Orbegozo, A., Andres, B., Mula, J., Lauras, M., Monteiro, C., Malheiro, M.: An overview of optimization models for integrated replenishment and production planning decisions. In: Building Bridges Between Researchers and Practitioners. Book of Abstracts of the International Joint Conference CIO-ICIEOM-IISE-AIM (IJC 2016), p. 68 (2016

“We can’t do it on our own!”—Integrating stakeholder and scientific knowledge of future flood risk to inform climate change adaptation planning in a coastal region

Decision-makers face a particular challenge in planning for climate adaptation. The complexity of climate change's likely impacts, such as increased flooding, has widened the scope of information necessary to take action. This is particularly the case in valuable low-lying coastal regions, which host many competing interests, and where there is a growing need to draw from varied fields in the risk-based management of flooding. The rising scrutiny over science's ability to match expectations of policy actors has called for the integration of stakeholder and scientific knowledge domains. Focusing on the Broads — the United Kingdom's largest protected wetland — this study looked to assess future flood risk and consider potential adaptation responses in a collaborative approach. Interviews and surveys with local stakeholders accompanied the development of a hydraulic model in an iterative participatory design, centred on a scientist-stakeholder workshop. Knowledge and perspectives were shared on processes driving risk in the Broads, as well as on the implications of adaptation measures, allowing for their prioritisation. The research outcomes highlight not only the challenges that scientist-stakeholder integrated assessments of future flood risk face, but also their potential to lead to the production of useful information for decision-making

Development of OCIPSE Learning Model to Increase Students' Scientific Creativity in Natural Science Learning

This Research & Development (R & D) has the main goal to develop and produce OCIPSE learning model. The main product of this research is the OCIPSE learning model with five phases, they are 1) Orient and organize the students for study; 2) Collaborative Investigation; 3) Presentation and discussion; 4) Strengthening of scientific creativity; and 5) Evaluate and provide recognition. The OCIPSE learning model' quality data is obtained through an expert validation process by using the OCIPSE learning model Qualification Assessment Instrument. The OCIPSE learning model quality analysis used an average validity score, single measures ICC, and Cronbach's coefficient alpha. The result of the research shows OCIPSE learning model with average content validity (3.69), construct validity (3.69), with the validity of each aspect statistically in (rα = .92) and reliability in (α = .87).  The results of this study indicate that the developed OCIPSE learning model was declared qualified by experts. The research implication is that a qualified OCIPSE learning model can be used to enhance the scientific creativity of junior high school students in natural science learning.&nbsp

New Approaches to Participation in Fisheries Research

This study was commissioned by FAO (Food and Agriculture Organisation of the United Nations) and SIFAR (Support Unit for International Fisheries and Aquatic Research) on the recommendation of the Advisory Committee on Fisheries Research (ACFR). It is concerned with research in the context of fisheries development.The ACFR acknowledges that the fisheries sector is faced with serious social and environmental problems and that current approaches to research have their limitations. It is recognised that participatory approaches and methods potentially have a greater role to play in fisheries research. This study aims to explore that potential and to suggest how we might move forward. The main focus of the report is on experiences in developing countries because this is where much of the innovative work in participation in research is being carried out. However, it is acknowledged that there is also much to be learnt from developed world experience

Collaborative model development increases trust in and use of scientific information in environmental decision-making

While science matters for environmental management, creating science that is credible, salient to decision-makers, and deemed legitimate by stakeholders is challenging. Collaborative modeling is an increasingly-used approach to enable effective science-based decision-making. This work evaluates the modeling process conducted for two hydropower dam licensing negotiations, to explore how differences in the collaborative development of hydrological models affected differences in their use in subsequent decision-making. In one case, the model was developed iteratively through deliberation with stakeholders. Consequently, stakeholders understood the model and its limitations and trusted the model and modelers; the model itself was also better designed to evaluate resource managers’ questions. The collaboratively-developed model became the focal point for subsequent negotiations and enabled creative group problem-solving. Conversely, in the case with less engagement during model development, the model was not used subsequently by decision-makers. These differences are argued to result from trust built during the modeling process, applicability of the model to test real management scenarios, and the broader social context in which the models were used