Vision statement on open architecture for hydraulic modelling software tools

Khatibi, Rahman; Jackson, Dave; Curtin, John J.; Whitlow, Chris; Verwey, A.; Samuels, Paul

doi:10.2166/hydro.2004.0005

Cited by 5 publications

(13 citation statements)

References 9 publications

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“…Moreover, it is also depends on the increasing number of stakeholders whose decisions may be influenced by the results from modelling and their interactions with the innovators, developers and users of numerical models. This paper considers the historical development of numerical modelling as described by Abbot (Abbott 1991) and Khatibi and colleagues (Khatibi 2001(Khatibi , 2003aKhatibi et al 2004). …”

Section: Framework For Assessing Model Developmentmentioning

confidence: 99%

“…As you move from generation to generation, the roles of scientist, developer, user and supporter have gradually split and become distinct. The role of the common user in each generation is illustrated in Table 2 ( Abbott 1991;Abbott & Vojinovic 2009;Khatibi et al 2004). The re-definition of the fifth generation as 'Software-as-a-service' (Abbott & Vojinovic 2009) represents a logical continuation of the changing role of the user, who no longer needs to be an expert to run a piece of software.…”

Section: Framework For Assessing Model Developmentmentioning

confidence: 99%

“…As such, it is up to the developer to produce a service that has sufficient help and is sufficiently constrained to be used by a competent professional. Khatibi et al (2004) point out that the causes of the changes from one generation of models to another are not readily identifiable in Abbott's account and preferred to apply 'systemic knowledge management' (Khatibi 2003a, b) to explain the current status and potential future for software tools in hydraulic modelling. Khatibi (2003a) developed systemic knowledge management as a methodological tool for assessing the development of a scientific paradigm, in this case hydraulic modelling.…”

Section: Framework For Assessing Model Developmentmentioning

confidence: 99%

“…Khatibi (2003a) proposed that 'an understanding of the interfaces between the interacting systems is the key for systemic problem-solving', while Khatibi (2003b) promotes a move towards an open architecture which uses standard interfaces to link modules. Khatibi et al (2004) Harvey & Han (2002) and others. This paper explores many of the current issues that need to be overcome to promote the concept of model integration by the dynamic linking of models.…”

mentioning

confidence: 99%

“…However, most of the established hydraulic and morphodynamic models were developed as proprietary or bespoke packages. These models largely followed the closed architecture philosophy, which emerged in response to the development of a niche market for modelling services but which also posed problems for the clients of these services (Khatibi et al 2004): † Organizations that use or manage the results of these models need to manage the risk that a software capability becomes obsolete. † Consultants need to maintain a store of proprietary software products.…”

mentioning

confidence: 99%

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From integration to fusion: the challenges ahead

Sutherland¹,

Townend²,

Harpham³

et al. 2014

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The increasing complexity of numerical modelling systems in environmental sciences has led to the development of different supporting architectures. Integrated environmental modelling can be undertaken by building a 'super model' simulating many processes or by using a generic coupling framework to dynamically link distinct separate models during run-time. The application of systemic knowledge management to integrated environmental modelling indicates that we are at the onset of the norming stage, where gains will be made from consolidation in the range of standards and approaches that have proliferated in recent years. Consolidation is proposed in six topics: metadata for data and models; supporting information; Software-as-a-service; linking (or interface) technologies; diagnostic or reasoning tools; and the portrayal and understanding of integrated modelling. Consolidation in these topics will develop model fusion: the ability to link models, with easy access to information about the models, interface standards such as OpenMI and software tools to make integration easier. For this to happen, an open software architecture will be crucial, the use of open source software is likely to increase and a community must develop that values openness and the sharing of models and data as much as its publications and citation records.Gold Open Access: This article is published under the terms of the CC-BY 3.0 license.The past few decades have seen the inexorable rise of numerical modelling as a useful tool in hydro-environmental and geomorphological modelling. Models have become more and more detailed, representing more and more processes and, with increasing computer power, being solved using larger and larger geo-spatial structures. These models can be aimed at solving a single set of equations, but have often branched out to include a wider range of processes with the formation of modelling suites.Albeit a little belatedly, numerical modelling has followed mainstream information technology (IT) in the way that the code is structured and deployed. Programmers began by writing short, self-contained bespoke applications, consisting of sequential lines of procedural code in languages such as FORTRAN. The benefits of callable sub-routines or functions were then quickly realized as applications grew in complexity, leading to a desire for reuse and clean interfaces. Many legacy applications, and those developed by scientific programmers, are still this way today. Object-oriented languages took this trend to its logical conclusion where every code segment has its own attributes and interfaces, and componentdriven architectures have increased the scale of such implementations.Alternatively, a set of environmental phenomena can be simulated using a complex composition of linked models, each of which is considered as a component at this level. In this way the progression of numerical model code structure can be summarized as in Table 1, from sequential programs of procedural code on the left to compositions of linked m...

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Section: Framework For Assessing Model Developmentmentioning

confidence: 99%

Section: Framework For Assessing Model Developmentmentioning

confidence: 99%

Section: Framework For Assessing Model Developmentmentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

See 3 more Smart Citations

From integration to fusion: the challenges ahead

Sutherland¹,

Townend²,

Harpham³

et al. 2014

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Flood Forecasting Model Selection

Tilford

Sene

Khatibi

Advances in Natural and Technological Hazards Research

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Systemic data management for mathematical modelling of environmental problems

Khatibi

Lincoln

Jackson

et al. 2004

Management of Environmental Quality: An International Journal

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With the diversification of modelling activities encouraged by versatile modelling tools, handling their datasets has become a formidable problem. A further impetus stems from the emergence of the real‐time forecasting culture, transforming data embedded in computer programs of one‐off modelling activities of the 1970s‐1980s into dataset assets, an important feature of modelling since the 1990s, where modelling has emerged as a practice with a pivotal role to data transactions. The scope for data is now vast but in legacy data management practices datasets are fragmented, not transparent outside their native software systems, and normally “monolithic”. Emerging initiatives on published interfaces will make datasets transparent outside their native systems but will not solve the fragmentation and monolithic problems. These problems signify a lack of science base in data management and as such it is necessary to unravel inherent generic structures in data. This paper outlines root causes for these problems and presents a tentative solution referred to as “systemic data management”, which is capable of solving the above problems through the assemblage of packaged data. Categorisation is presented as a packaging methodology and the various sources contributing to the generic structure of data are outlined, e.g. modelling techniques, modelling problems, application areas and application problems. The opportunities offered by systemic data management include: promoting transparency among datasets of different software systems; exploiting inherent synergies within data; and treating data as assets with a long‐term view on reuse of these assets in an integrated capability.

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Vision statement on open architecture for hydraulic modelling software tools

Cited by 5 publications

References 9 publications

From integration to fusion: the challenges ahead

From integration to fusion: the challenges ahead

Flood Forecasting Model Selection

Systemic data management for mathematical modelling of environmental problems

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