scholarly journals A Query Language for Workflow Logs

2022 ◽  
Vol 13 (2) ◽  
pp. 1-28
Author(s):  
Yan Tang ◽  
Weilong Cui ◽  
Jianwen Su

A business process (workflow) is an assembly of tasks to accomplish a business goal. Real-world workflow models often demanded to change due to new laws and policies, changes in the environment, and so on. To understand the inner workings of a business process to facilitate changes, workflow logs have the potential to enable inspecting, monitoring, diagnosing, analyzing, and improving the design of a complex workflow. Querying workflow logs, however, is still mostly an ad hoc practice by workflow managers. In this article, we focus on the problem of querying workflow log concerning both control flow and dataflow properties. We develop a query language based on “incident patterns” to allow the user to directly query workflow logs instead of having to transform such queries into database operations. We provide the formal semantics and a query evaluation algorithm of our language. By deriving an accurate cost model, we develop an optimization mechanism to accelerate query evaluation. Our experiment results demonstrate the effectiveness of the optimization and achieves up to 50× speedup over an adaption of existing evaluation method.

2019 ◽  
Vol 26 (2) ◽  
pp. 548-569
Author(s):  
Junaid Haseeb ◽  
Naveed Ahmad ◽  
Saif U.R. Malik ◽  
Adeel Anjum

Purpose Business process (BP) reengineering is defined as reinventing BPs either structurally or technically to achieve dramatic improvements in performance. In any business process reengineering (BPR) project, process modeling is used to reason about problems found in existing (as-is) process and helps to design target (to-be) process. BP model notation is a widely accepted standard for process modeling. “Expressiveness” and “missing formal semantics” are two problems reported to its modeling practices. In existing studies, solutions to these problems are also proposed but still have certain limitations. The paper aims to discuss this issue. Design/methodology/approach In proposed methodology, a meta-model is formally defined that is composed of commonly used modeling elements and their well-formedness rules to check for syntactic and structural correctness of process models. Proposed solution also check semantics of process models and allows to compare as-is and to-be process models for gap identification which is another important aspect of BPR. To achieve the first goal, Z specification is used to provide formal specifications of modeling constructs and their rules and Z3 (an SMT solver) is used for comparisons and verifying properties. Findings Proposed method addresses both “expressiveness” and “missing formal semantics” of BPR models. The results of its evaluation clearly indicate that using formally specified meta-model, BPR model is syntactically and structurally correct. Moreover, formal modeling of BPs in Z3 helped to compare processes and to check control flow properties. Research limitations/implications Although the proposed method is tested on an example that is widely used in BPR literature, the example is only covering modeling elements which are part of the proposed subset and are reported in literature as frequently used modeling elements. A separate detailed study is required to test it on more complex systems. Practical implications Specifying process models using Z specification and Z3 solver requires certain expertise. Originality/value The proposed method adds value to BPR body of knowledge as it proposes a method to ensure structural and syntactic correctness of models, highlighting the importance of verifying run time properties and providing a direction toward comparing process models for gap analysis.


Algorithms ◽  
2021 ◽  
Vol 14 (5) ◽  
pp. 149
Author(s):  
Petros Zervoudakis ◽  
Haridimos Kondylakis ◽  
Nicolas Spyratos ◽  
Dimitris Plexousakis

HIFUN is a high-level query language for expressing analytic queries of big datasets, offering a clear separation between the conceptual layer, where analytic queries are defined independently of the nature and location of data, and the physical layer, where queries are evaluated. In this paper, we present a methodology based on the HIFUN language, and the corresponding algorithms for the incremental evaluation of continuous queries. In essence, our approach is able to process the most recent data batch by exploiting already computed information, without requiring the evaluation of the query over the complete dataset. We present the generic algorithm which we translated to both SQL and MapReduce using SPARK; it implements various query rewriting methods. We demonstrate the effectiveness of our approach in temrs of query answering efficiency. Finally, we show that by exploiting the formal query rewriting methods of HIFUN, we can further reduce the computational cost, adding another layer of query optimization to our implementation.


Author(s):  
Kavita Sardana ◽  
John C. Bergstrom ◽  
J. M. Bowker

Abstract We estimate a travel cost model for the George Washington & Jefferson National Forests using an On-Site Latent Class Poisson Model. We show that the constraints of ad-hoc truncation and homogenous preferences significantly impact consumer surplus estimates derived from the on-site travel cost model. By relaxing the constraints, we show that more than one class of visitors with unique preferences exists in the population. The resulting demand functions, price responsive behaviors, and consumer surplus estimates reflect differences across these classes of visitors. With heterogeneous preferences, a group of ‘local residents’ exists with a probability of 8% and, on average take 113 visits.


2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Peter Baumann ◽  
Dimitar Misev ◽  
Vlad Merticariu ◽  
Bang Pham Huu

AbstractMulti-dimensional arrays (also known as raster data or gridded data) play a key role in many, if not all science and engineering domains where they typically represent spatio-temporal sensor, image, simulation output, or statistics “datacubes”. As classic database technology does not support arrays adequately, such data today are maintained mostly in silo solutions, with architectures that tend to erode and not keep up with the increasing requirements on performance and service quality. Array Database systems attempt to close this gap by providing declarative query support for flexible ad-hoc analytics on large n-D arrays, similar to what SQL offers on set-oriented data, XQuery on hierarchical data, and SPARQL and CIPHER on graph data. Today, Petascale Array Database installations exist, employing massive parallelism and distributed processing. Hence, questions arise about technology and standards available, usability, and overall maturity. Several papers have compared models and formalisms, and benchmarks have been undertaken as well, typically comparing two systems against each other. While each of these represent valuable research to the best of our knowledge there is no comprehensive survey combining model, query language, architecture, and practical usability, and performance aspects. The size of this comparison differentiates our study as well with 19 systems compared, four benchmarked to an extent and depth clearly exceeding previous papers in the field; for example, subsetting tests were designed in a way that systems cannot be tuned to specifically these queries. It is hoped that this gives a representative overview to all who want to immerse into the field as well as a clear guidance to those who need to choose the best suited datacube tool for their application. This article presents results of the Research Data Alliance (RDA) Array Database Assessment Working Group (ADA:WG), a subgroup of the Big Data Interest Group. It has elicited the state of the art in Array Databases, technically supported by IEEE GRSS and CODATA Germany, to answer the question: how can data scientists and engineers benefit from Array Database technology? As it turns out, Array Databases can offer significant advantages in terms of flexibility, functionality, extensibility, as well as performance and scalability—in total, the database approach of offering “datacubes” analysis-ready heralds a new level of service quality. Investigation shows that there is a lively ecosystem of technology with increasing uptake, and proven array analytics standards are in place. Consequently, such approaches have to be considered a serious option for datacube services in science, engineering and beyond. Tools, though, vary greatly in functionality and performance as it turns out.


2004 ◽  
Vol 13 (03) ◽  
pp. 289-332 ◽  
Author(s):  
JULIANE DEHNERT ◽  
WIL M. P. VAN DER AALST

This paper presents a methodology to bridge the gap between business process modeling and workflow specification. While the first is concerned with intuitive descriptions that are mainly used for communication, the second is concerned with configuring a process-aware information system, thus requiring a more rigorous language less suitable for communication. Unlike existing approaches the gap is not bridged by providing formal semantics for an informal language. Instead it is assumed that the desired behavior is just a subset of the full behavior obtained using a liberal interpretation of the informal business process modeling language. Using a new correctness criterion (relaxed soundness), it is verified whether a selection of suitable behavior is possible. The methodology consists of five steps and is illustrated using event-driven process chains as a business process modeling language and Petri nets as the workflow specification language.


2018 ◽  
Vol 8 (2) ◽  
pp. 217-231 ◽  
Author(s):  
Wasana Bandara ◽  
Scott Bailey ◽  
Paul Mathiesen ◽  
Jo McCarthy ◽  
Chris Jones

Business process management (BPM) in the public sector is proliferating globally, but has its contextual challenges. Ad hoc process improvement initiatives across governmental departments are not uncommon. However, as for all organisations, BPM efforts that are coordinated across the organisation will reap better outcomes than those conducted in isolation. BPM education plays a vital role in supporting such organisation-wide BPM efforts. This teaching case is focused on the sustainable development and progression of enterprise business process management (E-BPM) capabilities at the Federal Department of Human Services: a large Australian federal government agency. The detailed case narrative vividly describes the case organisation, their prior and present BPM practices and how they have attempted BPM at an enterprise level, capturing pros and cons of the journey. A series of student activities pertaining to E-BPM practices is provided with model answers (covering key aspects of BPM governance, strategic alignment, culture, people, IT, methods, etc.). This case provides invaluable insights into E-BPM efforts in general and BPM within the public sector. It can be useful to BPM educators as a rich training resource and to BPM practitioners seeking guidance for their E-BPM efforts.


Author(s):  
Brian Stokes

Background with rationaleBusiness Intelligence (BI) software applications collect and process large amounts of data from one or more sources, and for a variety of purposes. These can include generating operational or sales reports, developing dashboards and data visualisations, and for ad-hoc analysis and querying of enterprise databases. Main AimBusiness Intelligence (BI) software applications collect and process large amounts of data from one or more sources, and for a variety of purposes. These can include generating operational or sales reports, developing dashboards and data visualisations, and for ad-hoc analysis and querying of enterprise databases. Methods/ApproachIn deciding to develop a series of dashboards to visually represent data stored in its MLM, the TDLU identified routine requests for these data and critically examined existing techniques for extracting data from its MLM. Traditionally Structured Query Language (SQL) queries were developed and used for a single purpose. By critically analysing limitations with this approach, the TDLU identified the power of BI tools and ease of use for both technical and non-technical staff. ResultsImplementing a BI tool is enabling quick and accurate production of a comprehensive array of information. Such information assists with cohort size estimation, producing data for routine and ad-hoc reporting, identifying data quality issues, and to answer questions from prospective users of linked data services including instantly producing estimates of links stored across disparate datasets. Conclusion BI tools are not traditionally considered integral to the operations of data linkage units. However, the TDLU has successfully applied the use of a BI tool to enable a rich set of data locked in its MLM to be quickly made available in multiple, easy to use formats and by technical and non-technical staff.


Author(s):  
Steven Noel ◽  
Stephen Purdy ◽  
Annie O’Rourke ◽  
Edward Overly ◽  
Brianna Chen ◽  
...  

This paper describes the Cyber Situational Understanding (Cyber SU) Proof of Concept (CySUP) software system for exploring advanced Cyber SU capabilities. CySUP distills complex interrelationships among cyberspace entities to provide the “so what” of cyber events for tactical operations. It combines a variety of software components to build an end-to-end pipeline for live data ingest that populates a graph knowledge base, with query-driven exploratory analysis and interactive visualizations. CySUP integrates with the core infrastructure environment supporting command posts to provide a cyber overlay onto a common operating picture oriented to tactical commanders. It also supports detailed analysis of cyberspace entities and relationships driven by ad hoc graph queries, including the conversion of natural language inquiries to formal query language. To help assess its Cyber SU capabilities, CySUP leverages automated cyber adversary emulation to carry out controlled cyberattack campaigns that impact elements of tactical missions.


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