Formation of analytical activity scenarios
Advanced analytics is one of the most required information technologies. Research of a scenario formation process of analytical activity is required for advanced analytics realization. Analytical activity scenarios define order of analytical activity conduction for obtainment of necessary informatio...
Gespeichert in:
| Datum: | 2014 |
|---|---|
| Hauptverfasser: | , , |
| Format: | Artikel |
| Sprache: | English |
| Veröffentlicht: |
Навчально-науковий комплекс "Інститут прикладного системного аналізу" НТУУ "КПІ" МОН та НАН України
2014
|
| Schriftenreihe: | Системні дослідження та інформаційні технології |
| Schlagworte: | |
| Online Zugang: | http://dspace.nbuv.gov.ua/handle/123456789/85457 |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| Назва журналу: | Digital Library of Periodicals of National Academy of Sciences of Ukraine |
| Zitieren: | Formation of analytical activity scenarios / О.V. Koval, К.А. Zaitseva, Yu.D. Boyko // Системні дослідження та інформаційні технології. — 2014. — № 1. — С. 20-25. — Бібліогр.: 19 назв. — англ. |
Institution
Digital Library of Periodicals of National Academy of Sciences of Ukraine| id |
irk-123456789-85457 |
|---|---|
| record_format |
dspace |
| spelling |
irk-123456789-854572016-04-15T13:53:48Z Formation of analytical activity scenarios Koval, О.V. Zaitseva, К.A. Boyko, Yu.D. Проблеми прийняття рішень і управління в економічних, технічних, екологічних і соціальних системах Advanced analytics is one of the most required information technologies. Research of a scenario formation process of analytical activity is required for advanced analytics realization. Analytical activity scenarios define order of analytical activity conduction for obtainment of necessary information that assist to produce informed decisions. Scenario formation contains of scenarios building and optimization. The subject of the article is improvement of domain model over which analytical activity is performed. Object-oriented modeling method and adaptive object model approach is used to build analyzable domain object model. An adaptive object model that submits classes, attributes and relationships as metadata is built. Use of improving domain model in scenario area method that is used for scenario optimization conducts to enhancement of scenario optimization results. Scenario area method is adopted with account of domain object model building that includes analytical activity scenarios. Class diagram has been developed for domain and scenarios object model and can be used as computer model element of information-analytical program platform. Розширену аналітику включено до десятки найбільш затребуваних інформаційних технологій. Дослідження процесу формування сценаріїв аналітичної діяльності необхідно для реалізації розширеної аналітики. Сценарії аналітичної діяльності визначають порядок проведення аналітичної діяльності з метою отримання необхідної інформації для прийняття обґрунтованих рішень. Формування сценаріїв включає їх побудову та оптимізацію. Предметом статті є вдосконалення моделі предметної області, відносно якої проводиться аналітична діяльність. Метод об’єктно-орієнтованого моделювання і принципи побудови адаптивних об’єктних моделей використовуються для побудови об’єктної моделі предметної області, що аналізується. Побудовано адаптивну об’єктну модель, яка представляє класи, атрибути та взаємозв’язки як метадані. Використання вдосконаленої моделі предметної області для оптимізації сценаріїв методом сценарних областей призводить до покращення результатів методу оптимізації. Для об’єктної моделі предметної області та сценаріїв розроблено діаграму класів, яка може бути використана як елемент комп’ютерної моделі інформаційно-аналітичної програмної платформи. Расширенная аналитика включена в десятку наиболее востребованных информационных технологий. Исследование процесса формирования сценариев аналитической деятельности необходимо для реализации расширенной аналитики. Сценарии аналитической деятельности определяют порядок проведения аналитической деятельности с целью получения необходимой информации для принятия обоснованных решений. Формирование сценариев включает их построение и оптимизацию. Предметом статьи является усовершенствование модели предметной области, относительно которой проводится аналитическая деятельность. Метод объектно-ориентированного моделирования и принципы построения адаптивных объектных моделей используются для построения объектной модели анализируемой предметной области. Построена адаптивная объектная модель, которая представляет классы, атрибуты и взаимосвязи как метаданные. Использование усовершенствованной модели предметной области для оптимизации сценариев методом сценарных областей приводит к улучшению результатов метода оптимизации. Для объектной модели предметной области и сценариев разработана диаграмма классов, которая может быть использована как элемент компьютерной модели информационно-аналитической программной платформы. 2014 Article Formation of analytical activity scenarios / О.V. Koval, К.А. Zaitseva, Yu.D. Boyko // Системні дослідження та інформаційні технології. — 2014. — № 1. — С. 20-25. — Бібліогр.: 19 назв. — англ. 1681–6048 http://dspace.nbuv.gov.ua/handle/123456789/85457 004.5 en Системні дослідження та інформаційні технології Навчально-науковий комплекс "Інститут прикладного системного аналізу" НТУУ "КПІ" МОН та НАН України |
| institution |
Digital Library of Periodicals of National Academy of Sciences of Ukraine |
| collection |
DSpace DC |
| language |
English |
| topic |
Проблеми прийняття рішень і управління в економічних, технічних, екологічних і соціальних системах Проблеми прийняття рішень і управління в економічних, технічних, екологічних і соціальних системах |
| spellingShingle |
Проблеми прийняття рішень і управління в економічних, технічних, екологічних і соціальних системах Проблеми прийняття рішень і управління в економічних, технічних, екологічних і соціальних системах Koval, О.V. Zaitseva, К.A. Boyko, Yu.D. Formation of analytical activity scenarios Системні дослідження та інформаційні технології |
| description |
Advanced analytics is one of the most required information technologies. Research of a scenario formation process of analytical activity is required for advanced analytics realization. Analytical activity scenarios define order of analytical activity conduction for obtainment of necessary information that assist to produce informed decisions. Scenario formation contains of scenarios building and optimization. The subject of the article is improvement of domain model over which analytical activity is performed. Object-oriented modeling method and adaptive object model approach is used to build analyzable domain object model. An adaptive object model that submits classes, attributes and relationships as metadata is built. Use of improving domain model in scenario area method that is used for scenario optimization conducts to enhancement of scenario optimization results. Scenario area method is adopted with account of domain object model building that includes analytical activity scenarios. Class diagram has been developed for domain and scenarios object model and can be used as computer model element of information-analytical program platform. |
| format |
Article |
| author |
Koval, О.V. Zaitseva, К.A. Boyko, Yu.D. |
| author_facet |
Koval, О.V. Zaitseva, К.A. Boyko, Yu.D. |
| author_sort |
Koval, О.V. |
| title |
Formation of analytical activity scenarios |
| title_short |
Formation of analytical activity scenarios |
| title_full |
Formation of analytical activity scenarios |
| title_fullStr |
Formation of analytical activity scenarios |
| title_full_unstemmed |
Formation of analytical activity scenarios |
| title_sort |
formation of analytical activity scenarios |
| publisher |
Навчально-науковий комплекс "Інститут прикладного системного аналізу" НТУУ "КПІ" МОН та НАН України |
| publishDate |
2014 |
| topic_facet |
Проблеми прийняття рішень і управління в економічних, технічних, екологічних і соціальних системах |
| url |
http://dspace.nbuv.gov.ua/handle/123456789/85457 |
| citation_txt |
Formation of analytical activity scenarios / О.V. Koval, К.А. Zaitseva, Yu.D. Boyko // Системні дослідження та інформаційні технології. — 2014. — № 1. — С. 20-25. — Бібліогр.: 19 назв. — англ. |
| series |
Системні дослідження та інформаційні технології |
| work_keys_str_mv |
AT kovalov formationofanalyticalactivityscenarios AT zaitsevaka formationofanalyticalactivityscenarios AT boykoyud formationofanalyticalactivityscenarios |
| first_indexed |
2025-07-06T12:39:31Z |
| last_indexed |
2025-07-06T12:39:31Z |
| _version_ |
1836901279276728320 |
| fulltext |
© O.V. Koval, K.A. Zaitseva, Yu.D. Boyko, 2014
20 ISSN 1681–6048 System Research & Information Technologies, 2014, № 1
УДК 004.5
FORMATION OF ANALYTICAL ACTIVITY SCENARIOS
O.V. KOVAL, K.A. ZAITSEVA, Yu.D. BOYKO
Advanced analytics is one of the most required information technologies. Research
of a scenario formation process of analytical activity is required for advanced ana-
lytics realization. Analytical activity scenarios define order of analytical activity
conduction for obtainment of necessary information that assist to produce informed
decisions. Scenario formation contains of scenarios building and optimization. The
subject of the article is improvement of domain model over which analytical activity
is performed. Object-oriented modeling method and adaptive object model approach
is used to build analyzable domain object model. An adaptive object model that
submits classes, attributes and relationships as metadata is built. Use of improving
domain model in scenario area method that is used for scenario optimization con-
ducts to enhancement of scenario optimization results. Scenario area method is
adopted with account of domain object model building that includes analytical activ-
ity scenarios. Class diagram has been developed for domain and scenarios object
model and can be used as computer model element of information-analytical pro-
gram platform.
INTRODUCTION
Advanced analytics, new generation analytics and actionable analytics there are
terms that Gartner used to identify information technology trends in analytics [1].
“Optimization and simulation is using analytical tools and models to maximize
business process and decision effectiveness by examining alternative outcomes
and scenarios, before, during and after process implementation and execution”, in
this way Gartner identifies Advanced analytics [2]. Advanced analytical systems
don’t have enough theoretical bases in development of information-analytical
platform.
Advanced analytics application in decision management systems demands
task solution of process of analytical activity scenarios formation. Analytical ac-
tivity consists of regular collection and processing of information that can be used
to support decision making and to study and investigate objects and processes
features. Analytical activity scenarios specify order of analytical activity imple-
mentation with the aim of getting necessary information for sufficient decision-
making. Scenario formation contains of scenarios building and optimization. That
is why building and optimization methods are considered separately.
Design of information-analytical program platform requires development of
adaptive elements in computer model of this system. It is necessary to create
adaptive method of advanced analytics scenario formation according to the con-
cept of object-oriented design and object model adaption for program platform.
ANALYSIS OF LATEST SCIENTIFIC RESEARCH AND ISSUES
Scenario building methods in scenario planning for socio-economic system de-
velopment have being studied by V.V. Kulba [3, 4], S.A. Yudickiy [5]. Yudickiy
gave a definition to the term scenario as a set of acts-operations that are imple-
Formation of analytical activity scenarios
Системні дослідження та інформаційні технології, 2014, № 1 21
mented in current order either parallel or sequentially. The circuit-recursive
method, suggested by Yudickiy S.A., is based on functional units building. Im-
plementation of a scenario research with circuit-recursive method assumes decom-
position of a system on component parts and defines the next parts of triad scheme:
• executive structure;
• scenarios as picture of planned behavior of executors;
• “supervisor” — manager that directs executors’ behavior in accordance
with specified scenario and real situations that particularly appear by exposure of
external activities.
Circuit-recursive approach assumes sequentially entering and analyzing of
new schemas that is associated with the result of previous modeling schemas. Re-
lations between them display by tree-like graph. System consists of three levels
and hierarchic structure. High difficulty of the system can cause the large number
of functional units that are complicated to interpret or can cause contradictions in
it. To remove existing limitation have been suggested to use object-oriented ap-
proach.
Methods of scenario optimization have been studied by P. Van Notten [6],
P.H. Shumaher [7], A. Yang and H.A. Abbas [8], D.A. Kononov [9, 10],
Z.K. Avdeeva and V.I. Maximov [11]. Those methods are using to find positive,
negative and neutral variants of actions development.
Object structure includes a set of factors that define state of object and rela-
tionships between factors. This allows us to carry out an aggregation of factors
into unified indicator. There is no necessity to conduct the aggregation of factors
during scenario optimization because of different object entities in domain.
The aim of scenario area method is generation of possible scenarios that cor-
respond to specified criteria. Criteria are used to split alternative set on groups
and to make selection from variants due to conditions.
Analytical activity automation consists of two stages:
• Description of Domain — the stage where domain object model is con-
structed.
• Generation of Analytical activity scenarios — the stage in which func-
tional part of information analysis process is built.
Analytical activity scenarios use domain object model (AOM) for access to
correspondent objects. In this way we suggest to build adaptive object model that
simultaneously includes description of domain and scenarios.
The aim of this article is development of adaptive object model (AOM) of
domain and analytical activity scenarios that can be used to design programming
platform of information-analytical system.
Object-oriented modeling method (DOMM) and adaptive object model ap-
proach are used to build domain object model for scenarios. Object-oriented mod-
eling method assumes composing of object-oriented analyze and design. A result
of applying OOMM is domain object model development [12].
Adaptive object model architecture has being studied by H.S. Ferreira [13],
N. Revault [14] and L. Welicki [15,16]. An Adaptive Object-Model is a system
that represents classes, attributes, and relationships as metadata. It is a model
based on instances rather than classes. Users change the metadata (object model)
to reflect changes in the domain.
O.V. Koval, K.A. Zaitseva, Yu.D. Boyko
ISSN 1681–6048 System Research & Information Technologies, 2014, № 1 22
An Adaptive Object Model is where the object representation of the domain
under study has itself an explicit object model (however partial) that is interpreted
at run-time. Such an object model can be changed with immediate (but controlled)
effect on the system during it’s interpretation and runing [17].
The real power in Adaptive Object-Models is that the definition of a domain
model and rules for its integrity can be configured by domain experts external to
the execution of the program [18].
The main advantage of adaptive object model is ease change. Adaptive ob-
ject model is used for development of system which allow user to “program with-
out programming” [19]. AOM is appropriate solution when system domain has
been changing permanently or users have need of dynamically configuring their
applications.
Scenario area method was suggested for scenario optimization. Concept of
variable and its range are used in this method. We applied this method for build-
ing scenario object model and made two analogies: from value to “Entity” of do-
main object model and from value of variable to “Attribute” (see next).
An adaptive object model that submits classes, attributes and relationships as
metadata in the notation of class diagram has been developed using the concept of
model-oriented approach and basic methodology of Adaptive Object Model build-
ing which create a possibility to form object model in accordance with mathemati-
cal model and analytical activity scenarios on the basis of object model (Figure).
Figure. Adaptive object model of domain and scenarios
Formation of analytical activity scenarios
Системні дослідження та інформаційні технології, 2014, № 1 23
Adaptive object domain model includes following items: “Domain”, “En-
tity”, “Attribute” and “Attribute Type”.
• “Domain” — a combination of interrelated concepts that characterized by
following properties:
- “Domain Name” — a short name of the subject area;
- “Description” — a brief description of the subject area;
- “Reference to entities” — a link to all entities that compose description
of the subject area.
• “Entity” — combination of objects in the domain. It has following
properties:
- “Entity name” — a short name for domain entity;
- “Description of the entity” — a brief description of domain entity;
- “Link to the attributes” — a reference to the list of attributes that char-
acterize this entity.
• “Attribute” — characteristic property of domain entity:
- “Attribute name” — a short name for attribute of entity;
- “Attribute type” — a type of value for attribute (numeric, text, etc.);
- “Link to value” — a reference to program data containers, which pro-
vide access to values of attribute in appropriate structures of data (files, data-
bases).
Value — data structures that store attribute values of domain entities.
Data structures — data in different file types (text, executive, multimedia)
and elements of databases and data warehouses.
Values can be single (number, character string) or plural (database record,
database table, data warehouse cube).
• “Attribute TYPE” — a directory of all scenario event types with follow-
ing properties:
- “Code ID” — a unique code for each type of attribute;
- “Type name” — a name of attribute type.
Scenario object model includes following items: “Scenario”, “Scenario Ele-
ment”, “Element Type” and “Action”.
• “Scenario” — a combination of interconnected elements of scenario in
various types (actions, events, messages, etc.).
- “Name” — a short name of scenario;
- “Scenario GOAL” — a goal of scenario analysis;
- “Description” — a brief description of scenario;
- “Scenario participant” — a participant of scenario (Analyst, domain
expert or users and also members of processes that interact with this scenario);
- “Initial Elements” — a link to initial elements of scenario (one or
more), from which it begins;
- “Link to elements” — a reference to all elements of scenario (scenario
element can be part of some scenarios).
• “Scenario Element” — an entirety of consistently associated between
each other scenario elements that specify different activity types (actions, events,
messages, etc.) and maintain links to implement their functions.
- “Element Name” — a short name of scenario element;
- “Element type” — an identifier of actions, events, messages, etc.;
O.V. Koval, K.A. Zaitseva, Yu.D. Boyko
ISSN 1681–6048 System Research & Information Technologies, 2014, № 1 24
- “Description of the element” — a brief description of element;
- “Link to the following elements” — a reference to elements of scenario
that will be enforced after this action;
- “Reference to previous elements” — a reference to scenario elements
that precede on this action;
- “Function Reference” — a reference on description of function that im-
plements functionality of the scenario element;
- “Element Member” — a subject that activates execution of this ele-
ment.
• “Element Type” — an element type specifies various mechanisms of the
element implementation during scenario execution.
- “Type ID” — a unique code for each scenario element type;
- “Type Name” — a text description of scenario element (“action”,
“event”, “message”, etc.).
• “Action” — describes functional realization of scenario elements. An ob-
ject “Action” has following properties:
- “Function name” — a function name, which is used when calling action
of those exist;
- “Options” — a list of action parameters (possibly empty);
- “Description of action” — an algorithm of action in terms of domain
objects;
- “Link to implementation” — a reference to software implementation of
actions (module, service).
Software implementation — is a software module or a service that imple-
ments the algorithm for corresponding action.
Access to data is performed through the metadata of domain model. In this
way scenario model doesn’t depend on data and can be configured on different
data sources through appropriate metadata.
This building model feature allows modelling of scenarios executing using
relative data in test mode. Scenario can be configured on real data base after it
testing through configuring of the appropriate metadata.
Such elements of adaptive object model as “GOAL” and “Participant” are
incomplete which demand more detailed research.
SUMMARY AND CONCLUSIONS
Use of described adaptive method of analytical activity scenarios formation ex-
tended the possibilities of scenario-target approach application in management
activity. Advanced class diagram can be used in information-analytical system on
program platform. Analyze and assessment of socio-economic, ecological-
economic and similar processes in region and those that related to it will be sim-
plified by analytical activity processes.
Area of research in this field is the next-generation research. Tasks that
should be considered are: development of information technology for fast inter-
pretation of adaptive object model and enhancement of this model by defining
objects “Goal” and “Participant”.
Formation of analytical activity scenarios
Системні дослідження та інформаційні технології, 2014, № 1 25
REFERENCES
1. Magic Quadrant for Business Intelligence and Analytics Platforms. — 2013, © Gartner.
2. Gartner Identifies the Top 10 Strategic Technologies for 2010. — 2009, © Gartner.
3. Кульба В.В., Кононов Д.А., Чернов И.В., Рощин П.Е., Шулигина О.А. Сценарное
исследование сложных систем: анализ методов группового управления //
Управление большими системами. 2010. Специальный выпуск 30.1 «Сете-
вые модели в управлении». — C. 154–186.
4. Кульбаба В.В., Кононов Д.А., Косяченко С.А., Шубина А.Н. Методы формиро-
вания сценариев развития социально-экономических систем / Серия «Сис-
темы и проблемы управления». — 2004. — 296 c.
5. Юдицкий С.А., Барон Ю.Л., Жукова Г.Н. Построение и анализ логического
портрета сложных систем: Препринт. — М.: ИПУ РАН, 1997. — 48 с.
6. Ph. Van Notten, Scenario Development: a Typology of Approaches // Think Sce-
nario, Rethink Education. — Paris: OECD Publishing, 2006. — Р. 69–84.
7. Schoemaker PJH. Multiple scenario development: Its conceptual and behavioural
foundation // Strategic Management Journal. — 1993. — N 14. — P. 193–213.
8. Yang A., Abbass H.A. & Sarker R. 2006. Land Combat Scenario Planning: A Mul-
tiobjective Approach, Lecture Notes Computer Science, LNCS 4247, Springer-
Verlag. — P. 837–844.
9. Кононов Д.А. Эффективные стратегии формирования сценариев в АСУ ЧС //
Автоматика и телемеханика. — 2001. — № 2. — С. 170–181.
10. Кононов Д.А., Косяченко С.А., Кульбаба В.В. Формирование и анализ сценариев
развития социально-экономических систем с использованием аппарата
операторных графов // Автоматика и телемеханика. — 2007. — № 1. —
C. 121–136.
11. Авдеева З.К., Максимов В.И. Методика выбора факторов и построения сцена-
риев анализа развития ситуации на базе SWOT-схемы // Управление боль-
шими системами. — 2010. — № 31. — С. 6–34.
12. Об’єктно-орієнтоване моделювання програмних систем: Навчальний посібник. —
Львів: Видавничий центр ЛНУ ім. Івана Франка, 2007. — 108 с.
13. Ferreira H.S. Adaptive object-modelling: Patterns, tools and applications /
H.S. Ferreira, A. Aguiar, J.P. Faria // International Conference on Software Engi-
neering Advances. — IEEE Computer Society: Los Alamitos, CA, 2009. —
P. 530–535.
14. Revault N. Adaptive Object-Models and Metamodeling Techniques / N. Revault,
W.Y. Joseph // ECOOP Workshops. — 2001. — P. 57–71.
15. Welicki L. Adaptive Object Model Builder / L. Welicki, R. Wirfs-Brock, J.W. Yoder
// Pattern Languages of Programs PLoP 2009. — Chicago, 2009. — P. 1–7.
16. Welicki L., Yoder J.R., Wirfs-Brock R. Rendering Patterns for Adaptive Object
Models // 14th Pattern Language of Programs Conference. — Monticello,
2007. — P. 1–22.
17. Yoder J.W. Metadata and Active Object-Models / J.W. Yoder, B. Foote, D. Riehle,
M. Tilman // Workshop Results Submission. — OOPSLA Addendum, 1998. —
P. 50–60.
18. Marcio Sa, Diego Jesus. Adaptive Object Modeling. — 2010. — P. 22–31.
19. Yoder J.W. Architecture and Design of Adaptive Object-Models // SIGPLAN No-
tices 12. — 2001. — P. 50–51.
Received 30.10.2013
From the Editorial Board: the article corresponds completely to submitted manuscript.
|