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![Figure 1: DGI Data Governance Model[10] 2.3 Data Governance Model of...](profile/Hanung-Prasetyo/publication/286466947/figure/fig1/AS:1049831694946305@1627310789200/DGI-Data-Governance-Model10-23-Data-Governance-Model-of-DAMA-DAMA-International_Q320.jpg)
![Figure 2: DAMA International Model[6]](profile/Hanung-Prasetyo/publication/286466947/figure/fig2/AS:1049831694954498@1627310789229/DAMA-International-Model6_Q320.jpg)
![Figure 3: IBM Data Governanve Model[9]](profile/Hanung-Prasetyo/publication/286466947/figure/fig3/AS:1049831694946306@1627310789256/IBM-Data-Governanve-Model9_Q320.jpg)
![Figure 4 : Perspective of SSM building[2]](profile/Hanung-Prasetyo/publication/286466947/figure/fig4/AS:1049831694929921@1627310789305/Perspective-of-SSM-building2_Q320.jpg)
Today, many emerging various models of data governance like DAMA, DGI and the latest is a model from IBM. Model DAMA International is a data governance model designed by industry associations. The model requires the fulfillment of the entire artifact in a matrix that has been determined that too many components that must be built in data governance...
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... On the other hand, few studies exist on using SSM in determining the governance policy. Prasetyo and Surendro (2015) utilized SSM to create a data governance model tailored to the organisation's specific requirements. SSM aims to find a suitable model for data governance by considering stakeholders' definitions and perspectives and considering models from DAMA, ...
A data governance policy is a foundational document providing instructions to manage data assets and organizational information effectively. Within the field of data governance, data access is one of the most important aspects of data management and includes considerations such as the extent of access, how to access data, access position, and data control and application. This research focuses on the banking industry, as its multiple stakeholders, diverse attitudes, and intangible aspects have created a problematic situation. To better understand and improve the current situation, soft systems methodology (SSM) provides a rich picture of the complex situation of data access in the bank, extracts key system definitions, and leads to a correct understanding of purposeful activities. After identifying these purposeful activities, a support policy for each set of activities is evaluated based on the literature in the field of data governance, specifically regarding data access. A mapping is established between activities and the fundamental principles of the data governance policy. One important innovation of this research is that, instead of directly utilizing SSM in the policy development process, it describes the situation and fundamental actions to provide the foundation for the policy. In conclusion, the data access problem has been identified as having various dimensions that can be grouped into six categories: data application, risk, processing, infrastructure, route, and access. These categories have been used to develop 13 support policy rules.
... Así mismo, existen marcos de referencia estándares de las mejores prácticas sobre gestión y GD que definen reglas y características que facilitan su manejo, entre las cuales se encuentra el Data Management Book of Knowledge (DMBOK), el cual es un marco que especifica objetivos, entradas, actividades, salidas, técnicas, herramientas y métricas para llevar a cabo una buena planificación, control, desarrollo y operación de la gestión de datos en sus diferentes áreas de conocimiento [11,12] . Por otra parte, el Data Governance Framework (DGF) del Data Governance Institute es un marco de referencia dedicado al GD que involucra estructura, personas y procesos para clasificar, organizar y comunicar decisiones en diferentes enfoques de gobernabilidad que apoyan a la organización a la toma de decisiones [13,14] . ...
El gobierno de datos (GD) asegura que los datos cumplan con las expectativas del negocio, reduzca costos de gestión, protección y desarrolle los datos como un activo estratégico y de valor. En Colombia, el Ministerio de Tecnologías de la Información y las Comunicaciones (MinTIC) ha entregado una herramienta conceptual para que las entidades públicas puedan adoptar la Arquitectura TI Colombia, definiendo lineamientos y guías para facilitar su entendimiento y aplicación. Este artículo tiene como Objetivo: Caracterizar el alcance de los marcos de referencia para facilitar la implementación del GD establecido por MinTIC para las entidades públicas. Metodología: El proceso consistió en: 1) identificar marcos de referencia, 2) caracterizar relación de marcos de referencia con lineamientos y elementos, 3) identificar alineación de los ámbitos y aportes de los marcos de gestión y GD para la implementación del GD, y 4) analizar los resultados de la investigación. Resultados: El proceso permitió identificar los elementos que cada marco de referencia aporta a la implementación del GD de acuerdo a los lineamientos establecidos por el MinTIC. Conclusiones: El Data Management Body of Knowledge del Data Management Association (DAMA) entrega herramientas y técnicas que facilitan la implementación de lo estipulado por el ministerio, el cual puede complementarse con elementos del Data Governance Framework del Data Governance Institute (DGI) y The Open Group Architecture Framework (TOGAF).
... Para el desarrollo del modelo de gobierno de datos se utilizará la Metodología Soft systems Methodology (SSM), se considera los problemas de las organizaciones y la relación con el medio ambiente (Prasetyo & Surendro, 2015 Para lo cual se debe generar procesos participativos utilizando métodos y técnicas que permitan identificar el problema, se debe plantear las siguientes preguntas: ...
Al calor de la pandemia se hace necesario revisar, evaluar, reflexionar sobre la base de lo que hasta ahora hemos vivido en cada uno de los espacios educativos universitarios. Y este libro, se convierte en una oportunidad especial para socializar los aportes de destacados autores en el marco del tema objeto de estudio.
Desde la práctica educativa en modalidad virtual en las enseñanzas de ciencias experimentales en tiempo de covid-19, pasando por la virtualización de los procesos de aprendizaje en la educación superior: experiencia latinoamericana frente al covid-19, gravitando además sobre el impacto de la pandemia de covid-19 sobre la educación.
... However, [59] argued that organizations should establish a data governance structure to get responsibility for data out of the IT department. According to [42], similar to IT governance, data governance also needs to align with any organization's business strategy. Enterprise Data Management Data Governance Plan [88] argue that a data governance model helps organizations to structure and document the accountabilities for their data quality. ...
... Section 5.1 presents different data governance frameworks, emerging from this systematic literature review. Despite the repeated call by researchers for the need of data governance frameworks, our study shows only a handful of them, mainly developed by industry associations such as DAMA, DGI, and IBM IBM [6,42,49,77], In 2011, Cloud Security Alliance [60] proposed a framework for data governance, which consists of goals and structure. The goals are divided into formal IT, business and functional goals, while the structure is divided into focus of control, organizational form, and roles and committees. ...
... According to DGI, the development of data governance framework is a complex task that could be formed of various related items that include programs, stages, decision domain, universal objects, and components. DGI divides their framework (see Fig. 5) activity into three components, namely the rules and roles, people, and organizations [42,90]. In addition, IBM's approach to data governance was built from the perspective of the vendor data governance software provider, so, establishing a data governance will require software support [42,91]. ...
Data management solutions on their own are becoming very expensive and not able to cope with the reality of everlasting data complexity. Businesses have grown more sophisticated in their use of data, which drives new demands that require different ways to handle this data. Forward-thinking organizations believe that the only way to solve the data problem will be the implementation of an effective data governance. Attempts in governing data failed before, as they were driven by IT, and affected by rigid processes and fragmented activities carried out on system by system basis. Up to very recently governance is mostly informal with very ambiguous and generic regulations, in siloes around specific enterprise repositories, lacking structure and the wider support of the organization. Despite its highly recognized importance, the area of data governance is still under developed and under researched. Since data governance is still under researched, there is need to advance research in data governance in order to deepen practice. Currently, what exist are mostly descriptive literature reviews in the area of data governance. In this paper, a systematic literature review (SLR), which offers a structured, methodical, and rigorous approach to the understanding of the state-of-the-art of research in data governance. The objective of the study is to provide a credible intellectual guide for upcoming researchers in data governance to help them identify areas in data governance research where they can make the most impact. The systematic literature review covered published contributions from both academia and industry. The presented SLR searches and examines most relevant published work since year 2000 to-date for data governance for non-cloud, and for cloud computing since 2007. Only 52 studies met the inclusion criteria, which are critically reviewed.
... Scientific Papers in journals and conference proceedings (Allen et al. 2014), (Becker 2007), (Begg & Caira 2011), (Begg & Caira 2012), (Borgman et al. 2016), (Brooks 2019), (Brous et al. 2016a), (Brous et al. 2016b), (Brous et al. 2016c), (Brown & Toze 2017), (Bruhn 2014), (Carretero et al. 2017), (Cheng et al. 2017), (Cheong & Chang 2007), (Choi & Kroeschel 2015), (Cousins 2016), (Coyne et al. 2018), (Dahlberg & Nokkala 2015), (Daneshmandnia 2019), (de Abreu Faria et al. 2013), (Donaldson & Walker 2004), (Evans et al. 2019), (Felici et al. 2013), (Fu et al. 2011), (Gillies 2015), (Gillies & Howard 2005), (Grimstad & Myrseth 2011), (Guetat & Dakhli 2015), (Hagmann 2013), (Heredia-Vizcaíno & Nieto 2019), (Hovenga 2013), (Hovenga & Grain 2013), , (Jim & Chang 2018), (Kamioka et al. 2016), (Khatri 2016), (Khatri & Brown 2010), (Kim & Cho 2017), (Kim & Cho 2018), (Koltay 2016), (Kooper et al. 2011), (Korhonen et al. 2013), (Kravets & Zimmermann 2012), (Kusumah & Suhardi 2014), (Lajara & Maçada 2013), (Lăzăroiu et al. 2018), (Lee et al. 2017), (Lee et al. 2014), (Lemieux et al. 2014), (Lillie & Eybers 2019), (Lomas 2010), (Malik 2013), (Marchildon et al. 2018), (Mikalef et al. 2018), (Mlangeni & Ruhode 2017), (Neff et al. 2013), (Ng et al. 2015), (Nguyen et al. 2014), (Nielsen 2017), (Nielsen et al. 2018), (Niemi & Laine 2016), (Nwabude et al. 2014), (Otto 2011a), (Otto 2011b), (Otto 2011c), (Otto 2012), (Otto 2013), (Palczewska et al. 2013), (Panian 2010), (Permana & Suroso 2018), (Prasetyo 2016), (Prasetyo & Surendro 2015), (Proença et al. 2016), (Proença et al. 2017), (Rasouli et al. 2016a), (Rasouli et al. 2016b), (Rasouli et al. 2016c), (Rasouli et al. 2017), (Renaud 2014), (Rifaie et al. 2009), (Rosenbaum 2010), (Saputra et al. 2018), (Silic & Back 2013), (Tallon 2013), , (Tallon et al. 2014), (Thammaboosadee & Dumthanasarn 2018), (Thiarai et al. 2019), (Thompson et al. 2015), (Traulsen & Troebs 2011), (Tse et al. 2018 (Waltl et al. 2015), (Watson et al. 2004), (Weber et al. 2009), (Weller 2008), (Wende 2007), (Wende & Otto 2007), (Were & Moturi 2017), (Wilbanks & Lehman 2012), (Winter & Davidson 2017), (Winter & Davidson 2018), (Wright 2013), (Young & McConkey 2012), (Yu & Foster 2017), (Yulfitri 2016), (Zhang et al. 2017) Theses (Barker 2016), (Cave 2017), (Nguyen 2016), (Randhawa 2019), (Rasouli 2016) Practiceoriented Books (Dreibelbis et al. 2008), (Dyché & Levy 2006), (Loshin 2008), (Morabito 2015) ...
Data governance refers to the exercise of authority and control over the management of data. The purpose of data governance is to increase the value of data and minimize data-related cost and risk. Despite data governance gaining in importance in recent years, a holistic view on data governance, which could guide both practitioners and researchers, is missing. In this review paper, we aim to close this gap and develop a conceptual framework for data governance, synthesize the literature, and provide a research agenda. We base our work on a structured literature review including 145 research papers and practitioner publications published during 2001-2019. We identify the major building blocks of data governance and decompose them along six dimensions. The paper supports future research on data governance by identifying five research areas and displaying a total of 15 research questions. Furthermore, the conceptual framework provides an overview of antecedents, scoping parameters, and governance mechanisms to assist practitioners in approaching data governance in a structured manner.
... This includes information on how an organisation is to be directed as well as control structures and policies that will help fulfill business objectives. According to the IBM IT Governance Approach, IT governance is also defined to be concerned with strategic alignment between the goals and objectives of the business and the utilization of its IT resources to effectively achieve the desired results (Prasetyo & Surendro, 2015). ...
... To achieve successful data governance, organisations need a strategy framework that can be easily implemented in accordance with the needs and resources of information [11,12]. A good data governance framework can also help organisations to create a clear mission, achieve clarity, increase confidence in using organisational data, establish accountabilities, maintain scope and focus, and define measurable successes [11,13]. ...
... Non-cloud: [6,7,9,[11][12][13][14]30,33,34,37,44,[47][48][49][50][51][52][53][54][55][56][57][58][59]. ...
Forward-thinking organisations believe that the only way to solve the data problem is the implementation of effective data governance. Attempts to govern data have failed before, as they were driven by information technology, and affected by rigid processes and fragmented activities carried out on a system-by-system basis. Until very recently, governance has been mostly informal, with very ambiguous and generic regulations, in siloes around specific enterprise repositories, lacking structure and the wider support of the organisation. Despite its highly recognised importance, the area of data governance is still underdeveloped and under-researched. Consequently, there is a need to advance research in data governance in order to deepen practice. Currently, in the area of data governance, research consists mostly of descriptive literature reviews. The analysis of literature further emphasises the need to build a standardised strategy for data governance. This task can be a very complex one and needs to be accomplished in stages. Therefore, as a first and necessary stage, a taxonomy approach to define the different attributes of data governance is expected to make a valuable contribution to knowledge, helping researchers and decision makers to understand the most important factors that need to be considered when implementing a data governance strategy for cloud computing services. In addition to the proposed taxonomy, the paper clarifies the concepts of data governance in contracts with other governance domains.
Man and how to play his role in various fields is the main issue
of governance. Therefore, the study of various governance
issues should be done according to this factor. The social
sciences and humanities owe engineering sciences the
application of systems methodologies, especially soft
methodology over the past few decades. The purpose of this
study was to evaluate the capabilities of various research
methods in soft operations in governance studies and
according to the research questions based on the method
adopted (qualitative approach using meta-analysis) in the
period from 2000 to 2021, it was found that the use of soft
methods is on the rise. "soft systems methodology, scenario�based planning, and viable systems model" being used for
governance studies, corporate governance, public
governance, and information technology governance. The
studies led to the extraction of a model for selecting the type
of soft research method for governance studies. Therefore,
considering that, this study with these dimensions has not
been done in the country so far and has not led to pattern
design, it is new. It was also found that methods such as
heaven-to-earth approach methodology, futures studies,
analysis and development of strategic options, and the method
of revealing and testing strategic assumptions have been less
used in governance studies.
La pandemia de la COVID 19 ha cambiado sustancialmente la vida de las personas, incluso ha alterado las condiciones organizativas y funcionales de las instituciones educativas, en el modo presencial la educación tenía décadas en desarrollo, siendo uno de los retos más importantes en esta modalidad educativa el de destacar la integración social de la comunidad universitaria, en especial los jóvenes, hoy el reto se hace un desafío, porque pasamos a la virtualidad.
En otro orden de ideas, cabe señalar que los múltiples estudios sobre la pandemia la COVID 19 han sido sistemáticos, profundos y quizás desproporcionados, dado que cada país tiene sus propias estrategias y por ende las instituciones también la tienen, esto hizo que se haga complejo el proceso del cambio educativo.
Este libro pretende generar una reflexión global de la Educación Superior y la Covid 19, expuesta en diferentes capítulos y desarrollo por parte de notables docentes investigadores, que han realizado monográficos de cara a la importancia del cambio ocurrido en el paso de la COVID 19.
En los aportes expuestos en esta obra, dan cuenta los autores de la importancia y del impacto que ha traído las medidas de confinamiento para salvaguardar las vidas humanas, en especial de la comunidad universitaria, siendo el principal actor los jóvenes universitarios, cuyo esfuerzo se presenta al momento de aunar esfuerzos y colaborar de manera segura y efectiva con las autoridades universitarias, con los interlocutores sociales, la sociedad civil, la instituciones, a fin de aplicar estrictamente las medidas que provienen del ente gubernamental y educativo para el resguardo de la salud de la población universitaria.
La obra presenta historias y declaraciones importantes sobre la Covid 19 incluyendo ideas innovadoras que determinan la reflexión de los investigadores en torno a cómo afrontar la crisis.
En este sentido, los aportes de esta obra permitirán el apoyo y amplificación de opiniones y acciones a tomar en torno al COVID 19, instando a los lectores a realizar urgentes, especificas e inteligentes lecturas para conocer de manera particular los avances que se han suscitado en torno al COVID 19 y la educación superior. Merece especial atención los actores estudiantes y jóvenes de la comunidad universitaria, quienes requieren de formación, protección social, garantía de calidad, facilitación de aprendizaje en línea y a distancia, complementariedad en estrategias didácticas, apoyo psicosocial y actividades que sean cónsonas a combatir el estrés que trae el confinamiento y un cambio transcendental en el proceso de enseñanza y aprendizajes.
La Universidad Nacional del Chimborazo se complace en la difusión de estos estudios, por cuanto es una respuesta al mundo académico ante la crisis de la pandemia de la COVID 19, en especial por su impacto en la interrupción de la educación y formación, el aumento de la vulnerabilidad de los jóvenes y sus hogares, y además los efectos que trae consigo las desigualdades y el potencial productivo que esta generación requiere en el proceso de su formación profesional.
