This paper addresses the problem of evaluating the maturity of a digital archive in terms of its digital preservation capabilities. The European eArchiving initiative supports this assessment by providing the key tools of: a maturity model (eACMM), a reference architecture (eRA), and a collection of real-world cases based on the eRA framework. To our knowledge, this is the first paper to integrate these artifacts for a comprehensive evaluation. The eACMM is represented by a set of detailed requirements classified by importance. The eRA is represented by an ArchiMate model, and the real-world cases are represented as ArchiMate eRA viewpoints. This paper details the process of how to assess the real-world cases against the eACMM and demonstrates the value of such viewpoints. One significant challenge addressed in the literature is the lack of efective view models for identifying gaps in reference architectures. Despite the systematic prescription ofered by maturity models, they often lack the support of mechanisms that are necessary to fully realize the potential of diagnosing the current stage and identifying the next steps to increase maturity. This paper contributes with a solution implemented in a Enterprise Architecture management tool where the output is the automatic creation of Enterprise Architecture blueprints. Obtained results corroborate that our solution easily identifies the level of eACMM maturity in respect to eRA concepts, and also an immediate identification of actions that should be done to improve the eACMM level.
One limitation identified in the literature is the lack of tools currently available for representing the
maturity gaps. Usually, this is done manually, but automatic approaches are already being pointed as a
future solution to obtain better assessments [
Central to this process is the usage of the tool ATLAS 3 that supports various features of EA management. Specially relevant to our focus was its capability to generate views providing a visual synthesis of complex data, making it easier to analyze and identify discrepancies within the models. By leveraging ATLAS, the paper demonstrates how a systematic approach can be used to visualize and thereby enhance the maturity models under consideration. A dataset containing real digital archives implementations that used the eRA validates our maturity assessment proposal. It is important to emphasize that this paper is closely aligned with the eArchiving initiative, the eRA and the eACMM. eACMM is composed by a set of requirements represented as structured information, while eRA and the cases were represented in an ArchiMate model as a structured collection of elements, relationships and viewpoints.
For short, the solution encompasses the following stages done in the EAM tool: a) importing data, b) classifying the eACMM in the eRA model, c) computing the eACMM capability level for each element of the real-world case represented by the eRA model, and d) visualizing the eACMM capability levels organized by capability.
The Design Science Research (DSR) method, as outlined by Pefers et al. [
The paper is organized as follows. Section 2 presents the background concepts. Then, Section 3 describes and compares the EA tools that are of potential use in our paper. Afterwards, Section 4 details our solution. Section 5 validates the solution using the available datasets from E-ARK project. Finally, Section 6 concludes the paper and identifies future work.
The E-ARK project (European Archival Records and Knowledge Preservation) was a multinational initiative aimed at standardizing digital archiving methods across Europe. Running from 2014 and cofunded by the European Commission, it developed guidelines, open technical products, and integrated archiving infrastructure to enhance the availability, access, and use of archival data. Its results were adopted by the present eArchiving Initiative, which is influencing the European landscape in relation to the concern of digital preservation in the domain of digital archives.
This paper uses the dataset of the "eArchiving Referece Architecture v2.0", which is publicly available at: https://kc.dlmforum.eu/earchiving-ra20/ and the maturity model eACMM, both developed by EARK. These components already exist and are confirmed in the domain of digital archives and digital preservation. The focus is on enhancing their usability and efectiveness through the development of visual features.
Maturity models are widely used and recognized in both business and academics due to their simplicity and efectiveness. They can assist stakeholders grasp the present degree of maturity of a certain element in a meaningful way, allowing them to clearly identify strengths and weaknesses that need to be improved, and so prioritize what has to be done to achieve the next level. This may be used to 3https://linkconsulting.com/what-we-do/products/atlas/ demonstrate the outcomes of that endeavor, allowing stakeholders to determine whether the results justify the work or expenditure.
According to Proença and Borbinha [
Proença and Borbinha [
This method allows businesses to analyze their information governance practices around digital preservation. The eACMM focuses on the most significant references for digital archiving, particularly those that are being enhanced as part of the old eArchiving Building Block and the present eArchiving Initiative.
Reference architectures and maturity models are two key ideas in EA [
Pereira and Sousa [
Luftman [
The symbiotic relationship between reference architecture and maturity models is addressed Pereira and Sousa [12]. Reference architectures can serve as a foundation upon which maturity models can be applied, as they can provide the structured environment necessary for the efective maturity assessment. For instance, the use of a comprehensive reference architecture ensures that all components of the organization that are modeled can be considered during the maturity assessment, thereby providing a holistic view of the capabilities of the business.
Van Steenbergen et al. [13] discuss on how maturity models leverage reference architectures to identify gaps and weaknesses in the current system is presented. By mapping maturity model assessments to the reference architecture, organizations can pinpoint specific areas that require improvement and develop targeted strategies to enhance those areas. This alignment ensures that improvements are implemented in a systematic and cohesive way, consistent with the organization’s overarching strategic direction. For example, the Business IT Alignment Maturity model may be linked to the architectural domains of TOGAF (business, data, application, and technology), indicating a clear route to greater levels of alignment and maturity.
Gonzalez-Perez et al. [14] emphasize that reference models facilitate the implementation of maturity models by providing predefined templates and best practices. These characteristics are critical for businesses with lower maturity levels, where procedures may be unclear or poorly defined. Reference models provide a starting point and a set of standards that may be customized to meet the organization’s particular needs. This organized strategy reduces the risks associated with ad hoc deployments and guarantees that gains last in the long run.
According to Proença and Borbinha [15], the EA domain exists to address the challenge of ensuring alignment between IT and business. EA ofers advice on harmonizing business and IT, but adopting its approaches might be dificult. This study seeks to provide a maturity model for EA in companies as a governance tool for analyzing and improving their existing status. Maturity models enable reengineering linked to the EA life cycle through benchmarking and road map planning. This model is built on design science research and current literature, and it identifies essential success elements while also reviewing previous maturity models. The suggested model, which was tested in a multistep procedure, fills gaps in existing models by including best practices and key success criteria. EA entails developing models that represent an enterprise’s organizational structure, business processes, information systems, and infrastructure in order to manage and maintain alignment across time. Despite existing approaches, companies lack tools for assessing their present EA practices and identifying changes, making it dificult to improve their EA management practices.
In conclusion, the relationship between reference architectures and maturity models in the EA context is integral to achieving organizational excellence. Reference architectures provide the structural framework and common language necessary for efective maturity assessments, while maturity models ofer a road map for continuous improvement. Together, they enable organizations to systematically enhance their processes and capabilities, ensuring alignment with strategic objectives and fostering long-term success [16, 17].
This section reports to EA tools that are available to capture, transform and generate related data. EA is defined by TOGAF [ 18] as "the structure of components, their inter-relationships, and the principles and guidelines governing their design and evolution over time". Also, Greefhorst and Proper [ 19] consider three perspectives for architecture: "regulation-oriented, design-oriented, and knowledge-oriented, where the first corresponds to the prescriptive perspective, the second corresponds to the descriptive perspective, and the third corresponding to the high-level design decisions of the system". The EA way of working are proposed by many standards that are widely used in industry, e.g. TOGAF, DODAF, MODAF, etc., and are recognized as a lingua franca between clients, suppliers, consultants and/or researchers. The usage of tools aids the creation of EA artifacts, such as catalogs, matrices and diagrams, avoiding expending large amounts of time and efort to create them.
From the data summarized in Table 1, it is observable that ATLAS in comparison to other tools such as ADOIT5, Archi6, ARIS7, Enterprise Architect8, LeanIX9, MEGA10, and BizzDesign11, ofers features particularly suited to the maintenance of EA models and the creation of on-the-fly views of the model. ATLAS was used with a specific focus on digital preservation eforts, such as the E-ARK project, and is primarily used to generate graphical representations that aid in the analysis and decision-making processes in complex architectural environments.
ATLAS was chosen for the E-ARK project because of its capabilities to model and manage digital preservation procedures, and pragmatically, because it was a known tool for the research team. It assisted with critical activities such as blueprint design and efect analysis, both of which were required to assess digital archive maturity. However, it is crucial to highlight that the applicability of ATLAS varies based on the project objectives, and this comparison reflects its specific application within the context of the E-ARK project.
This section demonstrates the solution, systematically increasing the level of information provided to ensure a thorough understanding of the concepts presented. This step-by-step approach enhances clarity and guides the reader through the intricacies of our method, facilitating a detailed exploration of how our solution addresses the research problem. As an overview of the solution, Figure 2 depicts how the three steps are executed to generate the EA artifacts.
Prior to commencing the analysis of the solution, it is crucial to provide a comprehensive description of the dataset. The dataset is fundamentally derived from the project’s reference architecture, which encompasses 616 elements across various classes. The Table 2 provides a detailed breakdown and analysis of these dataset elements.
The initial step is to import the dataset into our ATLAS tool, and then create our metamodel based on the classes in the dataset. However, it is possible to add properties to these classes within the dataset. In addition to the convenience of using a Business Actor like Joe, the tool allows you to add properties to an object, such as Joe’s age. In ATLAS, the information about Joe object is stored, which is the Business Actor type and that he is, e.g., 40 years old. This method manipulates and adds properties to
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Business Information Application Technology Business Information Application Technology Business Information Application Technology Business Information Application Technology Technology Business Information Application Technology Business Information Application Technology Business Information Application
Standards
ArchiMate TOGAF
ArchiMate
ArchiMate TOGAF
ArchiMate TOGAF
— —
ArchiMate TOGAF
ArchiMate TOGAF
Artifacts Process models ERDs UML diagrams Data flow diagrams Process models ERDs UML diagrams Reports Process maps Swimlanes Decision trees Organizational charts Process models Data models UML diagrams BPMN diagrams Resource maps Cost reports Value stream maps Process models Data models UML diagrams Organizational charts Process maps Swimlanes Decision trees Organizational charts Process models Data models UML diagrams BPMN diagrams
Meta-model Variable Fixed Variable Fixed Variable Variable Fixed Variable metamodel classes using this analogy, allowing us to create blueprints. In this scenario, the Boolean property "isAssessed" is added to all metamodel classes to indicate which objects in the dataset were or were not covered by the maturity model. The paper also included a property named "environment" to distinguish which features are included in each case study and even the reference architecture. In addition to the classes found in the dataset, the Assessment class is generated, which has attributes like maturity level, capability level, and capability function. Objects in this class can be associated with objects in any other class in the metamodel, thus providing information on the relationship between the assessment made and the element covered by that assessment.
Our solution is based on the construction of blueprints and can be categorized into two distinct branches. One branch focuses on conducting a compliance analysis between real cases and the eRA, while the other branch centers on providing an overview of the eACMM. In the demonstration of the ifrst branch, a comparison between RODA case with eRA is done. Although the solution have the capability to analyse five real cases: RODA, ARS, ESSArch, NAE and NAF. The solution covers all these cases by inserting initial parameters when the blueprint is started. In this case, when blueprints are opened, for the first part of the solution, a pop-up window will appear, allowing us to choose an option from the list of real cases mentioned above. For example, for the following demonstrations below, the STEP A: Import data from eRA Archi model, including the RODA, ARS, ESSArch, NAE and NAF implementation cases.
STEP B: Using eACMM as a reference, classify the capability level of each architectural element as a data property.
STEP C: Compute data, using Algorithm 1 and 2, to obtain the visualization of the EA Diagram Artifacts. RODA parameter has been chosen. This means that the elements to be compared with the reference architecture will be those present in the RODA architecture.
In this study, various case studies were used to demonstrate the actual implementation of the eACMM maturity model in conjunction with EA models. The case studies chosen include RODA, ARS, ESSArch, NAE, and NAF. These are the identical cases used in the reports that will help us validate.
RODA (Repository of Authentic Digital Objects) is a digital preservation platform that ensures long-term access to digital content. It covers the entire digital archiving process, including ingest, archival storage, and access to digital objects.
The ARS (Archival Repository System) focuses on the management of archival records, ensuring that ingest, archival storage, and preservation processes are compliant with digital preservation standards.
ESSArch is a digital preservation system designed to maintain the integrity and accessibility of digital archives over time.
The NAE (National Archives of Estonia) focuses on ingesting and preserving large volumes of government records.
NAF (National Archives of Finland) handles both the preservation and dissemination of government records and historical data.
The purpose of the eACMM is to evaluate the maturity of digital preservation processes. It focuses on three major aspects of an archive: ingest, archival preservation, and dissemination. These processes are crucial in ensuring the long-term preservation and accessibility of digital records. The eACMM evaluates an organization’s capabilities in managing these processes using a set of capability levels, ranging from basic to optimizing. Each level assesses an organization’s ability to implement and maintain efective digital preservation workflows.
Our suggested approach makes use of EA models, specifically ArchiMate, to improve these procedures by ofering clear, pictorial depictions of the systems in question. These models aid in detecting weaknesses and potential areas for enhancement in the adoption of digital preservation best practices. Through mapping digital preservation systems’ capabilities to the eACMM, it is guaranteed that organizations can systematically advance their maturity in all important areas. For instance, depicting the data flow through the ingest process, from submission to archival storage, using ArchiMate models, emphasizes decision-making points and roles. Ineficiencies or potential issues in the preservation workflow can be then identified and changes that are consistent with greater capability levels can be suggested, by evaluating the implemented flow against the eACMM maturity criteria.
As previously mentioned, our solution includes a branch dedicated to conducting a compliance analysis between a given real case and the E-ARK reference architecture. This analysis involves assessing both sides to determine their alignment and compatibility. Starting with the most basic subset of this solution view. The figure 3 illustrates the business functions present in both the reference architecture and the scenario. The left box displays all business functions within the reference architecture, while the right box shows those present in the scenario. This visual comparison allows for a quick assessment of compliance, identifying which elements align and which do not between the two sets.
In the next stage, a box is located in the middle to indicate which elements have been reviewed, and therefore, are included in the maturity model. At this point, merely adding a box increases the amount of information provided by the plan. In the middle box, it is revealed the parts that are examined by the maturity model, which are the model’s major components. Figure 4 illustrates the process.
In the third step of our process, the box housing the assessed elements based on their capability are considered, and created an alternative blueprint version categorized by capability levels. As part of enhancing clarity and usability, color coding is incorporated, specifically employing green and red hues within the scenario elements box. These colors serve a crucial role in swiftly identifying whether an element has undergone evaluation or not. A red indication adjacent to an element signifies its non-assessment status, whereas a green indication denotes that the element has been thoroughly evaluated. This strategic integration of color coding not only streamlines the assessment process but also enhances the overall accessibility and interpretation of the blueprint and its respective components. Algorithm 1 depicts the pseudo code for construction of this process to designing the final blueprints.
The pseudo-code is adapted to the blueprint version that is organized by the capability levels, but it can be easily adapted to the maturity level version. On the one hand, our proposal have to check what capacity function an assessment that is associated with a dataset element has. The solution is checking what is written in the property "CapabilityFunction" from an assessment that is associated to an object from our dataset. To adapt it to the maturity level blueprint version a check about what are the number written on the "MaturityLevel" property from an assessment associated to an object is required. It will look like this: .. .
Figures 5 and 6 present the generated blueprints that include that third step, in the leftmost box all the elements belonging to the reference architecture. In the middle box, these same elements are evaluated, i.e., they are linked to the maturity model. In the right-hand box is depicted the elements that are part of the scenario, in this case the RODA scenario. It is shown that although there are only part of the elements present in the reference architecture, they correspond, and in the small colored boxes the elements evaluated in the scenario also conform to the reference model.
In this case, the scenario is in line with the reference architecture. Therefore, the organization would only recommend adding the elements that the reference architecture box contains and the real case does not. The elements that should be assessed are also in conformity. Figure 7 exemplifies the final solution blueprint covering all the layers that the scenario contains.
This section introduces an alternative blueprint emphasizing the maturity context of eACMM’s capabilities. Each capability is depicted as a series of nested boxes, illustrating its evolution across various capability levels. This hierarchical representation ofers a detailed view of how each capability progresses in terms of maturity within the E-ARK framework. Algorithm 2 depicts the pseudo-code trying to demonstrate the logic of the implementation of this part. Due to the code becoming repetitive, only the case in which the object is populated in the Pre-Ingest sub-container will be exemplified, however it can be generalized to Pre-ingest, Ingest, Access, Preservation, Data Management and Archival Storage. Figure 8 shows not only one class but as many as the ones contained in our maturity model. One business process and two business functions are observed. It is also relevant how the elements are distributed by their capability level. Figure 9 depicts the global result of the blueprint, here intentionally shown only as a low detailed glimpse view.
This section details the validation process undertaken to assess the efectiveness and reliability of our proposed solution. Our validation criterion centers on a comparison with definitive reports 12 13 generated by the E-ARK project team, considered authoritative and universally accepted as correct. The core of our validation hinges on achieving identical results to those outlined in this benchmark document. Our approach systematically scrutinizes the outputs generated by our solution against the outcomes documented in the E-ARK report. This thorough analysis ensures not only technical accuracy 12https://www.eark-project.com/resources/project-deliverables/46-d72initassess/eark_d7_2v2.pdf 13https://www.eark-project.com/resources/project-deliverables/96-d76-1/620998%20E-ARK%20D7.6.pdf_%3b%20filename_ %3dUTF-8%27%27620998%2520E-ARK%2520D7.6.pdf Algorithm 2 Pseudo-code explaining the construction of the solution blueprint showing the maturity model. but also alignment with established standards and methods stipulated by E-ARK. By demonstrating that our solution consistently produces results congruent with those in the authoritative report, this paper underscore its reliability and applicability within the context of compliance analysis for reference architectures.
Moreover, this validation phase serves as a cornerstone in afirming the credibility of our solution. The convergence of our findings with those of the E-ARK report validates not only the technical robustness of our method but also its potential to contribute significantly to advancing the field’s understanding and implementation of compliance analysis within reference architecture frameworks. compliance
maturity
RODA Archival information Dis emination Information Submis ion information
RODA Archival Storage Check availabil ty and rights Co rdinate archival and descriptive information storage Prepare dis emination information Proces request Provide ac es Receive and validate submis ion information
Retrieve information
RODA Ac es and Reuse Ac es data Create and Manage Active Records Long-term Preservation and Ac es Manage Archived Information Provide ac es to information Receive and store records Records Management Reuse information Submit Records to Archive
Busines Proces As es ed
Level 1 [AIS] Ar ange content [AIS] Manage Descriptive Metadata [AIS] Provide Ac es [Astia] Discovery [Astra] Ar ange content [Astra] Content QA [Astra] Create SIP [Astra] File Upload/Transfer Information [Astra] Manage Ap raisal Decisions [Astra] Manage Archival Schema & Description [Astra] Manage Clas if cation Schema [AV System] Export data and metadata [CubeMAM] View AV DIP content [Dataset e] Explore & Publish [dbDIPview] Instal DB from CSV [dbDIPview] Adjust DB DIP content (e.g. redaction) [dbDIPview] View DB DIP content [DBPTK] Content QA [DBPTK] Create SIARD [DBPTK] Create SIP [DBPTK] Export data & metadata [DBPTK] Instal DB from SIARD [DBPTK] Provide Ac es [DBPTK] Validate SIP [ElasticSearch] Search [ERMS] Export data & metadata [ERMS] Export data and metadata [File System] Export data and metadata [GEONetwork] Geo Search [GEOServer] View GEO DIP content [GIS] Export data and metadata [Kibana] Explore, Visualize, Discover [Omeka] Web Publish [Preservica] Create AIP [Preservica] Create DIP [Preservica] Manage Storage [Preservica] Manage Technical Metadata [Preservica] Preservation Plan ing [Preservica] Validate SIP [RDBMS] Export data and metadata [RDBMS] Export data and metadata (copy) [scopeArchiv] Metadata management [scopeIngest] Create AIP [scopeIngest] Prepare archival information [scopeIngest] Preservation Action [scopeIngest] Preservation Plan ing [scopeIngest] Validate SIP [USIP] Capture data and metadata [USIP] Create SIP [USIP] SIP Structure definit on [UVviewsoft] Universal Viewer [VAČ] Create/Adjust DIP [VAČ] Provide Ac es [VAČ] View DIP [VAČ] View unstructured data DIP content [VAU] Check availabil ty and rights [VAU] Manage Order [VAU] Proces Request [VAU] Provide Ac es Ac es ions Activ ty log Ap raisal / Select data and metadata Ap raisal and disposal Audio player Authentication Authority Records Check availabil ty and rights Cleanup Col ect Content (SIP)
RefArch [AIS] Ac es Catalogue [Archiv st's To lbox] [Astia] Ac es . Public ap lication [Astia] Virtual Archival Reading Ro m [Astra] Ap raisal & Clas if cation Ap lication [Astra] Submis ion Ap lication [CubeMAM] [dbDIPview] Ap lication [DBPTK] [DBPTK] Ap lication [DBPTK] Command [DGS] DIP Storage [ERMS] [ES Arch] Ac es [ES Arch] Actions [ES Arch] Administration [ES Arch] Archival Storage [ES Arch] Archive Maintenance [ES Arch] Data Management [ES Arch] EAIS [ES Arch] Finding & Viewing Aids [ES Arch] Ingest [ES Arch] Pre-Ingest [ES Arch] Services [ES Arch] System Administration Config [ES Arch] User set ings [ES Arch] Workflow Engine (Tasks/Actions) [External] Finding & Viewing Aids [External] Source Systems [FEDORA] AIP Storage [File server] AIP Storage [GEONetwork] Ap lication [GEOServer] Ap lication [LTO] AIP Storage [Preservica] Digital Preservation [RDBMS] Database [RODA] Pre-Ingest services [scopeOAIS] Archival IS [Unstructured content] [USIP] Pre-Ingest ap lication [VAČ] AC ES [VAČ] Basic Content Viewer [VAČ] Data Management [VAČ] Finding Aid [VAČ] Orders' Management [VAČ] Users' management [VAČ] Virtual Archival Reading Ro m [VAU] Finding Aids [VAU] Orders' Management [VAU] Sup ort and Consultation [VAU] Virtual Archival Reading Ro m Archival database (AHA ) AV System Commons IP Content ype validator CSIP Validators DBPTK Digital Preservation Service (SAPA) DIP Validators eArchiv ng To l Box (eATB) E-ARK Web E-ARK Web - Direct indexing and ac es to AIP ERMS ERMS export ES Arch File System GIS IP Viewer
Production Systems
7: The excerpt of a blueprint organized by the assessments distribute
This paper presents an advancement to the field of EA by addressing the critical need for efective tools/view models to enhance and maintain maturity models. By developing visual tools using the ATLAS platform, this research provides a novel approach to synthesizing complex data into comprehensible blueprints. These visual representations enable stakeholders to identify and rectify gaps, fostering a more intuitive understanding of the maturity model’s current state and areas requiring improvement. The alignment with the E-ARK project underscores the practical applicability of this research, demonstrating its relevance and potential impact. By integrating these visual tools with the E-ARK reference architecture and maturity model, the paper addresses the existing gaps between them and enhances the overall usability and efectiveness of maturity models.
Ultimately, this work aims to empower stakeholders to make more informed decisions and implement targeted improvements within their organizational structures. The comprehensive approach outlined in this paper not only maximizes the utility and impact of maturity models but also contributes to the broader goal of advancing EA practices. This paper represents a pivotal step towards more efective management and enhancement of maturity models, ensuring they fulfill their potential as valuable tools for organizational development and success.
In the end, we realized that two tasks could have been done diferently, which is now identified as future work: the assessments could have been imported by interpreting ATLAS Forms, creating a questionnaire that generates the same data as the manually importation that was done. Consequently, by filling in a questionnaire, the maturity assessment process would resemble the process that was used to generate the reports used to validate our solution. In addition, the second part of the solution, which had a diferent focus and did not allow the manipulation of colored flags, could have included a compliance analysis for the selected practical cases.
This work was funded by national funds through Fundação para a Ciência e a Tecnologia (FCT) (No: UIDB/50021/2020 (INESC-ID)), and the INESC-ID project E-ARK CSP (PR09033) and the eArchiving Common Services Platform - CNECT/LUX/2021/OP/0077 NUMBER – LC-01905904. [12] C. M. Pereira, P. Sousa, Enterprise architecture: business and it alignment, in: Proceedings of the 2005 ACM symposium on Applied computing, 2005, pp. 1344–1345. [13] M. Van Steenbergen, R. Bos, S. Brinkkemper, I. Van De Weerd, W. Bekkers, The design of focus area maturity models, in: Global Perspectives on Design Science Research: 5th International Conference, DESRIST 2010, St. Gallen, Switzerland, June 4-5, 2010. Proceedings. 5, Springer, 2010, pp. 317–332. [14] C. Gonzalez-Perez, T. McBride, B. Henderson-Sellers, A metamodel for assessable software development methodologies, Software Quality Journal 13 (2005) 195–214. [15] D. Proença, J. Borbinha, Enterprise architecture: A maturity model based on togaf adm, in: 2017 IEEE 19th Conference on Business Informatics (CBI), volume 01, 2017, pp. 257–266. doi:10.1109/ CBI.2017.38. [16] J. Ross, P. Weill, D. Robertson, Architecture as a strategy–creating a foundation for business execution, 2006. [17] K. D. Niemann, From enterprise architecture to IT governance, volume 1, Springer, 2006. [18] O. Group, Togaf® standard, version 9.2, 2018. [19] D. Greefhorst, E. Proper, D. Greefhorst, E. Proper, The role of enterprise architecture, Springer, 2011.