Entrepreneurship Through Open Data: An Opportunity for Sustainable Development

: Entrepreneurship and open data are key elements in the sustainable development ﬁeld, improving economic, social, and environmental dimensions. However, entrepreneurship and open data are barely studied together in the literature from a theoretical perspective. Therefore, this study identiﬁes the main themes in the previous studies and proposes a conceptual model for analyzing entrepreneurship through open data. For this purpose, a descriptive analysis and a co-word analysis were performed. Results show that the subject is multidisciplinary, and the main theme of study is how di ﬀ erent agents reuse information released by public administrations to generate new entrepreneurial initiatives, especially novel business models associated with new mobile applications. Open data sources, innovation, and business models are studied as critical factors for analyzing entrepreneurship through open data. Likewise, a conceptual model is presented and emerging themes for future research are proposed. Among them, the importance of encouraging collaboration between di ﬀ erent agents in the open data ecosystem for service development and improvement is emphasized. Our study identiﬁes an emerging theme that is still in an early phase: The study of sustainable entrepreneurship through open data as a value creation initiative to address global sustainable development. and Computer-Aided Software, D.C.-G.; Supervision, D.C.-G., E.-M.M.-V. and M.O.-d.-U.-C.; Validation, D.C.-G., E.-M.M.-V. and M.O.-d.-U.-C.; Visualization, D.C.-G., E.-M.M.-V. and M.O.-d.-U.-C.; Writing—original draft, D.C.-G., E.-M.M.-V. and M.O.-d.-U.-C.; Writing—review & editing, D.C.-G., E.-M.M.-V. and M.O.-d.-U.-C. All


Introduction
We live in a digital era to which governments, citizens, and companies are adapting at different speeds. Digital technologies foresee a new era in entrepreneurship, one in which the traditional ways and forms of pursuing entrepreneurial opportunities are increasingly questioned and refashioned [1]. In this scenario, entrepreneurial processes and outcomes have been transformed by new digital technologies [1], that have great impact on how new business ventures are created and developed [2]. In this sense, Elia et al. [2] (p. 1) state that "the arising technology paradigm is leveraging the potential of collaboration and collective intelligence to design and launch more robust and sustainable entrepreneurial initiatives". Digital context is also the arena in which open data are developing.
The economic, political, and social importance of open data has increased exponentially in recent years. The European Data Portal [3] defines open data as: "Data that anyone can access, use, and share. Governments, businesses and individuals can use open data to bring about social, economic, and environmental benefits". Zuiderwijk et al. [4] explain that open government ecosystems can help the decision-making and planning process. Open data ecosystems could be analyzed as business ecosystems, that is "an economic community supported by a foundation of interacting organizations and individuals-the organisms of the business world" [5] (p. 9). In addition, open data ecosystems
After answering these research questions, we will be better able to (a) know the main themes analyzed in the literature and their relationships (conceptual structure); (b) propose a conceptual framework for analyzing entrepreneurship through open data; and (c) orient new research about entrepreneurship through open data. Moreover, we identify an interesting future research line: The study of sustainable entrepreneurship through open data as a value creation initiative to address global sustainable development.

Methodology
A literature search was carried out using Web of Science (WoS) and Scopus databases, since they are the most relevant academic databases. They include a significant number of indexed journals [92]. The employed search protocols are shown in Table 2.

Indexes
All except chemistry databases -

Search
By "Topic" "Article title, Abstract, Keywords"

Filtering Process
Eliminated: 1 editorial, 1 conference paper (later published in a journal), and 6 documents that did not address this topic Eliminated: 5 conference reviews and 1 business article (the authors were not identified), 1 note, 1 conference paper (later published in a journal), and 7 documents that did not address this topic

Total Number of Documents From Both
Databases (for Entrepreneurship)

(after removing duplicates from both databases)
The bibliometric SciMAT software [93] was used for a co-word analysis and to identify the main topics related to this research area. Co-word analysis identifies relationships between ideas using models of co-occurrence of term pairs from a set of documents. Therefore, the relationships between the topics represented by the terms can be established [94]. Word filtering was carried out using the following criteria: • Initial number of keywords: 445. • Synonymous terms (e.g., "e-government" and "electronic government" were grouped as one keyword).

•
Terms that appear in their singular and plural forms (e.g., "hackathon," "hackathons") were grouped as the singular form.

•
Total number of keywords after filtering: 403.
Next, co-occurrence matrix and equivalence index calculations were carried out [95]. With these indices in mind, a simple centers algorithm [91] was used to create subgroups of terms with strong relationships, allowing identification of topics relevant to this line of research. Thematic networks with a maximum network size of 12 and a minimum size of 3 were then created. Callon et al. [95] proposed classifying each thematic network into one of the following groups: Well-developed and isolated themes; emerging or disappearing themes; basic and cross-sectional themes; and central themes, based on their measures of centrality and density for creating a strategic diagram.

Results
The number of documents combining entrepreneurship and open data published annually is shown in Figure 1. The first two documents were published in 2011; since 2013, the number of publications has increased. Furthermore, 62.3% of the documents were published in the last three years under analysis, with 13 in each of the last two years. Next, co-occurrence matrix and equivalence index calculations were carried out [95]. With these indices in mind, a simple centers algorithm [91] was used to create subgroups of terms with strong relationships, allowing identification of topics relevant to this line of research. Thematic networks with a maximum network size of 12 and a minimum size of 3 were then created. Callon et al. [95] proposed classifying each thematic network into one of the following groups: Well-developed and isolated themes; emerging or disappearing themes; basic and cross-sectional themes; and central themes, based on their measures of centrality and density for creating a strategic diagram.

Results
The number of documents combining entrepreneurship and open data published annually is shown in Figure 1. The first two documents were published in 2011; since 2013, the number of publications has increased. Furthermore, 62.3% of the documents were published in the last three years under analysis, with 13 in each of the last two years. To answer the first research question, an analysis of knowledge areas by document and author is presented.

Knowledge Areas by Document
Documents by type (article or conference paper) have been categorized by Journal Citation Report (JCR) and Scimago Journal and Country Rank (SJR) subject areas are shown in Tables  In contrast, Public Administration is highly relevant in the Social Sciences subject area, with Library and Information Sciences being the most notable category. The knowledge area Business Administration is also relevant and is primarily identified in the subject area of Business, Management, and Accounting; there are multiple associated categories, including Business, To answer the first research question, an analysis of knowledge areas by document and author is presented.

Knowledge Areas by Document
Documents by type (article or conference paper) have been categorized by Journal Citation Report (JCR) and Scimago Journal and Country Rank (SJR) subject areas are shown in Tables  In contrast, Public Administration is highly relevant in the Social Sciences subject area, with Library and Information Sciences being the most notable category. The knowledge area Business Administration is also relevant and is primarily identified in the subject area of Business, Management, and Accounting; there are multiple associated categories, including Business, Management and Accounting (miscellaneous), Business and International Management, Management Information Systems, and Management of Technology and Innovation.
Other knowledge areas also appear, such as Medicine, which is linked to the categories of Health Care Sciences and Services and Medical Informatics. Likewise, Agriculture is found within the Agricultural and Biological Sciences subject area, associated with the Agronomy and Crop Science and Animal Science and Zoology categories.

Knowledge Areas by Author
The seven authors with the highest number of publications are listed in Table 3 by affiliation and knowledge area. Lindman, from the University of Gothenburg, Sweden, has three documents and specializes in the knowledge areas of Information Technology, Information Systems, and Business Administration. His studies focus on the creation of new businesses using data from an open data ecosystem [24][25][26]. The main knowledge areas of the authors were also analyzed based on the JCR and SJR subject areas and categories. Several topics were studied within the knowledge areas of Information Technology, Computer Science and its derivatives, and Engineering. The influence of public open data or open government data is primarily analyzed with respect to the generation of new services and products through open innovation processes [96][97][98]. In addition, improvements in the usability of public open data have been analyzed with respect to the generation of new businesses through the open linked data format [99]. Some studies have also assessed the development of platforms that connect multiple agents, facilitating access to information and services, which favors innovation and entrepreneurship [100,101].
The effect of open data on the generation of new services and products is the primary subject of study in the knowledge areas of Public Administration and Business Administration. In the area of Public Administration, previous studies have primarily evaluated the role of open data portals as a support for reusing data [102,103] and the importance of the quality of open data with respect to its effective use [104]. In the knowledge area of Business Administration, attention was focused on the impact of open data on the creation of new businesses [24,105,106].
Finally, the creation of specific applications that use open data was investigated in the knowledge areas of Medicine and Agriculture. The development of mobile health applications based on open government data was studied specifically in the area of medicine [107]. Likewise, the development of Big Data applications was investigated in the knowledge area of Agriculture [108].

Main Topics of Study. Co-Word Analysis
To answer the second research question, the bibliometric technique of co-word analysis was used to identify different themes/topics and networks in the literature relating to open data and entrepreneurship. Science mapping uses co-occurrences among keywords to obtain thematic clusters [91].
Based on the strategic diagrams presented (Figure 2), "Public Sector" is the central theme. That is, it is characterized by a high degree of internal development and by strong ties with other concepts within a given field of research. The well-developed and isolated theme is "Public Sector Information". It has a high degree of internal development but is of marginal importance to the scientific area. Finally, "Open Data" is the basic and cross-sectional theme. It shows strong ties with other issues and is very relevant to the area of knowledge considered. No emerging or disappearing themes are identified in the co-word analysis.

Main Topics of Study. Co-Word Analysis
To answer the second research question, the bibliometric technique of co-word analysis was used to identify different themes/topics and networks in the literature relating to open data and entrepreneurship. Science mapping uses co-occurrences among keywords to obtain thematic clusters [91].
Based on the strategic diagrams presented (Figure 2), "Public Sector" is the central theme. That is, it is characterized by a high degree of internal development and by strong ties with other concepts within a given field of research. The well-developed and isolated theme is "Public Sector Information". It has a high degree of internal development but is of marginal importance to the scientific area. Finally, "Open Data" is the basic and cross-sectional theme. It shows strong ties with other issues and is very relevant to the area of knowledge considered. No emerging or disappearing themes are identified in the co-word analysis. In addition, for each theme, a subnetwork (Figures 3 and 4) is presented. Each subnetwork contains keywords that are related and form a topic. We have tagged each subnetwork with its most significant keyword.
-"Open data": This basic and cross-sectional theme has the highest number of documents (26) and the highest h-index (7).
The analysis of the subnetwork of the term demonstrates the relationships between the different terms and the main term ( Figure 3). The most important source of "Open Data" is "Government" because public administrations are providers of open data, specifically "Open Government Data", which are published in an open and machine readable format ("Government Data Processing") so as In addition, for each theme, a subnetwork (Figures 3 and 4) is presented. Each subnetwork contains keywords that are related and form a topic. We have tagged each subnetwork with its most significant keyword.
-"Open data": This basic and cross-sectional theme has the highest number of documents (26) and the highest h-index (7).
The analysis of the subnetwork of the term demonstrates the relationships between the different terms and the main term ( Figure 3). The most important source of "Open Data" is "Government" because public administrations are providers of open data, specifically "Open Government Data", which are published in an open and machine readable format ("Government Data Processing") so as to be available for "Re-Use" [109]. In a few cases, the "Re-Use" of these data occurs within an "Open Innovation" process that involves multiple agents [27,98,110].
to be available for "Re-Use" [109]. In a few cases, the "Re-Use" of these data occurs within an "Open Innovation" process that involves multiple agents [27,98,110]. Therefore, the "Open Data" ecosystem favors "Entrepreneurship" and "Innovation," and new "Business Models" are created by improving or creating novel services or products based on "Open Data" [6], such as new applications. Some of these actions are promoted through collaborative meetings, such as "Hackathons" [111]. These actions generate value, lending "Open Data" a positive "Economic" impact [109,112,113] and contributing to the "Transparency" of the public administrations that release them [113,114].
-"Public Sector": This central theme provided five documents and an h-index of 2. The term refers to different institutions, administrations, and organizations that form the public sector.
The analysis of the term subnetwork ( Figure 4) showed a significant relationship between the terms "Societies and Institutions" and "Knowledge Management", demonstrating that high-quality public services can be generated, and access of entrepreneurs and citizens to data can be improved [114]. There was also a relationship between the terms "Open Government" and "e-Government." The latter is part of the concept of openness shown by the "Open Government" in electronically giving citizen access to information and services provided by the government and other public administrations ("Public Sector") [114,115]. Therefore, the "Open Data" ecosystem favors "Entrepreneurship" and "Innovation," and new "Business Models" are created by improving or creating novel services or products based on "Open Data" [6], such as new applications. Some of these actions are promoted through collaborative meetings, such as "Hackathons" [111]. These actions generate value, lending "Open Data" a positive "Economic" impact [109,112,113] and contributing to the "Transparency" of the public administrations that release them [113,114].
-"Public Sector": This central theme provided five documents and an h-index of 2. The term refers to different institutions, administrations, and organizations that form the public sector.
The analysis of the term subnetwork ( Figure 4) showed a significant relationship between the terms "Societies and Institutions" and "Knowledge Management", demonstrating that high-quality public services can be generated, and access of entrepreneurs and citizens to data can be improved [114]. There was also a relationship between the terms "Open Government" and "e-Government." The latter is part of the concept of openness shown by the "Open Government" in electronically giving citizen access to information and services provided by the government and other public administrations ("Public Sector") [114,115].
Finally, there was a relationship between "Artificial Intelligence" and the main term, indicating the introduction of "Artificial Intelligence" technologies to create a platform that uses open data to assist public administrations, citizens, private entrepreneurs, and experts in multiple fields of study; this improves decision-making with respect to the valuation and adaptive reuse of cultural heritage ("Public Sector") [100].  Finally, there was a relationship between "Artificial Intelligence" and the main term, indicating the introduction of "Artificial Intelligence" technologies to create a platform that uses open data to assist public administrations, citizens, private entrepreneurs, and experts in multiple fields of study; this improves decision-making with respect to the valuation and adaptive reuse of cultural heritage ("Public Sector") [100].
-"Public Sector Information": This theme is well-developed and isolated, with three documents and an h-index of 2. The term refers to the information provided by different institutions, administrations, and organizations that constitute the public sector.
The study of the term subnetwork ( Figure 4) demonstrates a strong relationship between the main term and both "Copyright" and "Surveys" because of the execution of "Surveys" of various public institutions to improve open government initiatives and present open government data in an open licensing format; this takes into consideration the fact that the data released by the public sector ("Public Sector Information") and governments are sometimes under "Copyright" and, therefore, must be released under certain licenses that allow their reuse [116].

Discussion
To answer the third research question we have identified the key elements for engaging in entrepreneurship using open data. The elements were identified using the results obtained from the subnetwork of the basic and cross-sectional theme, "Open Data" (Figure 3). This is the most relevant theme to the area of knowledge considered.
We have identified three key elements in the study of entrepreneurship through open data: (1) Open data sources, (2) innovation, and (3) business models. We have developed a discussion of each element, and we have proposed a conceptual model for analyzing entrepreneurship through open data.
-Open data sources: The literature focuses on the study of open data released by public administrations, which is the main source of open data for generating new businesses and services [97,98]. These data are usually published in open data portals, facilitating their reuse in generating new services, such as applications [102,117]. Nonetheless, few studies have evaluated the development of entrepreneurial initiatives based on open data from companies, except for some that analyzed open data released by entrepreneurs and their effect on the open data ecosystem [25]. Sadiq and Indulska [104] have shown that there is no consensus on what open data quality means. -"Public Sector Information": This theme is well-developed and isolated, with three documents and an h-index of 2. The term refers to the information provided by different institutions, administrations, and organizations that constitute the public sector.
The study of the term subnetwork ( Figure 4) demonstrates a strong relationship between the main term and both "Copyright" and "Surveys" because of the execution of "Surveys" of various public institutions to improve open government initiatives and present open government data in an open licensing format; this takes into consideration the fact that the data released by the public sector ("Public Sector Information") and governments are sometimes under "Copyright" and, therefore, must be released under certain licenses that allow their reuse [116].

Discussion
To answer the third research question we have identified the key elements for engaging in entrepreneurship using open data. The elements were identified using the results obtained from the subnetwork of the basic and cross-sectional theme, "Open Data" (Figure 3). This is the most relevant theme to the area of knowledge considered.
We have identified three key elements in the study of entrepreneurship through open data: (1) Open data sources, (2) innovation, and (3) business models. We have developed a discussion of each element, and we have proposed a conceptual model for analyzing entrepreneurship through open data.
-Open data sources: The literature focuses on the study of open data released by public administrations, which is the main source of open data for generating new businesses and services [97,98]. These data are usually published in open data portals, facilitating their reuse in generating new services, such as applications [102,117]. Nonetheless, few studies have evaluated the development of entrepreneurial initiatives based on open data from companies, except for some that analyzed open data released by entrepreneurs and their effect on the open data ecosystem [25]. Sadiq and Indulska [104] have shown that there is no consensus on what open data quality means.
Therefore, additional studies are necessary in order to analyze the effective use of open data for creating new businesses. In addition, it is generally necessary to develop studies that thoroughly identify and classify types of open data and applications developed by entrepreneurs. In contrast, several studies have used open data from crowdfunding platforms to elucidate this phenomenon and entrepreneurial initiatives, consolidating these topics as a new area of study [118,119].
-Innovation: The main topic of study in the literature is the reuse of open data and its impact on the generation of new entrepreneurial initiatives, with a focus on new businesses based on services and applications in different fields. These studies evaluated hackathons and the innovation they generate, favoring contacts between entrepreneurs and companies and encouraging the generation of applications based on open data, thereby creating start-ups based on these applications [110,111]. Kitsios and Kamariotou [105] reported that, generally speaking, more research and development of guidelines were required for hackathon organizers to efficiently meet the needs of participants. In turn, Kitsios and Kamariotou [111] stressed the need to develop a public catalog consisting of the most demanded open data.
Similarly, Kitsios and Kamariotou [105] have shown that hackathons are only the first phase of application development, and that knowledge about their collaborative development should be expanded. In this respect, research has also focused on the collaborative ecosystem that generates open innovation, in which public entities encourage entrepreneurs and citizens to collaborate with each other to develop specific services and applications [11]. In this context, users of services are the main players involved in providing high-quality services. Authors like Smith and Sandberg [97] highlight the need to focus on the innovation ecosystem for open government data users, which favors entrepreneurial initiatives.
-Business models: The literature has primarily focused on the relationships and collaboration between the different agents of the open data ecosystem and the development of entrepreneurial initiatives. In this respect, the elements necessary to build an open data business model through the Canvas model have been analyzed [6,27]. Some studies have used different classifications of open data business models [27].
Among those authors who study open data and business models, Marijn Janssen from the Delf University of Technology in the Netherlands has authored the highest number of documents (5). Janssen's publications have analyzed the efficient use of open data that yields benefits to public and private entities, thereby generating value through innovation and allowing the development of new business models [120][121][122][123][124]. While these publications primarily investigate the generation of value through innovation using open data released by public entities, one of them proposes a decision support framework for opening data by private entities in order to generate an open data ecosystem that would improve transparency, innovation, and the generation of new business models; this in turn would benefit various actors, including the private and public sectors and academia [121]. This research stresses that, because of uncertainty, open data business models need to be constantly reviewed and remade to adapt to changes in the environment [123].
The absence of emerging themes in the strategic diagram is notable ( Figure 2). Thus, it is interesting to propose some emerging themes. To do that, we have conducted a qualitative analysis of the previous literature considering our co-word analysis. Based on these analyses, we have identified several factors that affect entrepreneurship through open data and proposed a conceptual model for analyzing entrepreneurship through open data (Table 4). Our starting point is that "entrepreneurship research has ignored the role that digital technologies play in entrepreneurship and the role that users and agents play in digital entrepreneurship" [28] (p. 56). In this sense, the concept of digital entrepreneurship ecosystem is mostly new [2]. Otherwise, open data ecosystem is considered as a business and digital ecosystem. Then, a new proposal for understanding the entrepreneurship through open data as ecosystem can be developed: "open data entrepreneurship ecosystem".
The model proposed in Table 4 shows the different aspects to be considered to understand entrepreneurship through open data, grouped by key elements. The first element, context, is determined by the theories and principles (open government and e-government) that govern the open data world and by the combination of the business and open data ecosystems. There are two specific applications. One that shows significant study is the smart city. The other is sustainable development, which is an emerging theme.
Second, we have to consider the necessary inputs for the entrepreneurial process, which in this case are data: Open government data, linked data, and big data. Various processes are then applied to these data to carry out entrepreneurial actions. Entities must manage the information, apply reuse actions, and consider innovation processes, especially open innovation and its possible development through tools such as hackathons. All this gives rise to outputs, that is, products/services, and apps that allow entities to define and delimit the business model. Finally, the phenomenon of entrepreneurship through open data by combining different areas and applications has an impact in the social, economic, environmental, and political spheres.
Third, taking into account the absence of emerging themes about these topics in the strategic diagram, some emerging themes for future studies have been identified. We comment on these emerging themes below.
More studies on the relationship between entrepreneurship and the concepts of open government and e-government are necessary. Smith and Sandberg [97] have analyzed the effect of barriers to innovation on the use of open government data by various agents, including entrepreneurs. However, future studies will have to determine the types of open government data released by public administrations and classify the data used in open data portals by entrepreneurs, correlating them with the type of products, services, applications, or business models developed. This information is key for decision making and the development of new entrepreneurial activities. In addition, few studies have specifically assessed the importance of open data for the smart city ecosystem with regards to generating entrepreneurial initiatives.
There are studies, including that of Rojas et al. [106], which have jointly assessed open data and big data and have established certain connections with the development of new businesses. In this respect, released open data are not always in a structured format that favors their reuse. Gandomi and Haider [125] have shown that 95% of big data has an unstructured format.
Although studies have analyzed the type of machine-readable data format of open data released by public administrations in open data portals [102], further studies should work to resolve the problem of open data released in an unstructured format.
Furthermore, although previous studies have shown that big data create new opportunities for entrepreneurship [126], the use of big data technologies should be further investigated to standardize data format and allow their effective reuse. This approach could enhance entrepreneurship and the generation of new business models based on the development of digital services, such as applications.
Therefore, open data should be in a structured format appropriate for reuse, as is the case of linked data [117,[127][128][129], thereby allowing their effective reuse by application developers. In this respect, the lack of consensus on the quality of open data should be addressed, as highlighted by Sadiq and Indulska [104]. In this sense, it is necessary that more studies analyze the datasets used by entrepreneurs in open format, assessing the degree of compliance with fundamental principles of open government data [130] as the first step in determining the quality of released open data. In this respect, entrepreneurs can use open data sources that allow a more effective reuse of data to create new products or services, such as applications.
It should be emphasized that while there is research like that of Kitsios et al. [6], which evaluates the open data ecosystem from a business perspective, more studies are needed that elucidate the concept of the so-called business ecosystem within the open data ecosystem. While most open data come from public administrations, some open data is released by the private sector as well. The literature should further investigate the use of open data coming from companies as a factor that promotes entrepreneurship, adding to the existing research on the equivalent role that open government data plays [25]. Questions like the following need to be addressed to encourage entrepreneurship from this perspective: (1) What kinds of products, services, applications, or business models can be developed through the innovative reuse or management of open data coming from the private sector? (2)  This study also compared open data business models with open source models using information collected by entrepreneurs, given the need for more studies that focus jointly on the development of data and on the development of applications through said data [24].
Although some authors, such as Ramos [113], have tried to address questions like "how successful are government actions in supporting economic development through open data?" generally, few studies have quantitatively measured the potential social, economic, environmental, and political impact of open data on the development of entrepreneurial activities.
Finally, there is a lack of articles focused on the influence of entrepreneurial initiatives through open data on the different dimensions that make up the sustainability concept. The context of sustainable development for entrepreneurship through open data is an interesting emerging theme that remains in an early research phase. Sustainable development is a topic that has been increasingly researched and applied by academics and practitioners in recent decades [131]. Sustainable development has a two-part application in our model. On the one hand, it offers a new context for the study of entrepreneurship through open data. On the other hand, it affects the impact of this phenomenon, especially in the environmental, social, and economic spheres. Some authors have shown an interest in studying the emerging field of sustainable entrepreneurship [79][80][81][82][83][84][85][86][87][88]. Entrepreneurs are increasingly aware of sustainability, introducing new sustainable services and products to provide social and environmental value [132,133]. According to Muñoz and Cohen [83] (p. 300), "The recognition of entrepreneurship as a solution to, rather than a cause of, environmental degradation and social inequality moved the field to identify a new type of entrepreneurial activity, namely sustainable entrepreneurship". Sustainable entrepreneurship applies the entrepreneurial approach to achieve societal and environmental goals [81]. Therefore, sustainable entrepreneurship can be defined as "the examination of how opportunities to bring into existence 'future' goods and services are discovered, created, and exploited, by whom, and with what economic, psychological, social, and environmental consequences" [134] (p. 35).
According to Hall et al. [21] sustainable development implies that renewable resources should be used wherever possible and it seeks to place social, environmental, and economic objectives (triple bottom line). In this context, open data are free and accessible and can be reused [6], allowing a sustainable development of new business. Lindman et al. [25] highlight the importance of open data entrepreneurship in order to create new services and sustainable value networks based in open data released by governments. The release of open data by public administrations such as governments promotes more transparent and accountable institutions, with this being important for social development and sustainable development [135]. However, we have observed a lack of works that study the generation of entrepreneurial initiatives through open data from a sustainable development perspective. Thus, sustainable entrepreneurship through open data constitutes a new phenomenon to be studied.
We have seen that open data can foster sustainable development as an instrument that allows the connection and involvement of society stakeholders [7,8] via co-creative open innovation processes [9][10][11][12]. In addition, sustainability is a concept that presents three main dimensions: Environmental, social, and economic [136]. Sustainable development initiatives improve these three dimensions, fostering innovation and collaboration between stakeholders of the socio-economic system in order to achieve their main objectives [136][137][138][139]. In addition, we have adapted the Elia et al. [140] framework to define responses to sustainable development challenges; then, five dimensions can be analyzed: (1) What (participating sides, actors, and groups), (2) who (actions, flows, and coordination mechanisms; (3) how (actions); (4) why (value drivers, benefits, and externalities); and (5) governance (rules regulating the affiliation and interaction processes). Therefore, studies that analyze the impact of sustainable entrepreneurship through open data can be an interesting new field of research.

Conclusions
This study identifies the main knowledge areas in which research into entrepreneurship through open data has been carried out (first research question). The JCR and SJR subject areas and categories were used as a basis, with most relating to the Information Technology and Computer Sciences knowledge areas. However, the subject is multidisciplinary, and other knowledge areas are present as well, including Public Administration, Engineering, Business Administration, Medicine, and Agriculture.
In addition, a co-word analysis was performed to identify relevant themes/topics and the relationships between them, as well as the key elements to engage in entrepreneurship through open data (second research question). The main subject under study is how entrepreneurial initiatives can be generated using information openly published by public administrations and reused by other agents, wherein these initiatives are primarily new business models based on new mobile applications. Three elements are critical for entrepreneurship through open data: Open data sources, innovation, and business models. Finally, a conceptual model for analyzing entrepreneurship based on open data is developed (third research question). This model allows us to propose emerging themes for future research lines.
Two academic contributions are derived from this paper. First, we have proposed a conceptual model focused on entrepreneurship through open data that presents a new combination of ecosystems in a digital context: "open data entrepreneurship ecosystem". This model constitutes a guide for researchers interested in both lines of research. Second, and due to the absence of emerging themes about these subjects, new emerging research topics are proposed. Future research should consider our proposals. For example, sustainable entrepreneurship through open data can be a value creation initiative to address global sustainable development. The main objective of sustainable development is "the long-term stability of economic systems, through the integration of environmental and social concerns throughout the policy and decision-making process" [140] (p. 1). A growing number of organizations operate in an environmentally and socially responsible manner, with stakeholders expecting this attitude from them [141]. Thus, sustainability is an important aspect in current business operations, with entrepreneurship and innovation appearing as key elements in the sustainable development field [131]. In this sense, sustainable development could be considered as an arena for innovation and an entrepreneurship field [140]. Further

Conflicts of Interest:
The authors declare no conflict of interest.

Appendix A
Documents by type (article or conference paper) have been categorized by JCR and SJR subject areas.