Owner's Responsibilities of Vehicles Used as Illegal Public Transport When Traffic Accidents Happened

The research objectives to be taken in the intended research plan are as follows: To know and analyzecriminal law construction for owners of vehicles used as public transportation or commercialized. To find out and analyzeconstruction of criminal law is the responsibility of owners of vehicles commercialized as public transportation. To find out and analyzesolution to the problem of responsibility of vehicle owners who commercialize their vehicles illegally when a traffic accident occurs on the highway. The method used by researchers isjuridical sociological approach to law and the specification in this research is including analytical descriptive. Based on the results of that research Construction based on criminal law Act No. 22 of 2009 concerningTraffic and road transportArticle 308 is a sanction for every person driving a public motorized vehicle not equipped with a license to carry out person transportation/not having a route. The construction of liability criminal law is based on Act No. 22 of 2009 concerningTraffic and road transport Article 315 states that when a criminal offense is committed by a Public Transportation Company, the criminal liability is imposed on the Public Transportation Company by adding a maximum fine of 3 (three) times the fines specified in each article and also subject to additional penalties in the form of temporary suspension or revocation transport operating license for the vehicle used.The obstacles: there are no articles in the Road Traffic and Transportation Act No. 22 of 2009 that can be used to ensnare vehicle owners. The solution is to hope that this article will exist so that in the future it can create a deterrent effect for vehicle owners so that they do not go around operating their vehicle without being equipped with existing terms and conditions in accordance with the law and in the future it is also expected to prevent the occurrence of traffic accident victims in large numbers.

Introduction
Road traffic and transportation have a strategic role in supporting national development and integration as part of efforts to advance public welfare as mandated by the 1945 Constitution of the Republic of Indonesia (hereinafter referred to as the 1945 Constitution of the Republic of Indonesia). As part of the national transportation system, road traffic and transportation must develop their potential and role in realizing security, welfare, traffic order and road transportation in the framework of supporting economic development and the development of science and technology, regional autonomy, and accountability for State administration. 1 ║ 2 In the framework of administering road traffic and transportation, Act No. 22 of 2009 concerning Road Traffic and Transportation (hereinafter abbreviated to Law on Road Traffic and Transportation) has been established which regulates several provisions including those related to the purpose of managing traffic and road transportation, division of authority between government agencies and regional governments, regulating matters of a technical nature to road traffic and road transportation operations, road traffic and transportation infrastructure, as well as efforts to develop, prevent, regulate and enforce laws. The Law on LLAJ states that there are three objectives for the implementation of Road Traffic and Transportation, namely: a. the realization of Traffic and Road Transportation services that are safe, secure, orderly, smooth, and integrated with other modes of transportation to encourage the national economy, promote public welfare, strengthen national unity and integrity, and be able to uphold national dignity; b. the realization of traffic ethics and national culture; and c. the realization of law enforcement and legal certainty for the community. 2 In its implementation, the Law on LLAJ has not been able to accommodate developments, problems and legal needs in society. Changes that occur in society in the context of road traffic and transportation occur so rapidly that they go beyond the existing Law on LLAJ. These changes should be followed by changes in existing legal rules so that conditions in society can be accommodated by law. In legal science, this concept is known as formal legal politics which aims to "make the ius constitutum developed from the old legal systems into ius constituendum or law for the future". 3 Transportation is a common thing in many places. All regions in Indonesia have a means of transportation that connects one place to another. The importance of transportation for the people of Indonesia is due to several factors, among others, the geographical condition of Indonesia which consists of thousands of small and large islands, waters which consist of most of the sea, rivers and lakes which allow transportation to be carried out by land, water and air to reach the entire territory. Indonesia. 4 The occurrence of traffic accidents, is not only contained in Article 240 of the Road Traffic and Transportation Law but is also regulated in the Law on Traffic and Road Transportation in Chapter XIV, the third part regarding obligations and responsibilities and paragraph 1 regarding the obligations and responsibilities of drivers, owners of motorized vehicles , and/or transportation companies, in Article 234 it is explained that drivers, motorized vehicle owners and/or public transport companies are responsible for losses suffered by passengers and/or goods owners and/or third parties due to the driver's negligence. Settlement of traffic accidents found on the streets at certain times and is considered a routine activity, because it is more of an administrative service. In the field of vehicles, apart from that, the discipline of road users is still very low. If physically there are no Volume  ║ 3 members of the Police/Traffic Police there is a tendency to commit violations by violating traffic signs. 5 The research objectives to be taken in the intended research plan are as follows: To know and analyzecriminal law construction for owners of vehicles used as public transportation or commercialized. To find out and analyzeconstruction of criminal law is the responsibility of owners of vehicles commercialized as public transportation. To find out and analyzesolution to the problem of responsibility of vehicle owners who commercialize their vehicles illegally when a traffic accident occurs on the highway.

Research methods
Through a sociological juridical approach, it means that an approach is carried out directly in the field. This research is a descriptive legal research.And secondary data obtained from literature study. The data were analyzed qualitatively.

Criminal Law Construction for Vehicle Owners Used As Public Or Commercial Transport
Law exists in every human society anywhere on this earth. However primitive and how modern a society must have laws. Therefore, the existence (existence) of law is universal. Law cannot be separated from society, but in fact has a reciprocal relationship. 6 The history of traffic in Indonesia cannot be separated from the development of world automotive technology which originated from the discovery of engines with petroleum fuels. During the era of the Dutch East Indies government which then ruled Indonesia, it began to bring 4-wheeled and 2-wheeled vehicles to Indonesia, causing traffic activity. 7 Traffic in Law No. 22 of 2009 is defined as the movement of vehicles and people in the road traffic space, while what is meant by road traffic space is infrastructure designated for moving vehicles, people, and/or goods in the form of roads and supporting facilities. The government has a goal of realizing safe, secure, fast, smooth, orderly and orderly road traffic and transportation, convenient and efficient through traffic management and traffic engineering. The procedure for traffic on the road is regulated by statutory regulations regarding traffic direction, priority to use roads, traffic lanes, traffic lanes and control of flow at intersections. 8 5  Whereas in the case of then that is the vehicle. The microbus elf is a private property, not a public transport company or managed by a company with legal status. And this article is only an administrative violation, not a crime or crime. Criminal law construction for owners of vehicles used as public transportation or commercialized based on Act No. 22 of 2009 concerningTraffic and road transportArticle 308 is a sanction for every person driving a public motorized vehicle not equipped with a license to carry out person transportation/not having a route. This article applies to every driver, not to the owner of the vehicle and this Article is only a violation, not a crime.

Construction of Criminal Law Liability of Owners of Vehicles Commercialized as Public Transportation
A traffic accident according to Act No. 22 Year 2009 Article 1 paragraph (24) is an incident on the road which is unexpected and accidentally involves a vehicle with or without other road users which results in human casualties and/or property. Traffic is the movement of vehicles and people in road traffic spaces. Accidents can cause mild to severe impacts, both material and non-material, human victims and property loss. 9 The existence of an accident is a driver's fault factor in the absence of a sense of caution and negligence in driving the vehicle. It can be said that the vehicle driver's mistake which results in death can be said that the person has committed a criminal act. 10 . It is understandable why the carrier (operator) is responsible for the passengers. Because the control over the transportation equipment rests with the operator both in operating, maintenance, including the safety of the transportation equipment. The operator is primarily responsible for doing this. The passenger position is passive. All you have to do is pay the freight, get on the vehicle and the rest will leave your fate to the operator to deliver it to its destination. 11 However, in public transportation, it is not only the drivers who are blamed for causing traffic accidents. Entrepreneurs or public transport companies that employ other people to become drivers or crew of their vehicles are also obliged to be responsible for any loss of traffic accidents caused by the actions of the driver or vehicle crew. concerningTraffic and road transport Article 315 states that when a criminal offense is committed by a Public Transportation Company, the criminal responsibility is imposed on the Public Transportation Company and/or its management by adding a maximum fine of 3 (three) times the fines specified in each article and also subject to additional penalties in the form of temporary freezing or revocation of transportation operation permit for used vehicles.

Solution to the Constraints and Responsibilities of Vehicle Owners Who Commercialize Their Vehicles Illegally When a Traffic Accident Occurs on the Highway
The fatality rate of a traffic accident is measured by the result of the accident the more victims who die as a result of the accident, the higher the fatality of the traffic accident. This fatality rate is measured by certain coefficients. Likewise in taking steps to reduce the number of accidents, the fatality rate of an accident must be reduced, of 12  course by paying attention to and prioritizing the safety factor in driving by complying with applicable regulations. 16 Public transportation is a means of transportation that is used by the community together by paying tariffs. Public transportation is the opposite of 'private vehicle'. Public transportation plays a role in meeting human needs for increased movement or mobility, to move from one place to another which is close, medium or far away. Public transport also plays a role in traffic control, fuel or energy savings, as well as regional planning & development. 17 Obstacles faced by investigators when conducting an investigation that leads to the owner the vehicle is the absence of Articles in the Law on Traffic and Road Transportation Number 22 of 2009 which can be used to ensnare the owner of the Microbus Elf vehicle as a suspect or person who has a role or person who can be held criminally responsible in the occurrence of a traffic accident the cross, given the large number o f casualties and large material losses. Traffic offenders still do not have a deterrent effect because until now there are still many traffic violations, lack of personnel to carry out their duties, and insufficient number of officers. There are still people who don't know about traffic rules. 18 Solution to the constraints of the responsibility of vehicle owners who commercialize their vehicles illegally when a traffic accident occurs on the highway, namely We hope that this article will have a deterrent effect on vehicle owners so that they do not operate their vehicle arbitrarily without being equipped with the existing terms and conditions in accordance with the law and in the future it is also hoped that it can prevent traffic accident victims in large numbers. The fact is that there are still many vehicle owners who operate their vehicles like travel vehicles even though the fact is that they are not equipped with a valid license and there is no legality.

Closing
Based on the description above, it can be concluded that ║ 7 revocation of transportation operation permit for used vehicles. Solution to the constraints of the responsibility of vehicle owners who commercialize their vehicles illegally when a traffic accident occurs on the highway.The obstacles: there are no articles in the Road Traffic and Transportation Act No. 22 of 2009 that can be used to ensnare the owner of the vehicle as a suspect or person who has a role or person who can be held criminally responsible in the traffic accident, given the number of heavy casualties and huge material losses. The solution is to hope that this article will exist so that in the future it can create a deterrent effect for vehicle owners so that they do not go around operating their vehicle without being equipped with existing terms and conditions in accordance with the law and in the future it is also expected to prevent the occurrence of traffic accident victims in large numbers. There is awareness for owners of private vehicles that are used as public transportation that do not have a route permit because their actions have caused losses to the Government and the Community, Owners of private vehicles should comply with all applicable procedures or provisions before making their vehicles. As a public transportation, the Department of Transportation, Communication and Information Technology must always socialize and apply the existence of Law of the Republic of Indonesia Number 22 of 2009 concerning Road Traffic and Transportation to owners of private vehicles that are used as public transportation without a route permit.


s2fieldsofstudy:
Computer Science
Art

text:
Challenges in Designing Natural Language Interfaces for Complex Visual Models

Intuitive interaction with visual models becomes an increasingly important task in the field of Visualization (VIS) and verbal interaction represents a significant aspect of it. Vice versa, modeling verbal interaction in visual environments is a major trend in ongoing research in NLP. To date, research on Language & Vision, however, mostly happens at the intersection of NLP and Computer Vision (CV), and much less at the intersection of NLP and Visualization, which is an important area in Human-Computer Interaction (HCI). This paper presents a brief survey of recent work on interactive tasks and set-ups in NLP and Visualization. We discuss the respective methods, show interesting gaps, and conclude by suggesting neural, visually grounded dialogue modeling as a promising potential for NLIs for visual models.

Introduction
In recent years, research in NLP has become more and more interested in data sets, tasks and models that pair Language and Vision, cf. work on image Captioning (Vinyals et al., 2015;Herdade et al., 2019;He et al., 2020), Visual Question Answering (Antol et al., 2015;Goyal et al., 2017;Kazemi and Elqursh, 2017), or Instruction Following and -Generation in visual domains (Fried et al., 2017(Fried et al., , 2018. This new area is generally called Vision & Language (Mogadala et al., 2019), but it is actually based mostly on combining methods from NLP (like e.g. language models) and Computer Vision, e.g. visual analysis and recognition models for encoding visual input like images. Methods and models from the research area of Visualization -which investigates solutions for modelling, exploring, analyzing and communicating data by using visual technologies and can be seen as the field of visual synthesis -are, to the best of our knowledge, less well known in the NLP community.
In the VIS community, interaction with visual models plays an important role and natural language interaction represents a big part of it (Bacci et al., 2020;. Natural Language Interfaces (NLIs) that support interactive visualizations based on language queries have found increasing interest in recent research (Narechania et al., 2020;Yu and Silva, 2020;. However, from an NLP point of view, the methods applied in these recent interfaces, mostly rely on established methods for implementing semantic parsers that map natural language instructions to symbolic data base queries, which are consecutively visualized by a visualization pipeline. In this paper, we argue that there is space for further support of intuitive interaction with visual models using state-of-the-art NLP methods that would also pose novel and interesting challenges for both domains. We focus this brief overview on a selection of methods for modeling interaction in the fields of NLP and VIS based on recent submissions to the top conferences ACL, EACL, VIS and EuroVIS. First, we briefly describe how interaction is understood in the respective fields (Section 2). We provide a short overview of recent, state-of-the-art systems related to interaction with visual models or in visual environments (Section 3). Finally, we discuss potential research gaps and challenges that could be addressed in future work on modelling interaction with visual models (Section 4). As interaction is a major research topic in both NLP and VIS, we do not aim for a complete survey, but we hope to make readers from both communities aware that there could be fruitful directions for collaboration. Hornbaek and Oulasvirta (2017). Work on interaction in NLP typically investigates verbal communication between human dialogue partners and models dialogue systems that interact with users via natural language, but also recognizes the fact that verbal communication typically happens in combination with other modalities, like touch, movements and gestures in embodied dialogue or gaze and visual stimuli in visual dialogue (Cuayáhuitl et al., 2015). In HCI and VIS, interaction via multiple modalities plays a very prominent role, i.e. involves gestures, movements, different input controllers, screens, gazes, modalities and more. The interaction between a user and a visual model is a key aspect of many VIS tasks and applications and impacts on the user evaluation of a visual model to a significant degree (Yi et al., 2007;Tominski, 2015;Figueiras, 2015).

Interaction in VIS
Generally speaking, the field of VIS is interested in the development of techniques for creating visual models (Brehmer and Munzner, 2013;Liu et al., 2014;Amar et al., 2005). A visual model is data that is mapped into a visually perceivable space by representing concepts in the data through visual concepts to make them easily perceivable and understandable by humans. This supports research and education in many aspects as well as data exploration and understanding of big data sets. Research on interaction in VIS often addresses the design of appropriate human-computer interfaces and the abilities they need to offer for interacting with a visual model. Natural Language Interfaces (NLIs), in this context, can be seen as one possible solution of enabling interaction with a visualization. Dimara and Perin (2019) provide a comprehensive study on how interaction is seen in VIS by defining it as "the interplay between a person and a data interface involving a data-related intent, at least one action from the person and an interface reaction that is perceived as such". The authors deliberately distinguish their view from the HCI definition of interaction as stated in Hornbaek and Oulasvirta (2017), by making the importance of the data related intent of the user the focus in VIS. As a conclusion, the authors observe that approaches towards interaction in VIS currently lack two points, i.e. flexibility and a better understanding of the user goal. The lack of these currently leads to interfaces that are too predictable, unsatisfying in their capacities to act or risk misdirected interactions with visual models. Despite that, Hornbaek and Oulasvirta (2017) and Dimara and Perin (2019) both argue that interaction foremost represents a form of dialogue which the authors evaluate in terms of its "naturalness" and its mutual "strong sense of understanding".
This highlights the point that interaction with a visual model is fundamentally conceived as a multi-modal process that leverages various different interface modalities for communication and information exchange. As discussed below, from an NLP perspective, interactions with systems in VIS can be seen as multi-modal dialogues between a system and a user having data-related goals.

Interaction in NLP
Work in NLP often aims at understanding and modeling how dialogue partners collaborate and achieve common ground by exchanging verbal utterances (potentially in combination with different modalities, like e.g. vision). This typically involves language understanding, dialogue management (reasoning over latent user goals) and language generation (Young et al., 2010(Young et al., , 2013. Recent work on dialogue has turned more and more to so-called neural end-to-end-dialogue systems that do not separate processes of understanding, reasoning and generation, and aim for more flexibility and adaptiveness (Santhanam and Shaikh, 2019). Santhanam and Shaikh (2019) distinguish between goal-driven and open dialogue systems as they address fundamentally different interaction and evaluation set-ups. Goal-or task-oriented systems are typically designed towards helping the user to achieve a very specific goal in a given context. For instance, in instruction-following and -generation (Fried et al., 2017(Fried et al., , 2018, a user or system needs to reach a specific position in an environment by following navigation instructions. Here, the interaction is often asymmetric in the sense that the modalities to be used by the partners are very restricted (the instruction follower acts, the giver speaks). Open-domain dialogue systems, like Li et al. (2017); Adiwardana et al. (2020) are not bound to a goal and therefore require a high awareness of context, personality and variety of the dialogue system as Santhanam and Shaikh (2019) point out.

Natural Language Interfaces in VIS
A range of recent papers have looked into integrating NLP in VIS systems, by implementing NLIs that translate a natural language query to a visualization command in some programming language. This allows users to "talk to some dataset", as illustrated in Figure 1. Existing NLIs are applied in systems that create and manipulate, e.g., chart visualizations (Shao and Nakashole, 2020). Similar interfaces are proposed in Narechania et al. These existing NLIs are mostly applied in the field of visual analytics. Here, the user has a concrete goal in mind, i.e. some manipulation of the underlying data table (e.g. aggregation, filtering). Dimara and Perin (2019) point out that the exact understanding of the users' goal is important in these interfaces and one current approach for improving the inference of the users' intent is to predict it based on activity logs. Setlur and Kumar (2020)'s work suggests that the handling of vague subjective modifiers in utterances can be improved by using sentiment analysis techniques.
In terms of NLP methods, these interfaces are mostly based on manually engineered grammars that parse user input to queries and then generate an appropriate visualization output, as e.g. in (Yu and Silva, 2020). These grammars are relatively easy to set-up even for non-experts (of NLP) and do not require large amounts of training data, as most state-of-the-art dialogue systems developed in NLP. An important limitation of this approach, however, is that such semantic grammars are designed to translate directly between a given user query in natural language and some underlying data query language like e.g. SQL. This means that, in longer multi-turn interactions between a user and a system, users are not able to formulate short, intuitive queries that implicitly refer to the context (e.g. "now, make this a bit bigger" where "this" refers to an aspect of the visual model discussed in the preceding context) or multi-modal queries (e.g. "increase the volume of this particle here" while user points to a region on the screen). Finally, and most importantly, they assume that the user can precisely formulate or describe the action or manipulation that is needed to obtain a certain visualization or information from the visual model, as shown for instance in Figure 1.
Beyond NLIs for visual analytics (Narechania et al., 2020;Yu and Silva, 2020), we see further potential for other NLP methods in visualization tasks that require more than plots of data for a specific, precisely formulated goal. In visual exploration, the goal is typically rather vague and developed during the exploration process itself, in an iterative fashion while interacting with the system. Moreover, applications in augmented and virtual reality entail new possibilities of immersive experiences and interaction for supporting performance as in (Butcher et al., 2020) or to enhance retention , which clearly includes multiple modalities. We argue that users of visual models in such exploratory setups could greatly benefit from natural language interaction, if the NLI would allow for more context-sensitive and situated querying of the model. Moreover, beyond querying, we expect that users would highly appreciate verbal system feedback or suggestions and explanations (see Figure  2). Ideally, this back-and-forth between the user and the system should support the user not only in realizing his goal, but also in establishing his goal or refining his initially vague goal.
Thus, we currently see a lot of interest in systems that enable interaction with an underlying data set via natural language, but the query-based approach used in many NLIs still seems to lack flexibility.

Language & Vision
A lot of recent work in NLP tackles dialogue modelling (Shuster et al., 2020;Qin et al., 2020;Ham et al., 2020;Rameshkumar and Bailey, 2020) or question answering (Baheti et al., 2020;. Goal-based dialogue covers navigation Zhu et al. (2020), manipulation (Jayannavar et al., 2020) or classical information presentation tasks (Andreas et al., 2020). A central problem in these mod-  (Jaques et al., 2020;Li et al., , 2016. RL optimizes the utterance understanding and generation in the system with respect to a certain reward function in the given environment. Next to these improvements on the level of dialogue modeling, recent developments in Language & Vision focus on grounding verbal utterances in visual inputs as, for instance, in visual question answering (Huang et al., 2020;Khademi, 2020). Visual dialogue (Das et al., 2017;Wang et al., 2020) extends the dialogue modelling task to the visual modality. Mixed-initiative visual dialogue, as e.g. in Ilinykh et al. (2019), aims at modeling interactions in which both dialogue partners can talk and act, which could be an interesting setting for visual exploration tasks. We believe that these successes in neural dialogue modelling and the integration of different modalities as in visual dialogue can lead to new possibilities for interactive systems in VIS, as we will discuss below.

Future Work
Uncertainty We believe that a fruitful direction for more flexible NLP-based systems in VIS is to look at scenarios where users might not have a concrete manipulation task or goal in mind, but want to explore a complex visual model. Numerous applications, such as in medicine (Meuschke et al., 2016(Meuschke et al., , 2017 or cultural-technical scenarios , require the visual exploration of complex models. Figure 2 shows an example of a 3D-mesh of an aneurysm and a corresponding, made-up dialogue that would support the user in exploring the model (Meuschke et al., 2018). On the NLP side, this setting involves a high degree of uncertainty. The user investigates a certain region of the model she is interested in, develops an understanding of the visual landscape and/or just learns how to handle it best. Thus, we argue that complex visual models like in Figure 2 probably call for different and more flexible types of interactions, as compared to NLIs discussed in Section 3.1. A user analyzing a barplot might be interested in minima, maxima, trends or outliers, which correspond to fixed goals. In contrast to that, a neurosurgeon inspecting an aneurysm in virtual reality is much more interested in the how than in the what and the goal might not be precisely formulated beforehand by the surgeon but evolving through the back and forth of the interaction with the visual model.
An important question that arises from that is, if users would really use natural language for exploring a visual model or if they would rather prefer the use of e.g. a controller or touch gesture. For many cases this might indeed be true, but we argue, that certain scenarios in visual exploration especially demand for verbal problem solution: recommendation of possibilities ("show me how to reach the largest vessel from here", "how to achieve a blood pressure increase in this region"), problemsolution-suggestions, tutorial-like action descriptions the user has to mimic, e.g. in educational scenarios or future state simulations that are highly hypothetical ("what would the vessel behave if we changed the blood flow drastically to ..."). These cases are in fact simulations of possible solutions helping the user to visualize and explore the solution space, which are much more convenient and intuitive expressed using natural language which can be supported by strong dialogue models that adapt to the context. Visual Grounding Visual language grounding in these scenarios captures not only the grounding of words into the scene (e.g. "vessel") but also the grounding of movements and gazes like pointer gestures (e.g. "here") which shows that the interplay of context awareness and multi-modal visual grounding are prerequisites for dialogue that humans would describe as "intuitive" and flexible. In contrast to systems like (Narechania et al., 2020) which are restricted to visual output and systems like (Adiwardana et al., 2020) which respond verbally, dialogue systems in visual models should be able to handle multi-modal responses, as illustrated in Figure 2. The highlighting, scaling, coloring or fading of certain visual properties is an important part of the response which not only contains text but rather text and a visual action combined. Figure 2 shows an example for a collaborative, mixed-initiative interaction where the the dialogue flow is not entirely centered on user queries.  used dialogue modelling for generating visual story lines in collaboration with a user and obtained promising results in leveraging visual exploration scenarios. In contrast to concise, goal-based visual analytics (see Section 3.1), hard-coded grammars might be too restricted to handle the high uncertainty and the complex underlying reasoning in explorative scenarios. The visual analytics task differs from the visual exploration task considering the fact that it is not driven by a concise goal. Introducing mixedinitiative dialogue in visual exploration enhances the users' ability of communicating uncertainties and supports experimenting and iterative engagement with the environment as applied in active visual problem solving or in educational settings. When no concrete goal can be formulated, a NLI has to adapt to the user and present contextual information like hints, explanations or react to expressed uncertainties (e.g. 'What does this blue region here show me?', 'How can I slice the vessel and investigate the thickness?', 'How does this spot evolve over time?') which is a form of guidance, an evolving field in visual analytics (Ceneda et al., 2020). This interaction also is not bound to text-language interaction, but furthermore accommodates gestures, movements or glances and therefore can be categorized as multi-modal. Here, recent advances in NLP could extend the interface flexibility by providing better context-awareness using visually grounded dialogue techniques and contributing to solve the user goal inference problem by re-framing the task as an iterative goal alignment task executed via mixed-initiative dialogue. We think that especially mixed-initiative dialogue would be a challenging but very promising direction and well-suited for inferring user intentions in complex VIS settings because of the usage of direct user feedback and iterative alignment. Furthermore, mixed-initiative dialogue methods could support the setup of user-centred evaluation of more complex visualization techniques, such as in (Lawonn et al., 2014). In sum, we argue that the role of NLP in interfaces with visual models is to enrich the dialogue between a system and a user (Dimara and Perin, 2019) with more flexible and intuitive ways of dialogue that might include touch-based or controller-based interaction.

Conclusion
In this paper, we gave a brief introduction on how interaction is understood and modelled in the fields of NLP and VIS. We found that existing work on NLIs in the Visualization domain heavily relies on query-based interactions. We argued that for interacting with highly complex visual models these strict interaction protocols might not be sufficient. Recent developments in Language & Vision investigate dialogue in visual contexts and reach promising results. We believe that this holds interesting research gaps for future work in integrating different variations of NLP-backed dialogue methods into visualizations enabling multi-modal interaction with visual models.


Assessing the Role of Cyberbiosecurity in Agriculture: A Case Study

Agriculture has adopted the use of smart technology to help meet growing food demands. This increased automation and associated connectivity increases the risk of farms being targeted by cyber-attacks. Increasing frequency of cybersecurity breaches in many industries illustrates the need for securing our food supply chain. The uniqueness of biological data, the complexity of integration across the food and agricultural system, and the importance of this system to the U.S. bioeconomy and public welfare suggests an urgency as well as unique challenges that are not common across all industries. To identify and address the gaps in awareness and knowledge as well as encourage collaborations, Virginia Tech hosted a virtual workshop consisting of professionals from agriculture, cybersecurity, government, and academia. During the workshop, thought leaders and influencers discussed 1) common food and agricultural system challenges, scenarios, outcomes and risks to various sectors of the system; 2) cyberbiosecurity strategies for the system, gaps in workforce and training, and research and policy needs. The meeting sessions were transcribed and analyzed using qualitative methodology. The most common themes that emerged were challenges, solutions, viewpoints, common vocabulary. From the results of the analysis, it is evident that none of the participating groups had available cybersecurity training and resources. Participants were uncertain about future pathways for training, implementation, and outreach related to cyberbiosecurity. Recommendations include creating training and education, continued interdisciplinary collaboration, and recruiting government involvement to speed up better security practices related to cyberbiosecurity.

INTRODUCTION
Agriculture continues to adopt new smart technologies that allow for increased and remote monitoring of crops and livestock. The interconnectivity of these technologies within a single farm or production facility and in exchange of data with suppliers and vendors creates unsupervised networks of information. With the adoption of these technologies comes increased risks for cybersecurity attacks on farms and agribusinesses (van der Linden et al., 2020). These attacks have the potential to disrupt food supply chains, damaging the bioeconomy and communities. Protecting agriculture includes both good cybersecurity and biosecurity decisions, critical control points, and human behavior and habits that influence the overall security. The combination of these domains has been coined cyberbiosecurity. While cybersecurity encompasses the protection of any electronic data, systems, networks, etc., cyberbiosecurity is one of its most important applications especially focused towards prevention of illegal intrusions and other activities and safeguard the data, information, and other online resources pertaining to life, medical, health, agricultural and food sciences (Murch and DiEuliis, 2019). Experts in the fields of information technology and life sciences tend to lack training in the other, making it difficult to create policies that encapsulate both (Richardson et al., 2019). Since cyberbiosecurity is such a new concept, there are no traditional training and certification courses available, making it difficult to educate people from secondary and post-secondary education to continuing professional development for employees of organizations.
Protecting agriculture and the food supply chain is a high priority, especially with increasing risk of food insecurity brought on by the Covid-19 pandemic (Laborde et al., 2020) as well as the rapid expansion in the global population. Unfortunately, it is uncommon for farms to have response plans for cyber penetrations (van der Linden et al., 2020) or to recognize the risks associated with corrupted data on decision making. Perceived risk of penetration and perceived benefits from better security are two influential factors for adopting better security habits (Geil et al., 2018). Relatively few people in agriculture have training in cybersecurity or biosecurity, which could lead to poor security practices anywhere in the supply chain. Security in a supply chain is only as effective as the weakest link, giving importance to every party involved. To improve cyberbiosecurity practices across the board, training and certifications must be created for current and future workers.

Cyberbiosecurity in Food and Agriculture
With development of technologies like the worldwide web, agriculture and food production and processing have been incorporated among the cyber-enabled life sciences technologies. Thus, cyberbiosecurity especially in the food and agriculture sector has been recognized by government agencies, producers, and security experts as the solution to cyber-based threats that could have potentially crippling effects on the nation's food supply chain (Murch et al., 2018). Growth in smart farming is expected to grow on a global scale to reach nearly 26B (USD) by 2028 and the largest market share is centered in North America (Emergen Research, 2020). Smart technologies, while beneficial, have the potential to be exploited by hackers to disrupt the farms using them and the downstream users relying on the supply chain. Potential risks that are attributed with precision agriculture and smart technologies include: false sensor data, data and machinery access control, and data encryption (i.e., ransomware attacks) (Chi et al., 2017).
An exploitation in any of these areas could compromise a farm's entire production. In 2017, the Department of Defense funded the National Strategic Research Institute at the University of Nebraska, along with Colorado State University and Virginia Tech to begin cyberbiosecurity research in biomanufacturing (Global Biodefense, 2017). Their goal was to create a list of preventative procedures for the industry to follow to reduce vulnerabilities to cyberattacks. Unfortunately, some of the solutions and preventative measures are not 'one size fits all' solutions because some producers do not have the means to invest the necessary resources into improving their security (Millet et al., 2017). In order to form better practices, experts and professionals from both agriculture and security have looked to other cybersecurity fields to adapt and adopt their procedures to better fit agriculture.

Current Cyberbiosecurity Initiatives
Cyber-attacks in agriculture are underreported due to a lack of detection capability in current hardware and software (Cyber Security in UK Agriculture NCC Group, 2020). This feeds into the idea of pulling practices from other fields to better adapt to agriculture. Cyber-attacks became more prevalent during the Covid-19, of which the healthcare organizations were the main victim (Pranggono and Arabo, 2020). The universities and organizations working on Covid-19 vaccine development, modelling, and testing were also very much vulnerable to the cyber-criminals (Muthuppalaniappan et al., 2021). The Covid-19 pandemic has increased the value of digitized biodata due to the research to understand the virus and the development of vaccines and other biological response mechanisms built on biodata. This is followed by a call to action for organizations to reallocate resources into understanding and improving cyberbiosecurity, both for preventing another viral or zoonotic-associated pandemic event, such as we are experiencing with Covid-19, from happening (Mueller, 2020), as well as protecting the integrity of the biological data and the systems in which that data is generated, validated, shared, and used for decisions.

Areas of Opportunity
A common theme among current literature is a call to action for professionals from cybersecurity and biosecurity to collaborate on ways to bring cyberbiosecurity forward into practice (Duncan et al., 2019;Richardson et al., 2019). There is no education and training for individuals interested in cyberbiosecurity to become specialists compared to cybersecurity and biosecurity. The ideal candidate for a job would possibly have a degree in life sciences, including agriculture and food domains, with additional knowledge and training in cybersecurity. (Richardson et al., 2019). Education and training that are kept relevant for the changing field of security need to be created to teach current and future professionals about cyberbiosecurity practices (Richardson et al., 2019).

A Case for Research in Cyberbiosecurity in Food and Agriculture
As production agriculture continues to adopt smart technologies to monitor and manage their operations, there is an increase in the amount and severity of vulnerability to these farms. A successful cyberattack could disrupt or lead to the destruction of a harvest, which would not only impact the farmers, but it would also ripple through the food system and impact the consumer (Chi et al., 2017). Smart technology, cyber attackers, and cybersecurity procedures are constantly evolving to fit the current environment (Wolfson and Leung, 2020). With agriculture now having a foot in the cybersecurity sector, it too must be able to adapt to the environment to safely operate. Failure to adapt cybersecurity practices to consider the unique structure and complexities of the agriculture and food system could lead to vulnerabilities that could put food supply chains in jeopardy. Future cyberbiosecurity research would allow for farmers and related companies to protect not only their financial interests but also would protect the food supply chain that people and businesses rely on (Duncan et al., 2019). Research specifically in agricultural cyberbiosecurity has not been an area of focus in literature.

Research Questions
Three research questions guided this work: 1. What is the current experience that professionals in agriculture and food have related to cyberbiosecurity in their field(s)? 2. In what ways are these professionals addressing new situations related to cyberbiosecurity that are new or novel? 3. What feedback or recommendations did the population have for future work related to cyberbiosecurity?

METHODOLOGY
A focused case study on a quasi-experimental research design was employed, using the population that participated in the conference (Privitera and Ahlgrim-Delzell, 2018) using a qualitative approach with multiple sources of data to increase rigor and reliability . A qualitative case study allowed for an in-depth understanding of a bound system (cyberbiosecurity in food and agriculture) and focused on the qualitative feedback from three populations: industries related to food and agriculture, faculty at universities who were investigating cyberbiosecurity, and law enforcement agencies (Yin, 2017). This study sought to understand how professionals knowledgeable about cyberbiosecurity worked with it in their respective professions, issues they worked with as a result of cyberbiosecurity breaches, and how to secure data for their entities and clients to avoid a cyberbiosecurity attack in the future. Participants consented to being recorded via Zoom (Zoom Video Communications Inc., San Jose. CA, Zoom.us) and any by-products created were transcribed and analyzed as part of this conference for research purposes. By-products were chat dialogue boxes in zoom, audio and video recorded meeting sessions, and Google Slides that facilitators used during breakout sessions. Data from approximately 80 participants was collected through audio recordings in Zoom, chat box dialog in Zoom, and Google Slides that were populated during breakout sessions. This case study looked to address the current state of cyberbiosecurity in these fields, what the challenges were to investigating and mitigating cyberbiosecurity threats, and what the participants viewed as areas where more resources and efforts should be in place to avoid future threats and mitigate attacks. Concurrently collecting data while the conference was running provided more opportunities for participants to respond and share their experiences, perceptions, and thoughts on cyberbiosecurity .

Data Collection
The data used in this paper were collected from a virtual 2-day workshop (Securing Agriculture, Food, and its Economy with Cybersecurity, 2020) held in Fall 2020 as part of a USDA AFRIfunded project (USDA-NIFA Grant No. 2019-67021-29,956, Accession No. 1019771). The workshop was held online via Zoom which included 8 sessions with a variety of agendas (see Table 1) where national and state level speakers addressed a variety of topics of relevance to securing digital, physical, and biological systems and associated data within the domestic food and agriculture system. Those sessions along with breakout rooms were facilitated by trained coordinators to manage the Zoom meeting and Google Slides to help participants organize thoughts, contribute in multiple ways, and enable all to participate to be inclusive to as many participants as possible.
The facilitators conducted small group discussion on leadership skills, helped in populating and managing any google based documents, and provided follow up questions. As this was a virtual workshop, participation within each session varied dramatically and only a count record of participants was obtained for each session, which made it difficult to remain informed about what organizations were represented in each session and whose 'voice' was heard and contributed to the data for this report. Data were collected from different sources throughout the conference: Zoom audio, Zoom video, and Google based artifacts. The researchers worked with the conference organizers to set up, organize, and transfer any recorded data from Zoom. Any data generated from breakout sessions was also placed into a shared repository that was available to only the research team.

Participants
The conference was advertised to a broad audience of professionals involved in food and agriculture, cybersecurity, government security, etc. The university worked with the Virginia Tech office of Continuing and Professional Education to advertise the workshop and register participants for the conference. Advertising included email distributions through a variety of regional and national listservs, LinkedIn posting, Facebook and other social media methods, information on websites, an advance article about the forthcoming workshop published through Virginia Tech news and subsequent national and global media pickup, and word of mouth invitations. Agribusinesses including food manufacturing companies, agricultural producers and commodity boards, auxiliary companies that support the agriculture and food sectors, other private sector businesses representing cybersecurity and technologies, universities, and state and federal agencies Frontiers in Bioengineering and Biotechnology | www.frontiersin.org August 2021 | Volume 9 | Article 737927 including law enforcement, were invited to participate in one or more sessions of the conference. Approximately 170 participants registered for the workshop. Figure 1 represents the number of participants from various backgrounds.

Data Analysis
In vivo coding is a type or category of qualitative data analysis which uses participant's own words to summarize or analyze the data (Manning, 2017). In this study, in vivo was conducted to determine what meaningful patterns were emerging to make up sub-categories of data, based on the conversation and other audio-based recordings and by-products collected (Charmaz, 2006). In vivo coding was employed to define patterns in the data and arrange the data in a systematic order (Saldaña, 2021). The data was first open coded where the it was categorized into major themes, and then focused coding was conducted to identify any repeating patterns and understand multi-layer meaning. . The resulting codes were more direct and began to explain larger segments of the data as they related to perceptions of cyberbiosecurity. Focused coding helped determine the adequacy of the in vivo codes (Charmaz, 2014). By comparing data to data, focused codes were created to help the researcher begin grouping like codes and refining them into larger groups of categories. Focused coding expedited the in vivo coding and helped to condense and reorganize what was found in the first round of coding (Charmaz, 2006). Axial coding was conducted as the final step of the coding process, helping the researchers bring all of the data together and determine themes based on the research questions (Corbin and Strauss, 2008). Development of the codebook emphasized the action-oriented nature of language in which participants discussed the issue of cyberbiosecurity from their viewpoint (Roth, 2008). Using constructs from work presented in the literature review and taking the coding scheme, the codebook was developed around key areas. The quotes in this work have been presented as is without any changes. In order to refrain from making the reading monotonous, all the quotes have not been included in the present article (Anderson, 2010). Only those quotes that best reflect the themes or the findings have been outlined here. The comprehensive data set could be provided upon requesting the corresponding author.

Limitations
Limitations of this work include the small sample size that is not generalizable to a larger audience about issues related to cyberbiosecurity. The body of literature on cyberbiosecurity related research is still relatively small and reporting baseline data like this can help add to the literature with the knowledge the sample was limited. This work mostly focuses on the current and future cyberbiosecurity situation in the US so had a limited scope on informing cyberbiosecurity issues that might influence international food supply chains. Another limitation is the inability to determine which facets of cyberbiosecurity were left out of the conversations that the data reported. The limits of our current knowledge in this new paradigm is confined to the expertise of the professionals who participated. There is much within the food and agriculture knowledge domains that we do not know or understand that also limits the capacity and potential for cyberbiosecurity characterization and knowledge.

RESULTS
Through qualitative analysis, four main themes from the conference were identified: challenges, solutions, viewpoints, and vocabulary. There is a lack of common language among disciplines that prevents or limits collaboration and communication between disciplines. For some, there has either been a lack of resources or knowledge of resources available for agribusinesses, affiliated companies, agriculture organizations, and farmer/producer to start investing in and improving their cybersecurity practices. It was also noted that lack of government involvement and programs has prevented some from increasing their cyberbiosecurity practices. Similar to other literature, we found a lack of basic cybersecurity training in agriculture to be a limiting factor (Duncan et al., 2019). We expand upon the four primary themes, providing quotes to illustrate and support the sub themes within each.

Theme 1: Challenges
Challenges related to work in cyberbiosecurity were abundant. At least 213 challenges were coded in the transcripts from the sessions. Since cyberbiosecurity is a newer issue, all participants at the conference, no matter their respective field or expertise, reported a multitude of challenges that had sprouted recently. One of the principal challenges is lack of infrastructure and expertise: "One of the challenges with small companies is that they simply do not have the infrastructure and they do not have the expertise . . . we want everything to be cool and quick and available on our iPhone and security is not always at the forefront of earlier adopters." The ability to protect against threats was one of the common challenges that was echoed throughout the conference from multiple perspectives. Additionally, other challenges came from the perspectives of different sectors in cyberbiosecurity that included "the supply chain impact," "ripple effects," and feeling "way behind" in regard to food and agriculture industries. Participants shared that many employees within organizations felt as though it wasn't their responsibility to address these issues or tertiary issues around cyberbiosecurity: "There's a mindset that this is something that doesn't involve me. There's a mindset that I have found in the sector that this is a technology I don't deal with, so therefore I don't do that, or I don't need that." Other participants knew and recognized how reliant food and agriculture are on cyber capabilities but also shared that their businesses were way behind in terms of protecting or being proactive against attacks. Some knew the detrimental effects that an attack could have on the supply chain and movement of products to consumers: "The supply chain impact, you know, stopping something at one point has a ripple effect. Some things back up, and some things go dry." Some challenges spanned beyond the scope of what importance cyberbiosecurity holds and questioned the logistics of bringing it to the private sector: "how do we connect all of the different players in this? How do we connect the stakeholders involved?" "What federal agency or agencies are going to take the lead in implementing safe cyberbiosecurity practices? Who's in charge?"

Theme 2: Solutions
Solutions came in response to challenges discussed among small groups at the conference. Solutions covered multiple parts of the supply chain and reached to different fields involved in cyberbiosecurity.
Cyberbiosecurity is not a one size fits all solution and will need to be adapted for individual circumstances.
"we want to get people away from the idea that anyone thinks they can just buy some off the shelf thing and plug it in and suddenly it will work for them. So what we need is a much larger conversation and so I think that's all focused around helping people understand what the definition (cyberbiosecurity) is and making sure they have buy into what that definition is." Training and classes have been identified as being important; however, it was questioned who would be qualified to lead cyberbiosecurity initiatives: "If there were not only training but 'train the trainer' kind of approaches with, you know validated packages it could be provided to companies obviously gonna make what you can't be everywhere and train everybody, but you can get standardized you know, training sets." In order to get government support and leadership, it was recommended that cyberbiosecurity initiatives need to be brought to the House of Representatives Agriculture Committee: Frontiers in Bioengineering and Biotechnology | www.frontiersin.org August 2021 | Volume 9 | Article 737927 "if you want to get real leadership on this, we would need to get Collin Peterson (former) chair of the House Ag Committee to add this to one of the hearings and have it be brought up in a hearing you want to create some leadership".
Since each producer's cybersecurity situation is unique, there are steps individual businesses can take to help identify their weaknesses, such as red teaming: "one approach that I thought was always pretty innovative, was like the white hat hacker approach... you actually send the good guys in there to do penetration testing, and you show them before they've been hacked, what their vulnerabilities are in a friendly way you say, you know, this is what we found, maybe there's some tighten up here."

Theme 3: Viewpoints
Collaboration among professionals from different fields showed different viewpoints on similar subjects of conversation. Like other industries such as biomedical, biomanufacturing, and chemical production, agriculture contributes to the bioeconomy. The obstacles surrounding agriculture data are similar to obstacles that other fields in the bioeconomy face.
"when we look at this aspect of the cyber data component, what we found is that when you look at the bioeconomy, its vulnerabilities to cyber issues are really not fundamentally different from that you find in other traditional areas, but you might have different outcomes." People in agriculture want to be certain that policy makers would have their best interest in mind by helping to protect their company data.
"From an ag perspective, one of the questions is do the people making these policy determinations understand the value and utility of an agricultural company's data." Some were hesitant to rely on government guidance for setting standards for cyberbiosecurity. Cooperation and viewing cyberbiosecurity as a multidisciplinary field would be required.
"on Capitol Hill, legislative bodies, like committees and member offices have historically addressed either cyber, or bio, or ag, or chem, or whatever else we are talking about separately 2 | Vocabulary terms identified as needed defining by some participants and the context in which terms were used during the Securing Agriculture and Food Economy (SAFE) with Cyberbiosecurity virtual workshop (October 6-7, 2020).

Terms
Use during the sessions/Excerpts Cyber pandemic "the crisis for the food and agricultural system focusing on parallel to our current viral pandemic, and we call it the cyber pandemic." Hacktivism "And then detailed such threats in some form of insider threats, industrial control systems or malware ransomware, a term I had not noticed called hacktivism, and intellectual property theft," "disrupt networks or expose/destroy data to advance a political or social cause" Biosecurity "So biosecurity is set of measures aimed at preventing the introduction or spread of harmful organisms, in order to minimize risk of transmission of infectious diseases to people, animals and plants caused by viruses, bacteria, or microorganisms." "biosecurity is more about when someone tries to purposely do harm in those systems, right." Cybersecurity, information technologies "cybersecurity refers to the body of technologies, processes and practices designed to protect networks, devices, programs and data from attack, damaged or overwrite the authorized to access. Cybersecurity may also be referred to as information technologies." Biosafety "biosafety is about when something happens accidentally, that causes harm." Threat actors "Who are threat actors: disgruntled employees, dissatisfied customers, criminals, foreign terrorist orgs, homegrown violent criminals, domestic extremist groups, industrial opposition" Economic espionage "steal trade secrets to help anyone other than owner" Insider threat "exploit credentials or old access to secure areas, sensitive information, etc." "current or former employees/contractors, steal IP or destroy data (life work)" Ransomware "victims in virtually every sector; infection vector (malicious attachment/link), ransom payment typically in bitcoin, FBI does not advocate paying a ransom" Agroterrorism "deliberate actions by politically motive extremest groups." Hybrid warfare "combines traditional and non traditional methods of attacking critical infrastructure" Complex attack "threats or incidents on social media accusing gov agencies of cover-ups, lack of transparency," Lateral thinking "in which you are in one field, but you are applying how you think and what you think, in that field to another field." Continuous monitoring "is obviously the idea that, okay, you're doing things, you've got programs in place, but now you have to monitor them, whether they're, for regulatory purposes, best practices, or to detect active threats and anomalies, changes to your program" Frontiers in Bioengineering and Biotechnology | www.frontiersin.org August 2021 | Volume 9 | Article 737927 6 and just because those things are converging does not mean that people on Capitol Hill are converging and they are going to work together to develop and pass legislation to address this risk".

Theme 4: Vocabulary
The fourth theme gathered from the conference was a list of vocabulary terms that were considered to be industry specific terms. These terms were used by attendees in one field that others didn't have a definition for or that may not be common language for other fields. Table 2 lists some of the new terms and their explanation by the participants. The goal of collecting these terms is to be able to define them and create a working lexicon for professionals to use that will help break language barriers for interdisciplinary collaboration.

DISCUSSION
The previously mentioned sessions included professionals from the university, producers, and security professionals to invoke interdisciplinary collaboration. Bringing professionals together from different fields addresses one of the recommendations commonly found in cyberbiosecurity literature. This allowed for professionals to build networks outside of their field and experience how different fields approach similar situations.
The experience among professionals in the food and agriculture fields is varied but the major theme running through each area of expertise was challenges and solutions. The challenges that were discussed covered current and future challenges in agriculture that may impact food supply chains. Smart farms are not always built with security in mind, meaning their equipment machines and computers may not have up-todate or any security measures installed to protect their equipment and data. Employees or farms, big and small, do not always have security and threat mitigation training and awareness. This can lead to issues when it comes to protecting data and being alert to potential security penetrations. If penetrations are detected, not everyone has a clear plan of action to take to limit damages and re-secure themselves. There's a lack of common language between professionals in agriculture and cyberbiosecurity, which was seen in the conferences where participants would have two different meanings for the same terminology. For those who want to improve their practices, there's either a lack of available resources or known resources to use. Participants questioned whether smaller businesses and farms could afford to invest the money, time, and other resources into upgrading their cyberbiosecurity measures.
Solutions discussed were a combination of recommendations to real and hypothetical problems brought up during the conferences. Developing classes, trainings, and workshops for students and current professionals about cyberbiosecurity was suggested multiple times. Trainings would help people be more cautious of, and better prepared to deal with security related issues. It would also provide ground for developing common language for those working in both industries. Having producers undergo training would allow them to identify weak points in their security and then secure those issues. Companies should create protocols for farmers/producers/agribusinesses to follow if a security penetration is suspected or detected. State and federal government could also establish security standards for smart farm equipment and offer assistance for farms looking to improve their security.
Viewpoints that were identified highlighted attendees' understandings and perspectives on different concepts that were discussed. Agriculture will increase the amount of data it produces, which helps drive the bioeconomy. The need to prepare and defend agriculture was commonly agreed upon by all attendees. It was mentioned that malicious attacks on agriculture are not something that most people think of or are prepared for. Multiple people mentioned that they felt agriculture is behind in issues related to security and they didn't trust the nation to protect the food sector. Having the United States Department of Agriculture (USDA) or the Food and Drug Administration (FDA) implement regulations on food processing and processing safety was suggested. However, it was mentioned that government involvement in cyberbiosecurity is sparse because agriculture, biology, and cybersecurity are often addressed as separate entities, not as a system that intertwines and overlaps.
Continued collaboration and work in cybersecurity was another focal point of the conference. One proposed goal was to host a larger, national conference with experts in cybersecurity, agriculture, biology, and in politics. Expanding the reach would bring more voices, expertise, and influencers to the field. Potential partners that would help expand the reach and available resources for cyberbiosecurity, such as the FDA, and FSIS, were mentioned. When individuals were asked how they saw themselves helping cyberbiosecurity in the future, no definite answers were given. Most attendees had an optimistic outlook for the future of cyberbiosecurity but there was no clear vision of the path or what the future of cyberbiosecurity would look like. The lack of a clear vision shows the need for strong leadership to help raise awareness of the importance that every party plays in its success.
Current literature in cyberbiosecurity points out that agriculture is becoming more and more reliant on the capabilities of technology, thus bringing along cybersecurity risks (van der Linden et al., 2020). Also, more resources need to be invested into cyberbiosecurity research and development to prevent large-scale issues from arising (Mueller, 2020). It was widely accepted among participants that agriculture and the cyber-industry are intertwined and will probably be more so in the future. The more reliant on technology agriculture becomes, the more potential vulnerabilities there are in the food supply chain. Increased vulnerabilities make proper security more important to the supply chain. Some participants noted that they didn't know if their organizations had response plans for cybersecurity or biosecurity issues, or available resources to help prevent them. This supports the calls from literature for the need to invest resources into cyberbiosecurity research and training to better prepare for potential future issues.

CONCLUSION
Agriculture is an expanding industry that is increasingly reliant on smart technology for more accurate and efficient farming (Chi Frontiers Emergen Research, 2020). In order to protect the U.S. bioeconomy and food supply chain, agriculture needs to adopt cyberbiosecurity practices (Duncan et al., 2019). However, there is a lack of traditional training routes in cyberbiosecurity available for people in agriculture (Richardson et al., 2019). Calls for interdisciplinary collaboration are common among cyberbiosecurity literature (Duncan et al., 2019;Richardson et al., 2019) However, little has been reported in literature about attempting to drive this interdisciplinary collaboration.
As an initial multi-sector foray into the cyberbiosecurity discussion, Virginia Tech hosted a virtual 2-day conference with 170 registered participants across agriculture, cybersecurity, government, and academia to encourage collaboration. The analysis of the workshop discussions identified themes -challenges, solutions, viewpoints, and vocabulary terms-and creates an opportunity for accelerating future discussions and progress on advancing cyberbiosecurity for the agriculture and food system.
To improve cyberbiosecurity practices in agriculture, education and training need to be created for current and future agriculture professionals. Continued interdisciplinary collaboration is needed to close gaps between cybersecurity and biosecurity. Government implemented security standards for agriculture would help speed up the widespread adoption of cyberbiosecurity practices. Cyberbiosecurity will be imperative to the future success and safety of the agriculture supply chain and bioeconomy, as cyber-attacks are not a matter of if but when, and it would beneficial to improve security to prevent successful attacks rather than as a reaction to a successful one.

RECOMMENDATIONS
Future research and collaboration among professionals across sectors are needed to best improve cyberbiosecurity in agriculture. Education and training were found to be the most pertinent need for all sectors. Workshops and classes need to be developed and offered to current professionals as well as cybersecurity and agriculture students. Gaining buy-in from business and educating producers so they can start learning what they can do to minimize threats, where their data goes, why it's important to protect it, and how participating in this process can be good for their businesses bottom line, should be an important goal. Training should be tailored to meet the needs of the particular group understanding that the education and training will have to be adaptable and adoptable in order to meet the needs of each audience. The focus of these trainings should be to familiarize attendees with the concept of cyberbiosecurity, how to identify and perceive potential threats, and how to devise methods of handling such threats. Collaboration must continue among sectors in agriculture and cybersecurity. Conferences, such as the one hosted by Virginia Tech, allow structured conversation and networking opportunities among multiple disciplines. Professionals from agriculture, cybersecurity, academia, and government should construct standards for cybersecurity in agriculture. Having the USDA, FSIS, or FDA implement standards for both producers and machine manufacturers would prompt a quicker transition to a cyberbiosecurity-focused industry.
Another recommendation for future work is to examine and track threats and breaches in a more comprehensive manner. While literature and current events are helpful, it's impossible to understand the breadth and depth of the field since companies are protecting intellectual property and don't want their breaches to be public knowledge per se. Research and training have limits and without actual cases to learn from or anticipate a response to, this will limit the education and training aspect recommended above.
A final recommendation would be to form synergistic collaborations between industry, government, law enforcement and higher education to provide viewpoints from multiple places to become more agile in responding to cyber-attacks and build infrastructure to train future employees for business, government, or law enforcement. Having a common lexicon, gaining a baseline understanding of what the landscape of the field is, and then taking a collaborative approach to approaching it will be paramount for the United States to remain competitive in the field of cyberbiosecurity.

DATA AVAILABILITY STATEMENT
The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding author.

ETHICS STATEMENT
The studies involving human participants were reviewed and approved by Virginia Tech Institutional Review Board. Written informed consent for participation was not required for this study in accordance with the national legislation and the institutional requirements.

AUTHOR CONTRIBUTIONS
TD, SD, RM, MS, JS developed and organized the workshop from which the manuscript was developed. TD, NM completed the transcription of by-products and analysis and coding. TD, NM, AS developed the draft manuscript. SD and TD reviewed and edited the manuscript.