fix (next steps): resolving typos and removing non-ASCII characters (see #58)

Author: njlyon0

mod_next-steps.qmd

@@ -34,27 +34,27 @@ Depositing your assembled dataset in a public repository ensures that others can
 
 [![Authors provide data and metadata to EDI through ezEML. EDI checks for metadata completeness, packages, and serves the data to users. Credit: EDI](images/the-data-package.png){fig-alt="a pipeline from data and metadata, through quality report and resource map to finished data package."}](https://edirepository.org/resources/the-data-package)
 
-The Environmental Data Initiative has developed the [ezEML app](https://edirepository.org/resources/creating-metadata-for-publication#ezeml:~:text=create%20EML%20metadata.-,ezEML,-ezEML%20is%20a) to simplify the publication of datasets with high-quality metadata. The form-based tool leads users through creating and validating Ecological Metadata Language (EML) documents, a standard that can describe many types of data and their use cases, and then submitting them to the repository with accompanying data files. To prepare for submitting your data you’ll need to gather some information and make a few decisions.
+The Environmental Data Initiative has developed the [ezEML app](https://edirepository.org/resources/creating-metadata-for-publication#ezeml:~:text=create%20EML%20metadata.-,ezEML,-ezEML%20is%20a) to simplify the publication of datasets with high-quality metadata. The form-based tool leads users through creating and validating Ecological Metadata Language (EML) documents, a standard that can describe many types of data and their use cases, and then submitting them to the repository with accompanying data files. To prepare for submitting your data you'll need to gather some information and make a few decisions.
 
--   **General dataset descriptors**: You’ll need a title, abstract, keywords and list of dataset creators (with associated [ORCIDs](https://orcid.org/)). While it’s tempting to just use the abstract for your paper here, an abstract for a dataset does NOT focus on scientific findings. Instead, focus on the purpose of the data, how they were assembled and what decisions were made in the process. In writing your metadata, try to adopt the perspective of a data user and ensure that the information you provide answers questions they might have about data quality and fitness for use.
+-   **General dataset descriptors**: You'll need a title, abstract, keywords and list of dataset creators (with associated [ORCIDs](https://orcid.org/)). While it's tempting to just use the abstract for your paper here, an abstract for a dataset does NOT focus on scientific findings. Instead, focus on the purpose of the data, how they were assembled and what decisions were made in the process. In writing your metadata, try to adopt the perspective of a data user and ensure that the information you provide answers questions they might have about data quality and fitness for use.
 
 -   **Data table descriptors**: The most common submission formats in EDI are simple comma-separated value (CSV) tables. What tables does your synthesized dataset contain, and how do they relate to each other?
 
 -   **Column descriptors**: List the column names, units, and descriptions for each column in each table.
 
 -   **Methods**: Be ready to describe, in reproducible detail, the steps used to create the published dataset. For a synthesis project, your team probably spent considerable time finding, cleaning, harmonizing, and assembling the finished product into something that could be analyzed. What were these steps?
 
--   **Provenance**: What original data sources did you draw on? You’ll want your dataset to link to the original data sources so that they, too, receive credit for their work. In ezEML, data provenance information is associated with the methods metadata, and links are displayed on all EDI dataset landing pages.
+-   **Provenance**: What original data sources did you draw on? You'll want your dataset to link to the original data sources so that they, too, receive credit for their work. In ezEML, data provenance information is associated with the methods metadata, and links are displayed on all EDI dataset landing pages.
 
--   **Reuse**: ezEML will ask you to decide on a license for reuse of your synthesized data. EDI and LTER recommend using a C[C-0 public domain dedication](https://creativecommons.org/publicdomain/zero/1.0/) which allows reuse and adaptation without requiring a specific form of citation. Professional standards and EDI policy encourage citation, but preserving flexibility about the form of citation relieves downstream users from the obligation to cite data in ways that may not be workable for large syntheses. [CC-BY](https://creativecommons.org/licenses/by/4.0/deed.en) is also an acceptable license. It allows downstream users to re-share and adapt the licensed work, but requires that users “give appropriate credit, provide a link to the license, and indicate if changes were made.”
+-   **Reuse**: ezEML will ask you to decide on a license for reuse of your synthesized data. EDI and LTER recommend using a C[C-0 public domain dedication](https://creativecommons.org/publicdomain/zero/1.0/) which allows reuse and adaptation without requiring a specific form of citation. Professional standards and EDI policy encourage citation, but preserving flexibility about the form of citation relieves downstream users from the obligation to cite data in ways that may not be workable for large syntheses. [CC-BY](https://creativecommons.org/licenses/by/4.0/deed.en) is also an acceptable license. It allows downstream users to re-share and adapt the licensed work, but requires that users "give appropriate credit, provide a link to the license, and indicate if changes were made."
 
--   **Sharing code**: Chances are, your code is already public on GitHub (and hopefully, well documented), but you’ll want to create a persistent reference to the version of the code that you used to conduct *this* analysis. One way to go is to package your code along with your data on EDI. That approach makes the code findable, because it is right there with the data, but the code remains static, and it can be difficult to represent the software package structure and release history. Many researchers now prefer to release their GitHub repository [code on Zenodo](https://docs.github.com/en/repositories/archiving-a-github-repository/referencing-and-citing-content) and reference the specific release with their dataset in EDI or another repository. This allows continued development of code in the repository, while linking together the dataset and the code for creating or analyzing it. This approach is great for synthesis groups that will continue adding new data, analyses, or publications in the future.
+-   **Sharing code**: Chances are, your code is already public on GitHub (and hopefully, well documented), but you'll want to create a persistent reference to the version of the code that you used to conduct *this* analysis. One way to go is to package your code along with your data on EDI. That approach makes the code findable, because it is right there with the data, but the code remains static, and it can be difficult to represent the software package structure and release history. Many researchers now prefer to release their GitHub repository [code on Zenodo](https://docs.github.com/en/repositories/archiving-a-github-repository/referencing-and-citing-content) and reference the specific release with their dataset in EDI or another repository. This allows continued development of code in the repository, while linking together the dataset and the code for creating or analyzing it. This approach is great for synthesis groups that will continue adding new data, analyses, or publications in the future.
 
 ## Promote your dataset (and other products)
 
-Now that potential users and collaborators can find your dataset, how will they? Data in EDI are easily found through EDI, DataONE and Google data search, but many potential users won’t even know what they should be searching for. “Build it and they will come” doesn’t work much better for data than it does in other realms – at least not yet. Eventually, AI-driven search tools for researchers may improve the situation, but for now it’s still important to garner the attention of individuals. Who do you want to reach? Who you want to reach and what you want them to do with the data, paper, or other tool will influence how you spend the (likely quite limited) time you have to spend on promotion.
+Now that potential users and collaborators can find your dataset, how will they? Data in EDI are easily found through EDI, DataONE and Google data search, but many potential users won't even know what they should be searching for. "Build it and they will come" doesn't work much better for data than it does in other realms – at least not yet. Eventually, AI-driven search tools for researchers may improve the situation, but for now it's still important to garner the attention of individuals. Who do you want to reach? Who you want to reach and what you want them to do with the data, paper, or other tool will influence how you spend the (likely quite limited) time you have to spend on promotion.
 
-Want to reach community ecologists? Modellers? Land managers? Teachers? The choice will affect both where and how you promote the work. The choices here are endless, but the examples below illustrate the principle.
+Want to reach community ecologists? Modelers? Land managers? Teachers? The choice will affect both where and how you promote the work. The choices here are endless, but the examples below illustrate the principle.
 
 -   **Data papers** are essentially an extended version of your metadata, published in the form of a paper, and referencing the published dataset. They are great for calling attention to a high-value dataset, especially when it crosses disciplinary boundaries. Data papers are most appropriate when you want to reach people, such as modelers, who will use the dataset directly rather than your analysis and interpretation. [*Earth System Science Data*](https://www.earth-system-science-data.net/), [*Biodiversity Data Journal*](https://bdj.pensoft.net/), and [*Scientific Data*](https://www.nature.com/sdata/) all focus on data papers and are relevant for environmental science.
 
@@ -66,27 +66,27 @@ Want to reach community ecologists? Modellers? Land managers? Teachers? The choi
 
 -   **Newsletters and trade publications**. If your work is truly relevant to a particular group of professionals such as land managers, urban planners, fishers, or foresters, consider developing a polished one-page summary or an infographic and reaching out to relevant trade journals and newsletters.
 
-Whatever tactics you pursue, spend a little time as a group agreeing on the language and the main talking points about your work. The potential impact is much greater when everyone amplifies a coherent set of messages. One time-honored tool for developing these messages is the “[Message Box](https://www.compassscicomm.org/leadership-development/the-message-box/)” developed by COMPASS. Assembling those key messages in one location, such as on a project website, also gives each team member a place to point interested individuals and a touchstone for reference.
+Whatever tactics you pursue, spend a little time as a group agreeing on the language and the main talking points about your work. The potential impact is much greater when everyone amplifies a coherent set of messages. One time-honored tool for developing these messages is the "[Message Box](https://www.compassscicomm.org/leadership-development/the-message-box/)" developed by COMPASS. Assembling those key messages in one location, such as on a project website, also gives each team member a place to point interested individuals and a touchstone for reference.
 
 ## Park Downhill
 
-Beyond preserving and promoting the current work, there are a few things you can do to prepare for the new research opportunities that it can generate. Ideally, the group has been tracking spinoff ideas as they come up. It’s impractical to chase them all down in the moment, but recording them, with just a few sentences of context and explanation, will help to resurface the inspiration at a later date.
+Beyond preserving and promoting the current work, there are a few things you can do to prepare for the new research opportunities that it can generate. Ideally, the group has been tracking spin-off ideas as they come up. It's impractical to chase them all down in the moment, but recording them, with just a few sentences of context and explanation, will help to resurface the inspiration at a later date.
 
 <figure >
 <img src="images/mind-map.png" alt="linked concepts around a central theme" width="50%" align="right">
 </figure>
 
 Now is the time to pull those ideas out of mothballs or, alternatively, return to the mind maps we made in the [project management session](https://lter.github.io/ssecr/mod_project-mgmt.html) to unearth some new ones.
 
-This year, you've tackled one, maybe two, of the relationships on that mind map. But chances are that the data you’ve assembled sheds light on several more. In this project group discussion, we’ll take some time to identify and explore a few of them. 
+This year, you've tackled one, maybe two, of the relationships on that mind map. But chances are that the data you've assembled sheds light on several more. In this project group discussion, we'll take some time to identify and explore a few of them. 
 
 :::panel-tabset
 ### Discussion: Preparing to Propose
 
 **Individually (15 minutes)**
 
 -  Pull up your running list of project ideas, the mind map you generated in the project management session, or start a new mind map with your current project theme at the center.
--  Come up with a related research idea that capitalizes on the data you’ve assembled. Try focusing on upsteam controls, downstream impacts or modifying factors to spur your creativity. It doesn't have to be Nobel-worthy, it's just for this exercise.
+-  Come up with a related research idea that capitalizes on the data you've assembled. Try focusing on upstream controls, downstream impacts or modifying factors to spur your creativity. It doesn't have to be Nobel-worthy, it's just for this exercise.
 -  Identify what additional data or analyses would be needed to clarify the nature and scale of the relationship  
 -  How might a change in our understanding of that relationship affect how we understand other processes? 
 
@@ -98,9 +98,9 @@ This year, you've tackled one, maybe two, of the relationships on that mind map.
 
 -  For each of your projects, brainstorm a list of people (individuals, groups, roles, agencies) who care about those changes or that might benefit from or be hurt by them.
 
-For example, say your original project was focused on understanding what factors influence the long term immobilization of soil carbon during decomposition. Spinoff ideas might look at:
+For example, say your original project was focused on understanding what factors influence the long term immobilization of soil carbon during decomposition. Spin-off ideas might look at:
 
--  additional controlling factors that you couldn’t include in the first effort; 
+-  additional controlling factors that you couldn't include in the first effort; 
 -  a wider range of ecosystems; 
 -  the role of variability (not only temperature, for example, but also the frequency of freeze-thaw cycles);
 -  the effect of the same factors on the mobilization of nutrients in soil; or 
@@ -121,7 +121,7 @@ Discuss how ideas came together and what kinds of audiences were identified.
 <figcaption background-color="white"></figcaption>
 </figure>
 
-When thinking about how to support a research program, strategy (setting goals and making plans to achieve them) is often contrasted with an opportunistic approach. But really, it’s essential to apply a bit of both. The list of people and agencies you generated from this exercise serves as a starting point for exploring funding opportunities. When you find an opportunity that intersects with a problem that you have the tools, skills, and data to tackle, that’s when you spring into action, building on knowledge gaps that you’ve already identified. 
+When thinking about how to support a research program, strategy (setting goals and making plans to achieve them) is often contrasted with an opportunistic approach. But really, it's essential to apply a bit of both. The list of people and agencies you generated from this exercise serves as a starting point for exploring funding opportunities. When you find an opportunity that intersects with a problem that you have the tools, skills, and data to tackle, that's when you spring into action, building on knowledge gaps that you've already identified. 
 
 When you have an idea that you're excited about, one great practice is to develop a "pocket proposal"--a two-page, scaled down description of the research you hope to do. Writing one will force you to clarify your ideas, improve your articulation of them, give you something to share with colleagues (either to invite collaborators or to seek critical feedback), and provide a head start when you DO find a funding opportunity that's a fit.
 
@@ -141,25 +141,25 @@ All NSF program pages have a link at the bottom leading to a list of past awards
 
 The bones of any proposal include answers to the following questions:
 
--  Context - what is already known/done? What’s the gap you’re trying to fill?
+-  Context - what is already known/done? What's the gap you're trying to fill?
 -  What do you want to do?
 -  How do you plan to do it?
 -  Why are you the right person/group to do it?
 -  Why is it a fit for THIS funder?
 -  How will you disseminate or apply the work?
 -  What do you expect the results to be
 
-Depending on the source of funding, the order and emphasis of these items will be different. For a foundation funder, the need and results might be most important, with the precise “how” taking a back seat. For a science agency, context and work plan will take higher priority, but be sure to include why you are the right group to do it and what you expect the results to be--even if only a sentence or two.
+Depending on the source of funding, the order and emphasis of these items will be different. For a foundation funder, the need and results might be most important, with the precise "how" taking a back seat. For a science agency, context and work plan will take higher priority, but be sure to include why you are the right group to do it and what you expect the results to be--even if only a sentence or two.
 
-Even for an individual donor, you’ll want to have a list of talking points that addresses these questions, but you probably won’t turn it into a formal proposal until you’ve developed a relationship.
+Even for an individual donor, you'll want to have a list of talking points that addresses these questions, but you probably won't turn it into a formal proposal until you've developed a relationship.
 
 It can be intimidating, but it is immensely helpful to ask for feedback from experienced colleagues at various stages of proposal development. Be sure to specify what kind of feedback would be useful to you and to give them a (reasonable) deadline.
 
 :::panel-tabset
 
 ##  Group Discussion: Revisit your Authorship Agreement
 
-Anytime a project undergoes a major transition, it’s a good idea to revisit the approach to authorship. An agreement that worked well for an organized project with fixed membership may not be as appropriate for spinoff projects, spearheaded by individual team members and involving rotating groups of collaborators. 
+Anytime a project undergoes a major transition, it's a good idea to revisit the approach to authorship. An agreement that worked well for an organized project with fixed membership may not be as appropriate for spin-off projects, spearheaded by individual team members and involving rotating groups of collaborators. 
 
 Break out into project groups and discuss the following questions as they might apply to emerging projects: