dataesr/scientific-paragraphs-categorization huggingface dataset:
The second building (B) integrating reused steel elements is a medium-high 18-story-high building, which may match with the new future French standard  [68]  of a flexible building (both offices and residential between 28 m and 50 m). This first approach made it possible to identify all the steps to ensure reuse and, in this sense, allows a generalization. In this study, a BIM software and a database tool were chosen and used. The methodology described applies to any other BIM software and other types of databases. Scenario "design with a stock" with reconstruction applied from an initial HRB towards a new medium-high building, for which we developed the workflows using the toolchain.
Step 3: Exportation Towards the Material Bank and Just-In-Time Circular Flow After creating the necessary parameters for reuse, we transferred the information to a database. Then export of the structural and environmental parameters contained in the digital mockup to the chosen database, Microsoft SQL, is performed. A BIM software extension is developed in Visual Studio to export the parameters, and to create the first gateway between the model and the database. The realization of such an extension is possible thanks to the existence of the BIM software API. We detailed these developments in Figure  6. To retrieve all the information entered, the extension, developed entirely in C#, realizes a filter according to the existing category in BIM software: BuiltInCategory. OST_StructuralColumns, BuiltInCategory.
OST_StructuralFraming, etc. , using logical filters, LogicalOrFilter. In practice, buttons are created and integrated into the BIM software ribbon, so that pressing them produces what is called an external command. The connection to Microsoft SQL is made directly in the BIM software extension, by writing parameters to the database. A division into several tables according to the type of the element (column, beam, sail or plate) is implemented when writing to the database. This chain of tools could be generalized to an entire territory within the framework of political incentives such as the French government's roadmap for a circular economy.
Step 4: Proof of Concept The aim is to produce a functional toolchain that allows an exhaustive generalization afterwards. When a structural engineer designs a project, she/he models the load-bearing elements on finite element software to execute the calculation model. Thus, in our methodology, this finite element software is then used to query the database to find a reusable load-bearing element and to incorporate it into the model. The database hosts reuse elements that make up the materials bank. In this way, the model can now include reused elements and replace new elements. Choosing a reused element means choosing an element that is oversized compared to the new one, either for lack of choice or for safety reasons. For this first request application, we established certain limitations.
To prove that the proposed approach is feasible, we limit the ULS check to axial forces (pure traction and compression). This method provides results for the two scenarios presented above. The scenario "design from a stock" allows reusing 100% of the elements by adjusting the design to the available stock. The possible variants have the following characteristics in Table  2. We made adjustments to the toolchain for the scenario "design with a stock". We developed an algorithm to perform a database query that allows the comparison between the stock table and the results (of the constraints determined in the building being designed). We then evaluated the best choice for replacing the columns of the model (of the building being designed) with reused elements.
To prove that the proposed approach is feasible, we limit the ULS check to axial forces (pure traction and compression). This method provides results for the two scenarios presented above. The scenario "design from a stock" allows reusing 100% of the elements by adjusting the design to the available stock. The possible variants have the following characteristics in Table  2. We made adjustments to the toolchain for the scenario "design with a stock". We developed an algorithm to perform a database query that allows the comparison between the stock table and the results (of the constraints determined in the building being designed). We then evaluated the best choice for replacing the columns of the model (of the building being designed) with reused elements. During a query, the user can determine the margin of tolerance.
However, the limited stock relating to a single original building is not suitable for a new "Design with a stock" scenario. The new reversible medium-high building standard has spans and ceiling heights that require particular load-bearing elements. A more classical building with the same office function would be able to integrate more reused elements. However, an enlarged and generalized stock for territory would allow a more excellent choice and would avoid such a considerable oversizing. Despite this significant oversizing of +12% in mass, there is a gain on environmental impacts, compared to a new variant of Building B. When the final structure integrating a maximum of reused elements is fixed, new modeling on the software can be carried out and, in turn, feed the material bank database.
Discussion This study sets up the tool suite to allow the transfer of structural properties between the BIM modeling software, the structural calculation software and a database hosting the ready-to-reuse materials bank. The accuracy of the properties attached to the BIM objects allows us to perform a finer LCA. With this toolchain and the database, the structural engineer's competence is now to control and reduce the environmental impact. Two cases are to be apprehended: the restrictive database or the almost unlimited database. In the case of the massification of reuse, the unlimited database is plausible and expected. The establishment of such a bank at the national level would generate a supply of materials more compatible with the real demand for current projects. Different points are discussed in the following parts.
Database Maintenance This article introduced a parametric BIM-workflow and database that should be accessible and interoperable throughout the lifetime of the buildings, up to hundreds of years. Software maintenance during such a long period is a critical issue, as there is little return on experience on this topic in the construction industry. However, some industries are already facing these challenges. For example, on-board software in a spacecraft or an extra-terrestrial rover should remain operational at any time, which brings the obligation to assemble a team devoted to software maintenance  [73]. The cost of such maintenance cannot be avoided in the reuse of buildings and may be very high in the long run. Two main options are available:.
• Second, the BIM model and database rely fundamentally on proprietary software. Private actors perform maintenance. Both options have their advantages and associated risks. For open-source solutions, the appearance of different branches is highly likely for a long-term project, which means that interoperability in practice becomes harder and harder to achieve. For proprietary solutions, this issue is less problematic, but the appearance of a monopolistic private software editor taking maintenance in charge is a risk that cannot be neglected. Finally, the central learning from this remark is that the BIM-Workflow and database should remain as simple as possible, to ease maintenance. The inflation of BIM complexity should be regarded with concern, as it also has an environmental impact that is not yet evaluated.
BIM-LCA Workflows and Generative Design Recent studies have dealt with the automation of the exchanges between BIM and LCA, allowing a reactive LCA to design changes. But the lack of data for initial LCA approaches during the early phases of a project needs to be improved. In general, better interoperability between all BIM and LCA software is still expected  [10, 30, 74]. BIM is a data source for LCA-and in the same way that parametric design has been developed for design-a parametric LCA  [75]  would be linked to the BIM model to enable immediate consideration of model changes in terms of environmental impacts. In this way, we could estimate the impact of different structural design options. Developments to integrate deconstruction plans with long-term tracked data would facilitate the anticipation of reuse.
Conclusions and Perspective This study has demonstrated the practical application of reuse through applied case studies with a suite of tools and constitute guidelines for practitioners. The constructive arrangements and structure typology feed the design for reuse (DfReu) concept, which is also based on a BIM framework and complete traceability defined in this study. The study is limited for the time being to the use of passive data, i. e. , data entered during the design and execution phases. A certain number of data are variables during the life of the structure, and other data are generated during the operation phase. Thus, the methodology did not integrate the possibility of having data emitted by sensors, for example. Another challenge is to link data from data acquisition systems, sensors, laser scan, drones, during the monitoring of buildings to evaluate the real-time impacts.
The toolchain presented and tested in this paper can be extended to a national practice in order also to benefit from a territory-wide pooled stock of elements. Moreover, this process is generalizable and adaptable for all BIM software, which would give more extensive access to the methodology proposed in this paper. The generalization of the stock would also increase the number of elements available for reuse. We had to make simplifications in terms of queries for the calculation model. The next part of the research is to make possible queries integrating more complex requests (such as compound bending). Another avenue for our future research is an adaptation of the LOD and LOI 600 and 700 of the BIM to LCA. Thus, a correlation between the BIM data of the project with their respective LOI levels in terms of environmental information and the data in the LCA database could generate LCA levels in first approaches at the beginning of the design.
We argue that computational conflict research, i. e. , the use of computational approaches to study conflict, can advance conflict research through at least three major innovative pathways: 1. The identification of spatio-temporal dynamics and mechanisms behind conflicts through simulation models that allow to track the interaction of actors in conflict scenarios and to understand the emergence of aggregated, macro-level consequences. 2. The availability of new, fine-grained datasets of conflict events at all scales from the local to the global ("big data") that have become available through digitization together with novel techniques in the computer age to collect, store, and analyze such data. 3. The combination of these simulation and other advanced computational methods with this vast, fine-grained empirical data.
The chapter "Non-state Armed Groups" uses both a large-scale dataset and draws on simulation techniques and is thus placed toward the center of the horizontal axis. Although this two-dimensional representation is of course quite simple-and perhaps even simplistic-it should in theory be possible to place any research conducted in the field of computational conflict research-including the studies discussed in Sect. 3-somewhere in this space. We thus hope this representation may prove to become a useful heuristic for the field. By bringing together novel research by an international team of scholars from a range of fields, this book strives to contribute to consolidating the emerging field of computational conflict research. It aims to be a valuable resource for students, scholars, and a general audience interested in the prospects of using computational social science to advance our understanding of conflict dynamics in all their facets.
Harking back to the weather analogy, the nature and shape of weather distributions certainly play a central place in meteorology. Examining descriptive data on such distributions can help us keep track of how some places have more foul weather than others, and provides a basis for evaluating the possible causes why. Against this more stringent yardstick, comparative data on conflict are a relative recent development in the long history of conflict research. It remained until recently largely a fringe activity, perhaps in part as a result of policy orientation and aversion to statistics and quantitative methods among many traditional security studies scholars (see, e. g. ,  Fazal 2016). One of the earliest datasets was collected by a sociologist,  Sorokin (1957 Sorokin ( [1937]] ), who sought to use data to test his theory of conflict as a result of value divergence.
With comprehensive information on the dates on key battles and troop sizes since antiquity, Sorokin's data were a major achievement. However, some features also limited their applicability. As the data were restricted to conflict between major powers, they could not speak to conflicts within states or conflicts with smaller powers. There is also no clear delineation of what makes states major powers, and a risk of circularity if influence for conflict is defined based on whether states tend to fight more. Wright (1942 Wright ( /1965 ) developed another influential dataset, intended to test a theory of peace as a result of active interstate organization and coordination that served to constraint possible factors that may lead to conflict if left unchecked. Although these data cover a shorter period than Sorokin's, they also included a more comprehensive delineation of states involved in conflict.
Wright also devoted a great deal of attention to developing clear inclusion criteria for the data collection efforts. Given his background in law, it is perhaps not surprising that the definitions were skewed towards legal conceptions of war, but his efforts and structured approach had a major influence on subsequent efforts to define war. The most unusual data pioneer was  Richardson (1960) , a physicist who sought to identify a dataset of violent events to assist with more fundamental mathematical and statistical models of conflict. Richardson started to work collecting conflict data after World War I, but the data were not published until much later. Richardson's unit of analysis was deadly quarrels, based only on observable deaths. The incidents were classified by their severity in terms of fatalities, binned by "orders-ofmagnitude" on a log10 scale.
This has in turn led to new interest in using network approaches to understand how individual states are embedded in larger networks of interdependence beyond the dyad, as well as new methods for dealing with temporal and spatial interdependence in statistical analyses  (Beck et al. 1998; Kinne 2009). Van Holt et al. (2016)  conduct a more formal analysis of scientific influence in conflict research based on citation patterns. Their findings are visualized in terms of paths between influential articles and common topics in Fig. 3. It is clear from Fig. 3  that many of the influential articles in the graph on interstate conflict are precisely those that describe new dataset or analytical methods. Notable examples include  Jaggers and Gurr (1995, introducing  the Polity democracy data prominent in studies of the democratic peace) and  Bremer (1992) , which was one of the first articles to propose systematic approaches to dyadic analysis of the onset of Militarized Interstate Disputes  (Jones et al.
For example,  Zammit-Mangion et al. (2012)  use models from geostatistics to model high resolution data on events in Afghanistan, obtained from Wikileaks, on a database of Significant Activities (SIGACTS) compiled by the US Army. They argue that this framework can be helpful for detecting and predicting conflict dynamics such as diffusion and relocation. The model seems to have high predictive ability, but on closer inspection it becomes clear that much of the heavy lifting in the predictive ability is done by the temporal lags. There is also a discernible "ring" in the spatial forecasts of location, which appears to reflect how improvised explosive devices tend to be placed around the Highway 1/Ring Road that circles the country. Ultimately, the model has limited content on the motivation of the actors, and the framework deemphasizes conflict as interaction between antagonists.
Even worse, there is plausibly an inverse relationship between size and granularity in some data sources. The Social Conflict Analysis Data (SCAD) provides a much used event dataset, which extends data on exclusively violent conflict and data limited to large-scale organized non-violent campaigns by providing more detailed event data on social conflict as well as geographical location information  (Salehyan et al. 2012). However, many events in the SCAD data are coded as nationwide, where the number of simultaneous events across a country is deemed to be so large that coders can no longer identify exhaustively all the individual events. The nationwide events are likely to have more participants than smaller events that are easy to identify as discrete events, yet analysts counting events may count the former as "less significant" since it is reflected in fewer event counts.
It is difficult to predict-especially about the future. I make no claim to be able to predict specific new scientific innovations or salient new topics with much confidence, but I am very confident that new data sources and methodologies for data development will figure prominently in a future updated version of a graph of scientific influence in conflict research akin to  Van Holt et al. (2016). Global Database of Events, Language, and Tone (https://www. gdeltproject. org/). Provides access to machine coded event data from electronic sources from 1979 to the present, using the Conflict and Mediation Event Observations (CAMEO) coding scheme. Global Terrorism Database (https://www. start. umd. edu/gtd/). Provides access to data on terrorist attacks since 1970, as well as some supplementary data sources on terrorist group profiles.
Integrated Crisis Early Warning System (https://dataverse. harvard. edu/dataverse/ icews). Daily event data coded from electronic news sources, with actor, event, and location identifiers. Note that the most recent public version of the data has a 1 year embargo. Phoenix [Cline Center Historical Phoenix Event Data] (https://clinecenter. illinois. edu/project/machine-generated-event-data-projects/phoenix-data). Event data for the period 1945-2015, machine coded from 14 million news stories from the New York Times , the BBC Monitoring's Summary of World  Broadcasts (1979 Broadcasts ( -2015) )  and the CIA's Foreign Broadcast Information Service  (1995) (1996) (1997) (1998) (1999) (2000) (2001) (2002) (2003) (2004). Phoenix [Real time Phoenix data] (http://eventdata. utdallas. edu/data. html).
A real time machine coded event dataset complementing the historical data, available from October 2017. Non-violent and Violent Campaigns and Outcomes (https://www. du. edu/korbel/ sie/research/chenow_navco_data. html). Provides access to an influential dataset that also documents non-violent mobilization over maximalist claims on a government. Social Conflict Analysis Database (https://www. strausscenter. org/scad. html). Provides access to event data on protests, riots, strikes, inter-communal conflict, government violence against civilians, and other forms of social conflict not systematically tracked in other conflict datasets. SCAD currently includes information on social conflicts from 1990-2017, covering all of Africa and now also Mexico, Central America, and the Caribbean. Uppsala Conflict Data Program (https://ucdp.
However, applying such procedures can be costly and difficult to implement in many settings. This is why we additionally suggested two cycles of combining dictionary approaches, supervised methods and unsupervised techniques to effectively cross-validate the outcome of these applications. Apart from extensive validation procedures, we believe that transparency in terms of methodological decisions and steps, accessibility to data and replication files as well as open access publications are critical to advance computational methods in conflict research and beyond. While researchers have started to follow these practices in providing online appendices on methodological details and robustness tests and making their replication files publicly available on dataverses, 7 there is still a large number of studies that are rather nebulous about these things, further enforcing the much-discussed replication crisis in the social sciences.
Military Alliance-Formation Dynamics They use data from the Kansas Event Data System (KEDS) on military actions in the Gulf region between 1979 to 1999. The event sequence involves over 200,000 events among 168 nations  (Lerner et al. , 2013a, p. 7). Events are coded as one-mode network events, with nations × nations interactions encoded in time. Additionally, for each event, a weight ranging from  [-10, 10]  encodes the strength of the interaction with positive values indicating friendly interactions and support among the two nations, and negative interactions denoting military aggression. They use the eventnet application to estimate the effects of (balanced) triadic closure on event occurrence. Their results give strong support to balance theory. Moreover, they find that controlling for external alliances no longer yields any additional insights if reciprocity and triadic closure is adequately controlled for in the model  (Lerner et al.
Influencing Dynamics Among EU Parliamentary Chambers  Malang et al. (2018)  examine social influencing dynamics among national parliaments in Europe. They examine the case of the Early Warning System of the EU, where national parliaments in Europe are allowed to veto legislative proposals brought forth by the European Commission. If over one third of the parliaments (or more precisely parliamentary chambers) veto the same proposal, the European Commission is forced to re-evaluate and defend the proposal. Malang et al. (2018)  argue that this vetoing threshold poses an incentive for chambers to influence each other and try to get them to veto the same proposal. They use data from 353 vetoes issued between January 2010 and September 2016 by 39 parliamentary chambers in the EU. Here, not person × person events are examined but chambers × proposals, i.
As the migration debate is one that has existed in the political sphere of Canada and the United States since their founding as nations of immigrants, we test our hypotheses on a wide, contemporary timeframe that captures both liberal and conservative legislatures and executives as well as different waves of migration patterns from a variety of conflicts spanning much of the world. Methodologically, we rely on unsupervised machine learning for our analysis of text data. The availability of the legislative speeches in easily accessible digital form and the computational power necessary for the analysis of large datasets at hand have jointly led to a surge of interest in analysis using automated text analysis techniques (see also Maerz and Puschmann in the chapter "Text as Data for Conflict Research: A Literature Survey" of this volume).