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Progress in the R Ecosystem for Representing and Handling Spatial Data
Journal of Geographical Systems https://doi.org/10.1007/s10109-020-00336-0 ORIGINAL ARTICLE Progress in the R ecosystem for representing and handling spatial data Roger S. Bivand1 Received: 9 October 2019 / Accepted: 8 September 2020 © The Author(s) 2020 Abstract Twenty years have passed since Bivand and Gebhardt (J Geogr Syst 2(3):307–317, 2000. https ://doi.org/10.1007/PL000 11460 ) indicated that there was a good match between the then nascent open-source R programming language and environment and the needs of researchers analysing spatial data. Recalling the development of classes for spatial data presented in book form in Bivand et al. (Applied spatial data analysis with R. Springer, New York, 2008, Applied spatial data analysis with R, 2nd edn. Springer, New York, 2013), it is important to present the progress now occurring in representation of spatial data, and possible consequences for spatial data handling and the statistical analysis of spatial data. Beyond this, it is imperative to discuss the relationships between R-spatial software and the larger open-source geospatial software community on whose work R packages crucially depend. Keywords Spatial data analysis · Open-source software · R programming language JEL Classifcation C00 · C88 · R15 1 Introduction While Bivand and Gebhardt (2000) did provide an introduction to R as a statistical programming language and to why one might choose to use a scripted language like R (or Python), this article is both retrospective and prospective. It is possible that those approaching the choice of tools for spatial analysis and for handling spatial data will fnd the following less than inviting; in that case, perusal of early chapters of Lovelace et al. -
Jaarregister 2005 HOV-Railnieuws
Jaarregister 2006 HOV-Railnieuws Jaargang 49 versie 12.0 N.B. 1) de cijfers vóór de haakjes verwijzen naar bladzijnummer(s), 2) de cijfers tussen de haakjes verwijzen naar het editienummer. ( Indien op- of aanmerkingen, mail naar: [email protected] of: [email protected] ) Deel 1: Stads- en regiovervoer: tram, sneltram, light rail, metro en bus Aachen (= Aken) 345-346(574) Adelaide 49(566), 313-314(573) Albtalbahn 285(572) Alexandrië 94(567) Algerije 91(567), 275(572), 313(573) Algiers 91(567), 275(572), 313(573) Alicante 387(575) Almaty 417(576) Almere connexxion 89(567) Alstom Transport 316(573) Ameland 126(568) Amsterdam 3-5(565), 41-43(566), 83-84(567), 121(568), 121-122(568), 159-162(569), 197-200(570), 233(571), 268-270(572), 307- 308(573), 335-339(574), 343(574), 377-378(575), 408- 411(576) Amsterdam gemeentebestuur 161(569) Amsterdam gratis OV 161(569), 307(573) Amsterdam infrastructuur 270(572), 308(573) Amsterdam koninginnedag 2006 161-162(569) Amsterdam Leidseplein 83-84(567) Amsterdam museumtramlijn 159(569), 162(569), 199(570), 233(571), 270(572), 308(573), 339(574) Amsterdam nieuw lijnennet 121(568) Amsterdam Noord-Zuidlijn 3(565), 41-42(566), 83(567), 161(569), 199(570), 233(571), 269(572), 307-308(573), 335(574), 336(574), 409-410(576) Amsterdam openbaar-vervoermuseum 3(565), 43(566), 122(568), 339(574) Amsterdam OV-politie 121-122(568) Amsterdam stadsmobiel 162(569) Amsterdam vandalisme 162(569) Amsterdam Weteringcircuit 161(569) Amsterdam Zuidas 409(576) Amsterdam zwartrijden in metro 269(572) Angers 279(572) -
Netznachrichten
NetzNachrichten September 2016 | Ausgabe 3/16 Informationen für Kunden der DB Netz AG und Interessierte InfraDialog 2016 iDIS zeigt das ganze Netz Pünktlichkeits-Task-Force DB Netz, DB Station& Ser vice und DB Innovativ und schnell: Die Einführung Der Einsatz von Knotenkoordinatoren Energie laden zur Kundenveranstal- des „integrierten Dispositionssystems“ für Fernzüge wirkt sich auch positiv auf tung am 3. November in Mainz ein. S. 2 erhöht die Betriebsqualität. S. 4 Nah- und Güterverkehre aus. S. 7 Weiterentwickeltes TPS geht an den Start Stellungnahmeverfahren und Marktkonsultationen laufen / Einführung erfolgt im Dezember 2017 ufgrund der neuen EU-Richtlinie 2012/34 TPS 2017: Schritte der Umsetzung A zur Schaffung eines einheitlichen euro- päischen Eisenbahnraums führt die DB Netz AG zum Fahrplanwechsel im Dezember 2017 Anfang September ca. 10. Oktober 11. Dezember NFP Wechsel 2016 das weiterentwickelte Trassenpreissystem 2016 2016 2017/2018 (TPS) ein. Die Basis dafür bildet das im Juli Marktkonsultation* verabschiedete Eisenbahnregulierungsgesetz 09.09. Berlin (ERegG). Mit dem weiterentwickelten TPS Veröffentlichung SNB inkl. 12.09. Frankfurt a. M. Übermittlung SNB & Veröffentlichung SNB Einführung Entgeltliste zur Stellungnahme 14.09. München Entgeltliste zur inkl. Entgeltliste TPS 2017 etabliert DB Netz eine neue Entgeltlogik, die durch Zugangsberechtigte Genehmigung an BNetzA aus zwei Kernbausteinen besteht: den unmit- (1 Monat) (2 Monate) telbaren Kosten des Zugbetriebs und einem *Nachholen der für Anfang Juli vorgesehenen Marktkonsultation Aufschlag, der sich aus den relativen Tragfä- higkeiten der jeweiligen Marktsegmente herlei tet. Weitere Elemente können hinzu- ERegG im Bundestag, einen Tag später auch 2017/18 die Trassenpreise im SPNV jährlich kommen. im Bundesrat verabschiedet. Das Gesetz führt nur noch um 1,8 Prozent erhöhen. -
Inhaltsverzeichnis
Anlage 1 zur Vorlage 06136-16 Ergebnisse des Dialog- und Beteiligungsverfahrens Inhaltsverzeichnis 1. Neue Instrumente und Methoden ..................................................................................... 2 1.1 Instrumente für Beteiligung und Dialog .................................................................... 2 1.2 Instrumente zur Projektentwicklung und Qualitätssicherung ............................... 4 1.3 Mobilisierung von Ressourcen ................................................................................... 5 2. Bericht aus den „Nordwärts“-Projektgremien................................................................ 6 2.1 Kuratorium .................................................................................................................. 6 2.2 Kuratoriumsvorstand .................................................................................................. 6 2.3 Strategiekreise .............................................................................................................. 6 2.4 Verwaltungskooperation ............................................................................................. 7 2.5 Arbeitsgruppen ............................................................................................................ 7 3. Neue Projekte der 2. Generation seit 01.01.2016 ............................................................. 7 4. Projektveränderungen der 1.-3. Projektgeneration ...................................................... 11 5. Öffentlichkeitsarbeit/Veranstaltungen -
R Generation [1] 25
IN DETAIL > y <- 25 > y R generation [1] 25 14 SIGNIFICANCE August 2018 The story of a statistical programming they shared an interest in what Ihaka calls “playing academic fun language that became a subcultural and games” with statistical computing languages. phenomenon. By Nick Thieme Each had questions about programming languages they wanted to answer. In particular, both Ihaka and Gentleman shared a common knowledge of the language called eyond the age of 5, very few people would profess “Scheme”, and both found the language useful in a variety to have a favourite letter. But if you have ever been of ways. Scheme, however, was unwieldy to type and lacked to a statistics or data science conference, you may desired functionality. Again, convenience brought good have seen more than a few grown adults wearing fortune. Each was familiar with another language, called “S”, Bbadges or stickers with the phrase “I love R!”. and S provided the kind of syntax they wanted. With no blend To these proud badge-wearers, R is much more than the of the two languages commercially available, Gentleman eighteenth letter of the modern English alphabet. The R suggested building something themselves. they love is a programming language that provides a robust Around that time, the University of Auckland needed environment for tabulating, analysing and visualising data, one a programming language to use in its undergraduate statistics powered by a community of millions of users collaborating courses as the school’s current tool had reached the end of its in ways large and small to make statistical computing more useful life. -
Folgende Stores Sind Auch Weiterhin Für Euch Geöffnet!
FOLGENDE STORES SIND AUCH WEITERHIN FÜR EUCH GEÖFFNET! BERLIN BERLIN BAHNHOF ALEXANDERPLATZ: Mo bis Fr 6:00 - 22:00 Uhr / Sa und So 7:00 - 22:00 Uhr BERLIN BAHNHOF SPANDAU: Mo bis Fr 6:00 - 21:00 Uhr / Sa 7:00 - 21:00 Uhr / So 8:00 - 21:00 Uhr BERLIN BAHNHOF FRIEDRICHSTRASSE: Mo bis Fr 6:00 - 21:00 Uhr / Sa 7:00 - 21:00 Uhr / So 8:00 - 21:00 Uhr BERLIN GESUNDBRUNNEN CENTER: Mo bis Sa 8:00 - 20:00 Uhr / SONNTAG GESCHLOSSEN BERLIN HAUPTBAHNHOF: Mo bis So 8:00 - 21:00 Uhr BERLIN HERMANNPLATZ: Mo bis Sa 8:00 - 20:00 Uhr / So 10:00 - 20:00 Uhr BERLIN KAISERDAMM: Mo bis Fr 9:00 - 20:00 Uhr / Sa und So 10:00 - 20:00 Uhr BERLIN OSTBAHNHOF: Mo bis Fr 7:00 - 21:00 Uhr / Sa und So 8:00 - 21:00 Uhr BERLIN RATHAUSPASSAGEN: Mo bis So 8:00 - 22:00 Uhr BERLIN RING CENTER: Mo bis Sa 8:00 - 21:00 Uhr / So 10:00 - 18:00 Uhr BERLIN SONY CENTER: Mo bis So 8:00 - 21:00 Uhr BERLIN WILMERSDORFER: Mo bis Sa 8:00 - 20:00 Uhr / So 10:00 - 18:00 Uhr BERLIN ZOOM: Mo bis So 7:00 - 22:00 Uhr / Sa und So 8:00 - 22:00 Uhr 1/4 NRW DORTMUND HAUPTBAHNHOF: Mo bis So 6:00 - 21:00 Uhr DÜSSELDORF HAUPTBAHNHOF: Mo bis So 6:00 - 21:00 Uhr ESSEN HAUPTBAHNHOF: Mo bis So 6:00 - 20:00 Uhr KÖLN HAUPTBAHNHOF: Mo bis So 7:00 - 21:00 Uhr WUPPERTAL HAUPTBAHNHOF: Mo bis So 10:00 - 18:00 Uhr KÖLN SCHILDERGASSE: Mo bis Sa 9:00 - 20:00 Uhr SONNTAGS GESCHLOSSEN RHEIN-MAIN FRANKFURT HAUPTBAHNHOF: Mo bis So 6:00 - 21:00 Uhr MAINZ HAUPTBAHNHOF: Mo bis So 9:00 - 20:00 Uhr HESSEN WIESBADEN: Mo bis So 9:00 - 20:00 Uhr FFM ZEIL: Mo bis So 10:00 - 20:00 Uhr 2/4 BAYERN / BADEN-WÜRTTEMBERG MÜNCHEN OEZ: -
Data Analysis in R
Data Analysis in R Course at a Glance This course will provide an introduction to reproducible data analysis with R (see Syllabus). Instructor Gabriel Baud-Bovy ([email protected] ) Credits: 5 Synopsis This course aims at giving to the student a methodology to analyze experimental results, from how to organize data to the writing of a report. It includes: an introduction to R an introduction to reproducible research with R examples of statistical analysis with R During this course, the student will have to analyze his own data and is expected to read before each course the material that will be made available on this page. The final grade will consist in the evaluation of a report demonstrating familiarity with the concepts and methods presented in the course. As an editor, the instructor will use Notepad++ (together with NppToR) on a Windows Machines but the student might use other ones (e.g., R studio, EMACS+ESS, Lyx, TexWork). The course will use Mardown as typesetting language. For those desirous to work with Latex and/or generate pdf, you will need to install also MikeTex. Syllabus Total of 15 hours Class 1: Case study, Reproducible research Class 2: R fundamental Class 3: Exploratory data analysis and graphical methods in R Class 4: Basic statistics Class 5: To be determined There will be a final examination decided by the instructor. Prerequisites The course assumes some familiarity with programming concepts and data structures (MATLAB, C/C++, Java or any other programming language). Contact the instructor if you have never programmed anything. -
A History of R (In 15 Minutes… and Mostly in Pictures)
A history of R (in 15 minutes… and mostly in pictures) JULY 23, 2020 Andrew Zief!ler Lunch & Learn Department of Educational Psychology RMCC University of Minnesota LATIS Who am I and Some Caveats Andy Zie!ler • I teach statistics courses in the Department of Educational Psychology • I have been using R since 2005, when I couldn’t put Me (on the EPSY faculty board) SAS on my computer (it didn’t run natively on a Me Mac), and even if I could have gotten it to run, I (everywhere else) couldn’t afford it. Some caveats • Although I was alive during much of the era I will be talking about, I was not working as a statistician at that time (not even as an elementary student for some of it). • My knowledge is second-hand, from other people and sources. Statistical Computing in the 1970s Bell Labs In 1976, scientists from the Statistics Research Group were actively discussing how to design a language for statistical computing that allowed interactive access to routines in their FORTRAN library. John Chambers John Tukey Home to Statistics Research Group Rick Becker Jean Mc Rae Judy Schilling Doug Dunn Introducing…`S` An Interactive Language for Data Analysis and Graphics Chambers sketch of the interface made on May 5, 1976. The GE-635, a 36-bit system that ran at a 0.5MIPS, starting at $2M in 1964 dollars or leasing at $45K/month. ’S’ was introduced to Bell Labs in November, but at the time it did not actually have a name. The Impact of UNIX on ’S' Tom London Ken Thompson and Dennis Ritchie, creators of John Reiser the UNIX operating system at a PDP-11. -
Checkliste Für ERASMUS
Checklist for ERASMUS Students (Incomings) What do I have to do prior to my arrival in Dortmund? After receiving the Welcome – E-mail be sure to arrange your journey to Dortmund early enough. Please consider arriving in Dortmund from Monday to Friday between 8 am and 4 pm. In case of an arrival at a later date or on a weekend, you will need to arrange another accommodation for the first day(s). A rather cheap possibility is the youth hostel “Jugendgästehaus Adolph Kolping” (http://www.djh-wl.de/jh/dortmund/). Further information for your journey and directions can be found at the end of this checklist. Please inform your departmental coordinator and me about the exact date and time of your arrival at TU Dortmund University as soon as possible. It is the only way to ensure that the corresponding arrangements for your pick-up service will be organized in time. ACCOMMODATION: TU Dortmund University offers accommodation in several dorms. These include different places on campus and the BfW, a dorm 5km off campus. The dorms on campus are furnished rooms in flats and apartments with kitchen, bathroom and shared facilities. You will receive a starter packet (containing a pillow, blankets and sheets as well as basic kitchen supplies). The rent will average 250 € per month (including bills and internet). The BfW is located in the southern district Hacheney next to Dortmund’s Rombergpark. You can get to university from here within about 40 min. by public transport. The single apartments are furnished and include a private bathroom and balcony as well as a shared kitchen. -
Models for Sustainable Development
Dissertation zur Erlangung des Grades Doktor-Ingenieur des Fachbereiches Bauingenieurwesen der Bergischen Universität Wuppertal METHODOLOGY AND STATISTICAL ANALYSIS OF SUSTAINABLE TRANSPORTATION CRITERIA FOR CERTIFICATION SYSTEMS vorgelegt von M.Sc. Amin Zeinal Hamedani Wuppertal, April 2014 Die Dissertation kann wie folgt zitiert werden: urn:nbn:de:hbz:468-20141007-112314-8 [http://nbn-resolving.de/urn/resolver.pl?urn=urn%3Anbn%3Ade%3Ahbz%3A468-20141007-112314-8] A Executive Summary Executive Summary Achieving sustainability has become one of the fundamental goals of many urban transportation systems in the past two decades. The emerging concept of sustainability has developed enormous interests among researchers and practitioners to develop a sustainable transport system. While many have focused on developing an appropriate definition of a sustainable transport by measures and indicators of sustainability to assess if a transport system is moving towards or away from sustainability, many others have put forward different strategies to make a transport system sustainable. Defining sustainable transport and identifying indicators are important to make this concept more correct, focused, and measurable. This study tries to measure and monitories urban transportation sustainability from viewpoint of an urban planner. The question comes out from the relation between urban transportation sustainability and usage of public transportation. How these two facts link to each other? Are there any logical relations between usage of public transportation and sustainable development? How we can define specific indicator for measuring sustainability of transportation or on the other words, how can we standardized indicator to measure and monitor the urban sustainable transportation? For response, exceeding questions two cities are selected which have a similarity and differences in structure and data sets. -
Anreiseskizze 2004-09-13 Englisch.Cdr
Your way to the Universität Dortmund MÜNSTER LÜNEN BREMEN A A B 4 2 AB-Kreuz 1 AB-Kreuz 3 AB-Kreuz 3 Recklinghausen DO - Nordwest 6 Kamen OBERHAUSEN A 2 A 2 A 2 HANNOVER A AB-Kreuz 4 AB-Kreuz DO - Castrop- 5 Herne Rauxel-Ost GELSENKIRCHEN A 42 Ausfahrt AB-Kreuz AB-Kreuz AB-Kreuz DO-Dorstfeld DO/Unna Bochum DO - West Universität ESSEN A 40 B 1 A 44 KASSEL AB-Kreuz AB-Kreuz Ausfahrt Ausfahrt Bochum/Witten DO/Witten DO-Eichlinghofen DO-Hombruch Universität BOCHUM A 44 4 A 45 3 FRANKFURT 5 4 1 B A A HAGEN WUPPERTAL KÖLN By Car The campus of the Universität Dortmund is situated close to the motorway intersection Dortmund West, where the Sauerlandlinie A 45 (Frankfurt- Dortmund) crosses the Ruhrschnellweg B 1 / A 40. That's how the university is connected to the west with the motorway network of the Ruhr Area and beyond that to the regions of the Lower Rhine and the Netherlands. In the eastern direction the B 1 leads through Dortmund to Unna, where there is a connection with the motorways leading to Bremen, Hannover/Berlin and Kassel. In the north, the A 45 ends after a few kilometres at the A 2, leading to the Kamener Kreuz and in the other direction to Oberhausen. In the Westhofener Kreuz, south of the university, the A 45 crosses the A 2, leading to Bremen and Köln. The best motorway exit you find on the A 45 is "Dortmund-Eichlinghofen" (closer to the Campus Süd) and on the B 1 / A 40 "Dortmund-Dorstfeld" (closer to the Campus Nord). -
Conference Brochure S P E a K E R S
04.07.2017 – 07.07.2017 www.user2017.brussels @useR_Brussels #user2017 CONFERENCE BROCHURE S P E A K E R S 2 As a student my use of R for data analyses was frowned upon - the suggestion was to stick with the existing software. P Access to R related literature was difficult. To admire R the very first R books one had to travel far, to the few enlightened universities. As a researcher I needed the help E of a secret floppy disk to dual boot into a GNU/Linux system with R, in order to escape from unnamed products. As a F starter in industry, people from unnamed companies made clear to my management that setting up R events for customers was A giving a ‘wrong signal to the market’. C Look how ‘wrong’ we have been... Fifteen years later R is shining brightly in the data science field. Students are E learning R before anything else and if statistics research is published without accompanying R package, it is considered a bad sign. Publishers have hundreds of books on display and major software houses are in a constant race against time to further integrate R into their product offerings. And now, more than 1000 people from all over the world have come to Brussels to discover the state of R at this conference. R has come a great way and the community that formed around the R project is and has always been critical to its success. The community has evolved in many ways and is active in many places throughout the year, but of all things the official useR conference still is the major community event of the year.